{"id": "subworkflow_pkg_fastq_qc_trim_filter_setstrandedness_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS", "modules": ["bbmap/bbsplit", "cat/fastq", "fastqc", "fq/lint", "fastq_remove_rrna", "fastq_subsample_fq_salmon", "fastq_fastqc_umitools_trimgalore", "fastq_fastqc_umitools_fastp"], "description": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files, preparing them for downstream analysis."}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS (bbmap/bbsplit, cat/fastq, fastqc, fq/lint, fastq_remove_rrna, fastq_subsample_fq_salmon, fastq_fastqc_umitools_trimgalore, fastq_fastqc_umitools_fastp) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS": null, "Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_4_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end oncology RNA-seq reads for chimeric transcript discovery?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fusion_bed": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "resource_bedtools_coverage_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COVERAGE", "tool": "bedtools/coverage", "description": "computes both the depth and breadth of coverage of features in file B on the features in file A"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COVERAGE (computes both the depth and breadth of coverage of features in file B on the fea) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_5_2", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness", "pipeline": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/riboseq, determine the input samplesheet column structure for: Ribosome profiling (Ribo-seq) footprint sequencing.", "criteria": {"sample,fastq_1,strandedness": null, "sample,bam": null, "sample,cdna_fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "mod_isoseq_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: IsoSeq - Cluster - Cluster trimmed consensus sequences (tools: isoseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq_cluster": null, "paraclu": null, "mat2json": null, "clusty": null, "trycycler_subsample": null}}, "target": "isoseq_cluster", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_2", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_sawfish_jointcall_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Joint calling of structural variants from multiple samples using Sawfish (tools: sawfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sawfish_jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "sniffles": "structural-variant calling with sniffles", "plink2_score": "Apply a scoring system to each sample in a plink 2 fileset", "saltshaker_plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "cobs_compactconstruct": "Builds a compact bloom filter COBS index"}}, "target": "sawfish_jointcall", "target_idx": 0}
{"id": "subworkflow_pkg_bam_dedup_umi_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_UMI", "modules": ["umitools/prepareforrsem", "samtools/sort", "bam_dedup_stats_samtools_umicollapse", "bam_dedup_stats_samtools_umitools", "bam_sort_stats_samtools"], "description": "BAM deduplication with UMI processing for both genome and transcriptome alignments"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_UMI (umitools/prepareforrsem, samtools/sort, bam_dedup_stats_samtools_umicollapse, bam_dedup_stats_samtools_umitools, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow BAM_DEDUP_UMI": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_dedup_umi": null}}, "target": "Use nf-core subworkflow bam_dedup_umi", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_bracken_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2_BRACKEN", "modules": ["kraken2/add", "kraken2/build", "bracken/build"], "description": "KRAKEN2 and BRACKEN build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2_BRACKEN (kraken2/add, kraken2/build, bracken/build) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTA_BUILD_ADD_KRAKEN2_BRACKEN": null, "Use nf-core subworkflow fasta_build_add_kraken2_bracken": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2_bracken", "target_idx": 2}
{"id": "mod_shinyngs_staticdifferential_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make plots for interpretation of differential abundance statistics (tools: shinyngs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anota2seq/anota2seqrun": null, "shinyngs/staticdifferential": null, "dotseq/dotseq": null, "lima": null, "viennarna/rnafold": null}}, "target": "shinyngs/staticdifferential", "target_idx": 1}
{"id": "schema_std_genomeqc_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeqc", "description": "Compare the quality of multiple genomes, along with their annotations.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/genomeqc?", "criteria": {"fasta,assembly,ncbi,gff,fastq": null, "sample,bundle,image": null, "sample,fastq_1,fastq_2,rundir,tags": null, "patient,sample,vcf,status,cna": null}}, "target": "fasta,assembly,ncbi,gff,fastq", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_24", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_abritamr_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes (tools: abritamr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "carveme_carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "gatk4_createsomaticpanelofnormals": "Create a panel of normals constraining germline and artifactual sites for use with mutect2."}}, "target": "abritamr_run", "target_idx": 0}
{"id": "resource_bacphlip_5", "category": "resource_profiling", "state": {"process": "BACPHLIP", "tool": "bacphlip", "description": "A bacteriophage lifestyle prediction tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACPHLIP (A bacteriophage lifestyle prediction tool) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_trycycler_subsample_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subsample a long-read sequencing fastq file for multiple assemblies (tools: trycycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_subsample_fq_salmon": "Subsample fastq", "bam2fastx_bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "telogator2": "Allele-specific telomere length estimation and TVR characterization from long reads", "trycycler_subsample": "Subsample a long-read sequencing fastq file for multiple assemblies"}}, "target": "trycycler_subsample", "target_idx": 4}
{"id": "mod_ribocode_metaplots_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Set up RiboCode ORF calling with metaplots (tools: ribocode)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode_prepare": "Prepare the annotation files for RiboCode ORF calling", "custom_orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "ribocode_metaplots": "Set up RiboCode ORF calling with metaplots", "abacas": "Contiguate draft genome assembly"}}, "target": "ribocode_metaplots", "target_idx": 3}
{"id": "resource_bcftools_split_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SPLIT", "tool": "bcftools/split", "description": "Split a vcf file into files per chromosome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SPLIT (Split a vcf file into files per chromosome) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_sickle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A windowed adaptive trimming tool for FASTQ files using quality (tools: sickle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "rapidnj": "Produces a Newick format phylogeny from a multiple sequence alignment using a Neighbour-Joining algorithm. Cap", "sickle": "A windowed adaptive trimming tool for FASTQ files using quality", "ariba_getref": "Download and prepare database for Ariba analysis", "pigz_compress": "Compresses files with pigz."}}, "target": "sickle", "target_idx": 2}
{"id": "mod_ilastik_pixelclassification_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. (tools: ilastik)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mash_sketch": "Creates vastly reduced representations of sequences using MinHash", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "pcne": "Estimates plasmid copy number from assembled genome", "numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "ilastik_pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells"}}, "target": "ilastik_pixelclassification", "target_idx": 4}
{"id": "mod_last_mafconvert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts MAF alignments in another format. (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/blastx": null, "last/lastal": null, "last/split": null, "last/mafconvert": null, "lissero": null}}, "target": "last/mafconvert", "target_idx": 3}
{"id": "intent_debug_error_21", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "debug_error": null, "ask_question": null, "build_pipeline": null}}, "target": "debug_error", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_43", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_21", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Multiplexed Oxford Nanopore run with barcode demultiplexing)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "mod_art_illumina_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simulation tool to generate synthetic Illumina next-generation sequencing reads (tools: art)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "meryl_histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "blast_blastdbcmd": "Retrieve entries from a BLAST database", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon"}}, "target": "art_illumina", "target_idx": 0}
{"id": "mod_mapad_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create mapAD index for reference genome (tools: mapad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mapad_map": "Map short-reads to an indexed reference genome", "bowtie_build": "Create bowtie index for reference genome", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "pbmarkdup": "Takes one or multiple sequencing chips of an amplified library as HiFi reads and marks or removes\nduplicates.", "mapad_index": "Create mapAD index for reference genome"}}, "target": "mapad_index", "target_idx": 4}
{"id": "resource_bedtools_shift_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHIFT", "tool": "bedtools/shift", "description": "Shifts each feature by specific number of bases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHIFT (Shifts each feature by specific number of bases) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_grimer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates an interactive HTML dashboard integrating taxonomy,\nannotation, and metadata to detect contamination in metagenomic\nand amplicon sequencing datasets. GRIMER is independent of\nquantification methods and directly analyses contingency tables. (tools: grimer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/combinebrackenoutputs": null, "grimer": null, "bracken/bracken": null, "odgi/draw": null, "khmer/uniquekmers": null}}, "target": "grimer", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_6_5", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns are standard for Environmental community metatranscriptomics de novo assembly input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,bam": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_4_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end low-input fragment FASTQs with target antibody and IgG negative control?", "criteria": {"sample,bam": null, "sample,target,control": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "mod_homer_groseq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.ucsd.edu/homer/ngs/groseq/groseq.html). (tools: homer_groseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkqc": "A simple program to parse Illumina NGS data and check it for quality criteria", "bbmap_clumpify": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates", "gcta_reml": "Run univariate REML heritability estimation with a dense GRM", "homer_groseq": "Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.", "fasta_vclust_prefilter_align_cluster": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter\nof candidate sequence pairs with `v"}}, "target": "homer_groseq", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_48", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_seqkit_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts sequences by id/name/sequence/length (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_sort": null, "agat_spextractsequences": null, "ultra_align": null, "custom_orfnormalise": null, "alignoth": null}}, "target": "seqkit_sort", "target_idx": 0}
{"id": "schema_std_variantbenchmarking_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/variantbenchmarking", "description": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/variantbenchmarking?", "criteria": {"id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,tools,file,index": null}}, "target": "id,test_vcf,test_regions,caller,subsample", "target_idx": 0}
{"id": "field_constraint_phenotype_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 1}
{"id": "mod_jvarkit_sam2tsv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert sam files to tsv files (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_replace": null, "deepvariant": null, "bwa_mem": null, "bwa_samse": null, "jvarkit_sam2tsv": null}}, "target": "jvarkit_sam2tsv", "target_idx": 4}
{"id": "mod_cache_download_ensemblvep_snpeff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: downlad annotation cache for snpeff and ensemblvep (tools: cache_download_ensemblvep_snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr/index": "Indexes a directory of fasta files for use with CoPTR", "salsa2": "SALSA, A tool to scaffold long read assemblies with HiC", "vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file", "snpeff/download": "Genetic variant annotation and functional effect prediction toolbox", "cache_download_ensemblvep_snpeff": "downlad annotation cache for snpeff and ensemblvep"}}, "target": "cache_download_ensemblvep_snpeff", "target_idx": 4}
{"id": "mod_souporcell_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: souporcell is a method for clustering mixed-genotype scRNAseq experiments by individual. (tools: souporcell)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ensemblvep/vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`.", "autocycler/cluster": "Cluster replicons in compressed assemblies with Autocycler.", "comebin/runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "rundbcan/easysubstrate": "Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzyme", "souporcell": "souporcell is a method for clustering mixed-genotype scRNAseq experiments by individual."}}, "target": "souporcell", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_2_38", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_bamtofastq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bamtofastq", "description": "Converts bam or cram files to fastq format and does quality control.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/bamtofastq?", "criteria": {"id,fasta,sequence": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample_id,mapped,index,file_type": null, "sample,fastq_1,fastq_2,strandedness,condition": null}}, "target": "sample_id,mapped,index,file_type", "target_idx": 2}
{"id": "field_constraint_sample_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "format: file-path": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "mod_bismark_methylationextractor_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts methylation information for individual cytosines from alignments. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pindel/pindel": "Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and", "bismark/summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "bismark/align": "Performs alignment of BS-Seq reads using bismark", "deacon/indexintersect": "Intersect multiple deacon indexes (A ∩ B ...)", "bismark/methylationextractor": "Extracts methylation information for individual cytosines from alignments."}}, "target": "bismark/methylationextractor", "target_idx": 4}
{"id": "mod_splitubam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: split one ubam into multiple, per line, fast (tools: splitubam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "shapeit5/phaserare": "Tool to phase rare variants onto a scaffold of common variants (output of phase_common / ligate).\nRequire feat", "splitubam": "split one ubam into multiple, per line, fast", "autocycler/combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "genmod/score": "Score the variants of a vcf based on their annotation"}}, "target": "splitubam", "target_idx": 2}
{"id": "resource_autocycler_trim_0", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_TRIM", "tool": "autocycler/trim", "description": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_TRIM (Trim cluster assembly graphs to remove unsupported segments prior to resolution.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_retry_errorstrategy_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_17", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_mira_influenza_sc2_3_2", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "INPUT_CHECK", "library_inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Custom MIRA-NF Influenza / SC2 pipeline with entry step INPUT_CHECK.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_custom_tabulartogseagct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a TSV or CSV with features by row and observations by column to a GCT format file as consumed by GSEA (tools: tabulartogseagct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/alncompare": null, "seqkit/fx2tab": null, "custom/tabulartogseagct": null, "custom/tabulartogseachip": null, "coptr/index": null}}, "target": "custom/tabulartogseagct", "target_idx": 2}
{"id": "resource_bamutil_trimbam_0", "category": "resource_profiling", "state": {"process": "BAMUTIL_TRIMBAM", "tool": "bamutil/trimbam", "description": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_TRIMBAM (trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality ) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_5_4", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Xenium in situ subcellular spatial RNA transcriptomics.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_16", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_1_4", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_basicpy_5", "category": "resource_profiling", "state": {"process": "BASICPY", "tool": "basicpy", "description": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is developed based on the Matlab version of BaSiC tool with major improvements in the algorithm."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASICPY (BaSiCPy is a python package for background and shading correction of optical mic) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_status_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_0_4", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "mod_svtk_countsvtypes_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Count the instances of each SVTYPE observed in each sample in a VCF. (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtk_vcf2bed": "Converts VCFs containing structural variants to BED format", "svtk_countsvtypes": "Count the instances of each SVTYPE observed in each sample in a VCF.", "pairtools_restrict": "Assign restriction fragments to pairs", "phyloflash": "phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illum", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "svtk_countsvtypes", "target_idx": 1}
{"id": "mod_deeptools_multibigwigsummary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the average scores for each of the files in every genomic region (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "ultra/pipeline": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection", "deeptools/bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "fungtion/fungtion": "Predicts fungal effector proteins from protein FASTA sequences using ESM-1b\nprotein language model embeddings ", "ucsc/bedgraphtobigwig": "Convert a bedGraph file to bigWig format."}}, "target": "deeptools/multibigwigsummary", "target_idx": 0}
{"id": "noul_multiple_script_sections_invalid_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "noul_confusing_combine_with_mix_semantics_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_tabix_bgzip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files (tools: bgzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat_fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "bismark_align": "Performs alignment of BS-Seq reads using bismark", "tabix_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files", "tabix_bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde", "quantmsutils_dianncfg": "Generate DIA-NN configuration arguments from enzyme and Unimod modification parameters.\nThis module uses quant"}}, "target": "tabix_bgzip", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Single-end Oxford Nanopore direct RNA. Input files: Single fastq per sample.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fast5": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_bowtie2_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds bowtie index for reference genome (tools: bowtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscreen_buildfromindex": "Build fastq screen config file from bowtie index files", "sequencetools_pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "atlas_call": "generate VCF file from a BAM file using various calling methods", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs", "bowtie2_build": "Builds bowtie index for reference genome"}}, "target": "bowtie2_build", "target_idx": 4}
{"id": "noul_named_process_output_emits_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_ask_question_20", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 0}
{"id": "noul_retry_errorstrategy_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_smrnaseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A small-RNA sequencing analysis pipeline. Topics: small-rna, smrna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]"}}, "target": "smrnaseq", "target_idx": 3}
{"id": "mod_gangstr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GangSTR is a tool for genome-wide profiling tandem repeats from short reads. (tools: gangstr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_applyvarcal": "Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the sec", "expansionhunter": "Estimate repeat sizes using NGS data", "expansionhunterdenovo_merge": "Merge STR profiles into a multi-sample STR profile", "severus": "Severus is a somatic structural variation (SV) caller for long reads (both PacBio and ONT)", "gangstr": "GangSTR is a tool for genome-wide profiling tandem repeats from short reads."}}, "target": "gangstr", "target_idx": 4}
{"id": "mod_krakenuniq_preloadedkrakenuniq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classifies metagenomic sequence data using unique k-mer counts (tools: krakenuniq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpeff/download": "Genetic variant annotation and functional effect prediction toolbox", "haplogrep2/classify": "classification into haplogroups", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "krakenuniq/preloadedkrakenuniq": "Classifies metagenomic sequence data using unique k-mer counts", "vrhyme/extractunbinned": "Extracting sequences that were unbinnned by vRhyme into a FASTA file"}}, "target": "krakenuniq/preloadedkrakenuniq", "target_idx": 3}
{"id": "mod_xz_decompress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decompresses files with xz. (tools: xz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spring_decompress": "Fast, efficient, lossless decompression of FASTQ files.", "unzipfiles": "Unzip ZIP archive files", "xz_decompress": "Decompresses files with xz.", "circexplorer2_annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse", "ultra_pipeline": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection"}}, "target": "xz_decompress", "target_idx": 2}
{"id": "mod_ngmaster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotyping Neisseria gonorrhoeae assemblies (tools: ngmaster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "ichorcna/run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "ngmaster": "Serotyping Neisseria gonorrhoeae assemblies", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "wisecondorx/newref": "Create a new reference using healthy reference samples"}}, "target": "ngmaster", "target_idx": 2}
{"id": "mod_manta_tumoronly_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. (tools: manta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec_freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "manta_tumoronly": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats", "foldcomp_decompress": "Decompression tool for foldcomp compressed structures", "controlfreec_makegraph": "Plot Freec output"}}, "target": "manta_tumoronly", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_17", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_oarfish_alignmentmode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quantify pre-computed alignments of reads to the transcriptome (a name-sorted BAM, e.g. from minimap2/pbmm2). (tools: oarfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju/mkfmi": "Make Kaiju FMI-index file from a protein FASTA file", "gatk4/gatherbqsrreports": "Gathers scattered BQSR recalibration reports into a single file", "oarfish/alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ascat": "copy number profiles of tumour cells."}}, "target": "oarfish/alignmentmode", "target_idx": 2}
{"id": "resource_amulety_antiberta2_3", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTA2", "tool": "amulety/antiberta2", "description": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTA2 (A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences ) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for ATAC-seq chromatin accessibility with biological replicates. Input files: Paired-end Tn5 transposed FASTQs across conditions and replicates.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "pipe_all101_rnavar_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze gatk4 RNA variant calling pipeline. Topics: gatk4, rna, rnaseq, variant-calling, worflow. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo"}}, "target": "rnavar", "target_idx": 0}
{"id": "resource_bcftools_isec_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ISEC", "tool": "bcftools/isec", "description": "Apply set operations to VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ISEC (Apply set operations to VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_channel_join_operator_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for ATAC-seq chromatin accessibility with biological replicates. Input files: Paired-end Tn5 transposed FASTQs across conditions and replicates.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ATAC-seq chromatin accessibility with biological replicates with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "mod_caddsv_get_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download CADD-SV annotation resources or SegmentNT model files. (tools: caddsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx/preparedepthofcoverage": null, "caddsv/get": null, "genometester4/glistmaker": null, "caddsv/run": null, "annotsv/annotsv": null}}, "target": "caddsv/get", "target_idx": 1}
{"id": "noul_single_hyphen_cli_params_error_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_phase_shapeit5_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_PHASE_SHAPEIT5", "modules": ["glimpse2/chunk", "shapeit5/phasecommon", "shapeit5/ligate", "bcftools/index"], "description": "Subworkflow to phase a reference panel VCF file using SHAPEIT5."}, "question": {"type": "choice", "instructions": "How should VCF_PHASE_SHAPEIT5 (glimpse2/chunk, shapeit5/phasecommon, shapeit5/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_phase_shapeit5": null, "Local subworkflow VCF_PHASE_SHAPEIT5": null}}, "target": "Use nf-core subworkflow vcf_phase_shapeit5", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Visium spatial transcriptomics with histology image)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,bam": null, "sample,image": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Paired-end Whole Exome Sequencing (WES) target capture. Input files: Paired-end FASTQs from Agilent/Twist exome target capture.", "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Whole Exome Sequencing (WES) target capture input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_viralconsensus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast and memory-efficient viral consensus genome sequence generation from read alignments (tools: viralconsensus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkv_updatedatabase": "Construct the database necessary for checkv's quality assessment", "plink2_score": "Apply a scoring system to each sample in a plink 2 fileset", "gatk4_denoisereadcounts": "Denoises read counts to produce denoised copy ratios", "checkv_endtoend": "Assess the quality of metagenome-assembled viral genomes.", "viralconsensus": "Fast and memory-efficient viral consensus genome sequence generation from read alignments"}}, "target": "viralconsensus", "target_idx": 4}
{"id": "mod_gatk4_getpileupsummaries_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarizes counts of reads that support reference, alternate and other alleles for given sites. Results can be used with CalculateContamination. Requires a common germline variant sites file, such as from gnomAD. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_staralign": null, "gatk4_getpileupsummaries": null, "rgi_main": null, "gatk4_analyzecovariates": null, "gatk4_annotateintervals": null}}, "target": "gatk4_getpileupsummaries", "target_idx": 1}
{"id": "mod_ucsc_bigwigaverageoverbed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: compute average score of bigwig over bed file (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "irescue": "Quantification of transposable elements expression in scRNA-seq", "ngscheckmate_ncm": "Determining whether sequencing data comes from the same individual by using SNP matching. Designed for humans ", "ucsc_bigwigaverageoverbed": "compute average score of bigwig over bed file", "deeptools_bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo"}}, "target": "ucsc_bigwigaverageoverbed", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_3_2", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CAGE-seq 5-prime capped transcript end sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,tss_bed": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "schema_std_sarek_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay": "sarek pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/sarek (Analysis pipeline to detect germline or somatic variants (pr)?", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample,fastq_1,fastq_2,genome": null, "sample,fastq_1,fastq_2,barcode": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 1}
{"id": "mod_disambiguate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ files. Useful in explant RNA/DNA-Seq workflows\nwhere reads from two species are present. For reads aligned to both organisms,\nthe algorithm compares alignment quality scores to determine the most likely\nspecies of origin. Produces four BAM files (uniquely assigned to species A or B,\nambiguous for species A or B) and a summary file. (tools: ngs-disambiguate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/concat": "Concatenate VCF files", "arcashla/extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "disambiguate": "Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ fi", "biscuit/align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "arriba/arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}}, "target": "disambiguate", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_7_0", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,bam": null, "sample,fastq_1,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "noul_process_conditional_execution_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_13", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_kaiju_mergeoutputs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge two tab-separated output files of Kaiju and Kraken in the column format (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge/centrifuge": "Classifies metagenomic sequence data", "kaiju/mergeoutputs": "Merge two tab-separated output files of Kaiju and Kraken in the column format", "conifer": "Calculate confidence scores from Kraken2 output", "odgi/build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1.", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate"}}, "target": "kaiju/mergeoutputs", "target_idx": 1}
{"id": "mod_islandpath_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genomic island prediction in bacterial and archaeal genomes (tools: islandpath)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio/exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "deepbgc/pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "islandpath": "Genomic island prediction in bacterial and archaeal genomes", "deepbgc/download": "Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning.", "sniffles": "structural-variant calling with sniffles"}}, "target": "islandpath", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_4_2", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status?", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_4_4", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates?", "criteria": {"plate,sample,bam": null, "sample,well,fastq": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_strandedness_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"type: boolean": null, "format: file-path": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_45", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_36", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_parabricks_haplotypecaller_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating GATK haplotypecaller. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_mergemutectstats": "Merges mutect2 stats generated on different intervals/regions", "elprep_split": "Split bam file into manageable chunks", "parabricks_haplotypecaller": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating GATK haplotypecaller.", "ferrohgvs_normalize": "Normalize HGVS variant descriptions to canonical form with ferro", "ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro"}}, "target": "parabricks_haplotypecaller", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_qc_stats_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_STATS", "modules": ["fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp"], "description": "Generate statistics for short read sequencing data using multiple tools"}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_STATS (fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_QC_STATS": null, "Use nf-core subworkflow fastq_qc_stats": null}}, "target": "Use nf-core subworkflow fastq_qc_stats", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_43", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "field_constraint_fastq_1_1_4", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_0_4", "category": "samplesheet_schema", "state": {"technology": "Ancient DNA", "workflow_entry": "FASTQC", "library_inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_chromap_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexes a fasta reference genome ready for chromatin profiling. (tools: chromap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromap_index": "Indexes a fasta reference genome ready for chromatin profiling.", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "drep_compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "bowtie_build": "Create bowtie index for reference genome", "whatshap_haplotag": "Tag reads by haplotype"}}, "target": "chromap_index", "target_idx": 0}
{"id": "mod_meningotype_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotyping of Neisseria meningitidis assemblies (tools: meningotype)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": null, "bamtools_stats": null, "meningotype": null, "amrfinderplus_update": null, "hmmer_hmmemit": null}}, "target": "meningotype", "target_idx": 2}
{"id": "mod_anndata_barcodes_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to subset AnnData object to cells with matching barcodes from the csv file (tools: anndata)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender/removebackground": null, "controlfreec/freec": null, "cellranger/mkvdjref": null, "gatk4/indexfeaturefile": null, "anndata/barcodes": null}}, "target": "anndata/barcodes", "target_idx": 4}
{"id": "resource_bracken_build_2", "category": "resource_profiling", "state": {"process": "BRACKEN_BUILD", "tool": "bracken/build", "description": "Extends a Kraken2 database to be compatible with Bracken"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BUILD (Extends a Kraken2 database to be compatible with Bracken) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_isoseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/isoseq", "assay": "isoseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/isoseq (Genome annotation with PacBio Iso-Seq. Takes raw subreads as)?", "criteria": {"sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,seq_data,pbi,start_from": null}}, "target": "sample,seq_data,pbi,start_from", "target_idx": 3}
{"id": "mod_instrain_profile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly accurate genome comparisons, analysis of coverage, microdiversity, and linkage, and sensitive SNP detection with gene localization and synonymous non-synonymous identification (tools: instrain)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "instrain_profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "gatk4_mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "instrain_profile", "target_idx": 1}
{"id": "pipe_all101_nanoseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for alignment. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]"}}, "target": "nanoseq", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_removeadapters_merge_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_REMOVEADAPTERS_MERGE", "modules": ["trimmomatic", "cutadapt", "trimgalore", "bbmap/bbduk", "leehom", "fastp", "adapterremoval", "cat/fastq"], "description": "Remove adapters and merge reads based on various module choices"}, "question": {"type": "choice", "instructions": "How should FASTQ_REMOVEADAPTERS_MERGE (trimmomatic, cutadapt, trimgalore, bbmap/bbduk, leehom, fastp, adapterremoval, cat/fastq) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_removeadapters_merge": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_REMOVEADAPTERS_MERGE": null}}, "target": "Use nf-core subworkflow fastq_removeadapters_merge", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_33", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_ucsc_bedgraphtobigwig_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a bedGraph file to bigWig format. (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "gem2_gem2bedmappability": "Convert a mappability file to bedgraph format", "ucsc_bedgraphtobigwig": "Convert a bedGraph file to bigWig format.", "custom_addmostseverepli": "Annotate a VEP annotated VCF with the most severe pLi field", "ngsbits_bedannotategc": "Annotates GC content fraction to regions in a BED file."}}, "target": "ucsc_bedgraphtobigwig", "target_idx": 2}
{"id": "mod_svdss_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index a reference genome FASTA file using SVDSS (via ropebwt3), producing either an FMD or FMR index for use with SVDSS smooth and search subcommands (tools: svdss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_collectsvevidence": null, "deeptools_plotfingerprint": null, "bandage_image": null, "svdss_index": null, "annotsv_annotsv": null}}, "target": "svdss_index", "target_idx": 3}
{"id": "mod_shasum_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Print SHA256 (256-bit) checksums. (tools: md5sum)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shasum": null, "rclone_checksum": null, "md5sum": null, "fastq_decontaminate_deacon_hostile": null, "eagle2": null}}, "target": "shasum", "target_idx": 0}
{"id": "mod_varscan_somatic_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, and copy number variations in both somatic and germline samples. It is particularly useful for analyzing tumor/normal sample pairs. (tools: varscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"varscan/somatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "methyldackel/mbias": "Generates methylation bias plots from alignments", "atlas/call": "generate VCF file from a BAM file using various calling methods", "wisecondorx/convert": "Convert and filter aligned reads to .npz"}}, "target": "varscan/somatic", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_38", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_numorph_resample_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: performs resampling of light-sheet microscopy images (tools: numorph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "bwa_samse": "Convert bwa SA coordinate file to SAM format", "numorph_resample": "performs resampling of light-sheet microscopy images", "numorph_intensity": "performs shading correction and intensity normalization between tile stacks", "custom_bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou"}}, "target": "numorph_resample", "target_idx": 2}
{"id": "mod_mat2json_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converst matlab .mat files into json or csv files. (tools: mat2json)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"humann3_regroup": "Regrouping genes to other functional categories", "mat2json": "converst matlab .mat files into json or csv files.", "expansionhunter": "Estimate repeat sizes using NGS data", "fastq_sanitise_seqkit": "Filters and reports malformed FASTQ sequences with seqkit/sana,\nand then pairs any paired-end files using seqk", "assemblyscan": "Assembly summary statistics in JSON format"}}, "target": "mat2json", "target_idx": 1}
{"id": "intent_prepare_data_7", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "prepare_data": null, "ask_question": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 1}
{"id": "pipe_all101_clipseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling options.. Topics: clip, clip-seq, peak-calling, rna-rbp-interactions. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]"}}, "target": "clipseq", "target_idx": 3}
{"id": "mod_pairtools_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairs statistics (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools/stats": null, "plink2/pca": null, "medaka": null, "custom/collectstats": null, "ltrretriever/lai": null}}, "target": "pairtools/stats", "target_idx": 0}
{"id": "resource_ale_4", "category": "resource_profiling", "state": {"process": "ALE", "tool": "ale", "description": "ALE: assembly likelihood estimator."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALE (ALE: assembly likelihood estimator.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_minibwa_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a minibwa index for a reference genome (tools: minibwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "glimpse_sample": "Generates haplotype calls by sampling haplotype estimates", "minibwa_index": "Create a minibwa index for a reference genome", "bcftools_index": "Index VCF tools", "pypgx_computecontrolstatistics": "Compute summary statistics for control gene from BAM files."}}, "target": "minibwa_index", "target_idx": 2}
{"id": "mod_genmap_map_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: create mappability files for a genome (tools: genmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem3/gem3indexer": "Create a GEM index from a FASTA file", "malt/build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "gem2/gemindexer": "Create a GEM index from a FASTA file", "picard/collectrnaseqmetrics": "Collect metrics from a RNAseq BAM file", "genmap/map": "create mappability files for a genome"}}, "target": "genmap/map", "target_idx": 4}
{"id": "mod_trimgalore_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith extra functionality for RRBS data (tools: trimgalore)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shasum": "Print SHA256 (256-bit) checksums.", "cooltools/insulation": "Calculate the diamond insulation scores and call insulating boundaries", "trimgalore": "A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith e", "chopper": "Filter and trim long read data.", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads"}}, "target": "trimgalore", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_4", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "field_constraint_fastq_1_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "mod_pharmcat_phenotyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The PharmCAT Phenotyper is a core module of the Pharmacogenomics Clinical Annotation Tool\nthat translates patient diplotypes into specific, actionable metabolizer phenotypes\n(e.g., Poor Metabolizer). It operates by analyzing the JSON output from the Named\nAllele Matcher, mapping these results to established clinical guidelines (such as\nCPIC) to predict drug response. (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamdbg_asm": "Metagenome assembler for long-read sequences (HiFi and ONT).", "vuegen": "The VueGen nf-core module is designed to automate report generation from outputs produced by other modules, su", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "pharmcat_phenotyper": "The PharmCAT Phenotyper is a core module of the Pharmacogenomics Clinical Annotation Tool\nthat translates pati", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "pharmcat_phenotyper", "target_idx": 3}
{"id": "pipe_all101_taxprofiler_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data. Topics: classification, illumina, long-reads, metagenomics, microbiome, nanopore. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]"}}, "target": "taxprofiler", "target_idx": 6}
{"id": "samplesheet_arch_pacbio_hifi_wgs_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/genomeassembler --input samplesheet.csv (Assay: Long-read Pacific Biosciences HiFi sequencing)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_sentieon_qualcal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate recalibration table and optionally perform base quality recalibration (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/applybqsr": null, "foldcomp/compress": null, "vg/index": null, "sentieon/qualcal": null, "gatk4/gatherbqsrreports": null}}, "target": "sentieon/qualcal", "target_idx": 3}
{"id": "mod_peka_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs PEKA CLIP peak k-mer analysis (tools: peka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi/unchop": "Merge unitigs into a single node preserving the node order.", "peka": "Runs PEKA CLIP peak k-mer analysis", "gatk4/cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "bedgraph_bedclip_bedgraphtobigwig": "Convert bedgraph to bigwig with clip", "icountmini/sigxls": "Runs iCount sigxls on a BED file of crosslinks"}}, "target": "peka", "target_idx": 1}
{"id": "field_constraint_fastq_2_0_5", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "field_constraint_fastq_1_1_11", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "mod_pbbam_pbmerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The pbbam software package provides components to create, query, & edit PacBio BAM files and associated indices. These components include a core C++ library, bindings for additional languages, and command-line utilities. (tools: pbbam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbbam_pbmerge": null, "utils_annotation_cache": null, "pbtk_pbmerge": null, "pbmarkdup": null, "abra2": null}}, "target": "pbbam_pbmerge", "target_idx": 0}
{"id": "noul_channel_mix_operator_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_last_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find split or spliced alignments in a MAF file (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_vcf": null, "last_lastal": null, "last_split": null, "shapeit5_phasecommon": null, "last_mafconvert": null}}, "target": "last_split", "target_idx": 2}
{"id": "resource_bio2zarr_vcf2zarrconvert_3", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARRCONVERT", "tool": "bio2zarr/vcf2zarrconvert", "description": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARRCONVERT (Convert VCF data to the VCF Zarr specification reliably, in parallel or distribu) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_6", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "schema_std_phaseimpute_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/phaseimpute", "description": "A bioinformatics pipeline to phase and impute genetic data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/phaseimpute?", "criteria": {"sample,tools,file,index": null, "sample,fasta": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "id,raw_file": null}}, "target": "sample,tools,file,index", "target_idx": 0}
{"id": "mod_sgdemux_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex bgzip'd fastq files (tools: sgdemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bclconvert": "Demultiplex Illumina BCL files", "holodeck_simulate": "Simulate sequencing reads from a reference genome with holodeck", "sgdemux": "Demultiplex bgzip'd fastq files", "bases2fastq": "Demultiplex Element Biosciences bases files", "authentict_deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries"}}, "target": "sgdemux", "target_idx": 2}
{"id": "mod_president_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairwise nucleotide identity with respect to a reference sequence (tools: president)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "vembrane_table": "Creates tabular (TSV) files from VCF/BCF data with flexible Python expressions", "fq_lint": "fq lint is a FASTQ file pair validator.", "president": "Calculate pairwise nucleotide identity with respect to a reference sequence"}}, "target": "president", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_14", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_agat_spmergeannotations_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated names and fixes other oddities met in those files. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterbyorfsize": null, "gnu_split": null, "agat_spflagshortintrons": null, "savana_classify": null, "agat_spmergeannotations": null}}, "target": "agat_spmergeannotations", "target_idx": 4}
{"id": "samplesheet_arch_prealigned_cram_indexed_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Genome analysis from reference-compressed CRAM files. Input files: Coordinate-sorted CRAM alignments with companion CRAI indexes.", "question": {"type": "choice", "instructions": "Which columns are standard for Genome analysis from reference-compressed CRAM files input samplesheet?", "criteria": {"sample,vcf": null, "sample,cram,crai": null, "sample,bam,bai": null, "sample,cram": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "mod_ucsc_bedtobigbed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert file from bed to bigBed format (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ucsc/bedtobigbed": "Convert file from bed to bigBed format", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "samtools/stats": "Produces comprehensive statistics from SAM/BAM/CRAM file", "gatk4/filtervarianttranches": "Apply tranche filtering"}}, "target": "ucsc/bedtobigbed", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_vg_deconstruct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deconstruct snarls present in a variation graph in GFA format to variants in VCF format (tools: vg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vg/deconstruct": "Deconstruct snarls present in a variation graph in GFA format to variants in VCF format", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "catpack/summarise": "Summarises results from CAT/BAT/RAT classification steps", "bcftools/annotate": "Add or remove annotations.", "bcftools/concat": "Concatenate VCF files"}}, "target": "vg/deconstruct", "target_idx": 0}
{"id": "mod_smoove_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: smoove simplifies and speeds calling and genotyping SVs for short reads. It also improves specificity by removing many spurious alignment signals that are indicative of low-level noise and often contribute to spurious calls. Developed by Brent Pedersen. (tools: smoove)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "kallisto/index": "Create kallisto index", "smoove/call": "smoove simplifies and speeds calling and genotyping SVs for short reads. It also improves specificity by remov", "ichorcna/run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "smoove/call", "target_idx": 2}
{"id": "mod_bedtools_getfasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: extract sequences in a FASTA file based on intervals defined in a feature file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "msisensorpro_baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "bedtools_getfasta": "extract sequences in a FASTA file based on intervals defined in a feature file."}}, "target": "bedtools_getfasta", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_2_36", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_propr_grea_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform Gene Ratio Enrichment Analysis (tools: grea)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr/grea": "Perform Gene Ratio Enrichment Analysis", "propr/logratio": "Transform the data matrix using centered logratio transformation (CLR) or additive logratio transformation (AL", "pairtools/split": "Split a .pairsam file into .pairs and .sam.", "differential_functional_enrichment": "Run functional analysis on differential abundance analysis output", "eggnogmapper": "Fast genome-wide functional annotation through orthology assignment."}}, "target": "propr/grea", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pre-aligned BAM variant calling pipeline)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "core_tool_multiqc_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Aggregate and summarize quality control metrics and analysis logs across FastQC, Cutadapt, and STAR into a single interactive HTML report.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"multiqc": null, "fastp": null, "picard": null, "fastqc": null, "trimmomatic": null}}, "target": "multiqc", "target_idx": 0}
{"id": "mod_sentieon_bwaindex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA index for reference genome (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_index": "Index VCF tools", "biscuit_index": "Indexes a reference genome for use with Biscuit", "bam_stringtie_merge": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a ", "picard_crosscheckfingerprints": "Checks that all data in the set of input files appear to come from the same individual", "sentieon_bwaindex": "Create BWA index for reference genome"}}, "target": "sentieon_bwaindex", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_1_33", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "local_subworkflow_prepilluminareads_1_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should this step (trimmomatic) be packaged: Single-step adapter trimming for Illumina reads?", "criteria": {"Use nf-core subworkflow prepilluminareads": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPILLUMINAREADS": null, "Leave them out": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_42", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_aardvark_merge_2", "category": "resource_profiling", "state": {"process": "AARDVARK_MERGE", "tool": "aardvark/merge", "description": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_MERGE (A tool to evaluate and merge multiple variant calls into a consensus VCF.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq. Input files: FastQ reads per sample.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_pharmcat_vcfpreprocessor_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The PharmCAT VCF Preprocessor is a script that can pre-process VCF files for PharmCAT to make sure the VCF file complies with PharmCAT's VCF Requirements (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequali": "Sequence quality metrics for FASTQ and uBAM files.", "mcstaging_macsima2mc": "Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO.", "freyja_demix": "specify the relative abundance of each known haplotype", "leehom": "Bayesian reconstruction of ancient DNA fragments", "pharmcat_vcfpreprocessor": "The PharmCAT VCF Preprocessor is a script that can pre-process VCF files for PharmCAT to make sure the VCF fil"}}, "target": "pharmcat_vcfpreprocessor", "target_idx": 4}
{"id": "samplesheet_arch_ont_metagenome_single_4_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: High molecular weight environmental metagenomic long reads per sampling site?", "criteria": {"sample,bam": null, "sample,fastq_1,group": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "local_subworkflow_preparereports_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should PREPAREREPORTS (custom/preparereports, multiqc) be built?", "criteria": {"Local subworkflow PREPAREREPORTS": null, "Use nf-core subworkflow preparereports": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 0}
{"id": "mod_vcfpgloader_load_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: High-performance VCF to PostgreSQL loader using asyncpg for bulk variant ingestion (tools: vcf-pg-loader)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcfpgloader_load": "High-performance VCF to PostgreSQL loader using asyncpg for bulk variant ingestion", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "spatyper": "Computational method for finding spa types.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "vcfpgloader_load", "target_idx": 0}
{"id": "resource_bedtools_merge_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MERGE", "tool": "bedtools/merge", "description": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MERGE (combines overlapping or “book-ended” features in an interval file into a single ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_5_4", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline custom/mira-nf, determine the input samplesheet column structure for: Custom MIRA-NF Influenza / SC2 pipeline.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_freyja_update_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: downloads new versions of the curated SARS-CoV-2 lineage file and barcodes (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "survivor/simsv": "Simulate an SV VCF file based on a reference genome", "cnvkit/fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "blast/makeblastdb": "Builds a BLAST database", "freyja/update": "downloads new versions of the curated SARS-CoV-2 lineage file and barcodes"}}, "target": "freyja/update", "target_idx": 4}
{"id": "noul_channel_filter_operator_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_sex_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "noul_exit_code_137_cause_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Metagenomic MAG assembly with comparative groups", "data_format": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "noul_channel_operator_map_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_bam_telomere_estimation_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TELOMERE_ESTIMATION", "modules": ["telseq", "telogator2", "telomerehunter", "custom/summarisetelomereestimation"], "description": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter"}, "question": {"type": "choice", "instructions": "How should BAM_TELOMERE_ESTIMATION (telseq, telogator2, telomerehunter, custom/summarisetelomereestimation) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_telomere_estimation": null, "Local subworkflow BAM_TELOMERE_ESTIMATION": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_telomere_estimation", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_4_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics Profiling", "workflow_entry": "FASTQC", "library_inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Short or long reads with run accession and library instrument platform?", "criteria": {"sample,kraken_db": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_dssp_mkdssp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates secondary structure assignments from PDB files using mkdssp (DSSP).\nDSSP is a standard tool for assigning secondary structure to amino acids in protein structures. (tools: dssp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/hwe": null, "deeptmhmm": null, "clusty": null, "dssp/mkdssp": null, "dragonflye": null}}, "target": "dssp/mkdssp", "target_idx": 3}
{"id": "noul_process_conditional_execution_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bandage_image_0", "category": "resource_profiling", "state": {"process": "BANDAGE_IMAGE", "tool": "bandage/image", "description": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BANDAGE_IMAGE (Render an assembly graph in GFA 1.0 format to PNG and SVG image formats) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gatk4spark_markduplicates_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originating from a single fragment of DNA. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4spark_markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "genmap_map": "create mappability files for a genome", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "plink_ld": "LD analysis in PLINK examines genetic variant associations within populations"}}, "target": "gatk4spark_markduplicates", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_0_3", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,bam": null, "sample,bam,bai": null, "patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "resource_bowtie_align_3", "category": "resource_profiling", "state": {"process": "BOWTIE_ALIGN", "tool": "bowtie/align", "description": "Align reads to a reference genome using bowtie"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_ALIGN (Align reads to a reference genome using bowtie) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_tiff_segmentation_vpt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool (tools: tiff_segmentation_vpt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"motus_preplong": "Taxonomic meta-omics profiling using universal marker genes", "spring_decompress": "Fast, efficient, lossless decompression of FASTQ files.", "ilastik_multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "tiff_segmentation_vpt": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool"}}, "target": "tiff_segmentation_vpt", "target_idx": 4}
{"id": "mod_cooler_digest_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate fragment-delimited genomic bins (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler/digest": null, "cooler/makebins": null, "quantmsutils/dianncfg": null, "shasta": null, "simpleaf/quant": null}}, "target": "cooler/digest", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_9", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_1_5", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_seqfu_check_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluates the integrity of DNA FASTQ files (tools: seqfu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqfu_stats": "Statistics for FASTA or FASTQ files", "parsesdrf_convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration ", "rclone_check": "Check that files in source and destination paths match", "seqfu_check": "Evaluates the integrity of DNA FASTQ files", "megahit": "An ultra-fast metagenomic assembler for large and complex metagenomics"}}, "target": "seqfu_check", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pre-aligned BAM variant calling pipeline)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "resource_arriba_download_0", "category": "resource_profiling", "state": {"process": "ARRIBA_DOWNLOAD", "tool": "arriba/download", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_DOWNLOAD (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_invalid_process_communication_via_globals_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_checkv_downloaddatabase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct the database necessary for checkv's quality assessment (tools: checkv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"muscle5/super5": null, "autocycler/combine": null, "checkm2/databasedownload": null, "checkv/downloaddatabase": null, "checkm2/predict": null}}, "target": "checkv/downloaddatabase", "target_idx": 3}
{"id": "resource_biohansel_3", "category": "resource_profiling", "state": {"process": "BIOHANSEL", "tool": "biohansel", "description": "Use k-mers to rapidly subtype S. enterica genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOHANSEL (Use k-mers to rapidly subtype S. enterica genomes) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_27", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bedtools_shift_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHIFT", "tool": "bedtools/shift", "description": "Shifts each feature by specific number of bases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHIFT (Shifts each feature by specific number of bases) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_bff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generating cell hashing calls from a matrix of count data. (tools: bff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strobealign": "Align short reads using dynamic seed size with strobemers", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "bff": "Generating cell hashing calls from a matrix of count data.", "gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU"}}, "target": "bff", "target_idx": 3}
{"id": "resource_agat_convertbed2gff_1", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTBED2GFF", "tool": "agat/convertbed2gff", "description": "Takes a bed12 file and converts to a GFF3 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTBED2GFF (Takes a bed12 file and converts to a GFF3 file) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gatk4_createreadcountpanelofnormals_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a panel of normals (PoN) for read-count denoising given the read counts for samples in the panel. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "mitorsaw_haplotype": "Mitorsaw analyses mitochondrial variants and identifies heteroplasmy and homoplasmy", "fgumi_duplex": "Calls duplex consensus sequences from reads generated from the same double-stranded\nsource molecule. This is a", "gatk4_createreadcountpanelofnormals": "Creates a panel of normals (PoN) for read-count denoising given the read counts for samples in the panel."}}, "target": "gatk4_createreadcountpanelofnormals", "target_idx": 4}
{"id": "resource_bamstats_generalstats_0", "category": "resource_profiling", "state": {"process": "BAMSTATS_GENERALSTATS", "tool": "bamstats/generalstats", "description": "write your description here"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMSTATS_GENERALSTATS (write your description here) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_bowtie2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BOWTIE2", "modules": ["bowtie2/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bowtie2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BOWTIE2 (bowtie2/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_BOWTIE2": null, "Use nf-core subworkflow fastq_align_bowtie2": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_bowtie2", "target_idx": 1}
{"id": "mod_pasty_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serogroup Pseudomonas aeruginosa assemblies (tools: pasty)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "fastqutils/info": "Performs quality control of FASTQ files", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "bakta/bakta": "Annotation of bacterial genomes (isolates, MAGs) and plasmids", "pasty": "Serogroup Pseudomonas aeruginosa assemblies"}}, "target": "pasty", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_2_12", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_dshbio_exportsegments_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Export assembly segment sequences in GFA 1.0 format to FASTA format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "kmergenie": "KmerGenie estimates the best k-mer length for genome de novo assembly", "dshbio/exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA", "odgi/build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1."}}, "target": "dshbio/exportsegments", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Visium spatial transcriptomics with histology image", "data_format": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Visium spatial transcriptomics with histology image with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null, "sample,fastq_1,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_3_0", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Dual RNA-seq simultaneous host and pathogen transcriptomics with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "mod_methylsieve_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter/tag unconverted reads in methylation sequencing with methylsieve; for maximum throughput it can also run inline in the alignment pipe (aligner | methylsieve | sort) rather than as a standalone step (tools: methylsieve)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"methylsieve": "Filter/tag unconverted reads in methylation sequencing with methylsieve; for maximum throughput it can also ru", "stainwarpy/transformsegmask": "Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "bismark/align": "Performs alignment of BS-Seq reads using bismark", "vcf2zarr/convert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster"}}, "target": "methylsieve", "target_idx": 0}
{"id": "resource_autocycler_resolve_5", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_RESOLVE", "tool": "autocycler/resolve", "description": "Resolve trimmed assembly graphs into final contigs within Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_RESOLVE (Resolve trimmed assembly graphs into final contigs within Autocycler.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_blast_blastdbcmd_4", "category": "resource_profiling", "state": {"process": "BLAST_BLASTDBCMD", "tool": "blast/blastdbcmd", "description": "Retrieve entries from a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTDBCMD (Retrieve entries from a BLAST database) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_blobtk_create_3", "category": "resource_profiling", "state": {"process": "BLOBTK_CREATE", "tool": "blobtk/create", "description": "Creates a minimal blobdir."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_CREATE (Creates a minimal blobdir.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_4", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_checkm_lineagewf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. (tools: checkm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkv_endtoend": null, "checkm_lineagewf": null, "blobtk_depth": null, "checkv_downloaddatabase": null, "sentieon_dnascope": null}}, "target": "checkm_lineagewf", "target_idx": 1}
{"id": "mod_sentieon_applyvarcal_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the second pass in a two-stage process called Variant Quality Score Recalibration (VQSR).\nSpecifically, it applies filtering to the input variants based on the recalibration table produced\nin the previous step VarCal and a target sensitivity value.\nhttps://support.sentieon.com/manual/usages/general/#applyvarcal-algorithm (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_collectvcmetrics": "Accelerated implementation of the Picard CollectVariantCallingMetrics tool.", "checkv_downloaddatabase": "Construct the database necessary for checkv's quality assessment", "bam_ngscheckmate": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set o", "sentieon_coveragemetrics": "Accelerated implementation of the GATK DepthOfCoverage tool.", "sentieon_applyvarcal": "Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the sec"}}, "target": "sentieon_applyvarcal", "target_idx": 4}
{"id": "mod_unzip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unzip ZIP archive files (tools: unzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spring_decompress": null, "fusionreport_download": null, "controlfreec_assesssignificance": null, "gunzip": null, "unzip": null}}, "target": "unzip", "target_idx": 4}
{"id": "resource_amrfinderplus_run_4", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_RUN", "tool": "amrfinderplus/run", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_RUN (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_octopusv_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge and harmonize structural variant calls from multiple samples. (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcflib/vcffixup": "Generates a VCF stream where AC and NS have been generated for each record using sample genotypes.", "motus/downloaddb": "Download the mOTUs database", "gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "annotsv/installannotations": "Install the AnnotSV annotations", "octopusv/merge": "Merge and harmonize structural variant calls from multiple samples."}}, "target": "octopusv/merge", "target_idx": 4}
{"id": "mod_sentieon_tnfilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters the raw output of sentieon/tnhaplotyper2. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file", "svdb_query": "Query a structural variant database, using a vcf file as query", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "sentieon_tnfilter": "Filters the raw output of sentieon/tnhaplotyper2."}}, "target": "sentieon_tnfilter", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_bam_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic tumor-normal calling from pre-aligned BAM files)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "schema_std_demultiplex_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/demultiplex", "assay": "demultiplex pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/demultiplex (Demultiplexing pipeline for sequencing data)?", "criteria": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "id,fasta,query": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "id,samplesheet,lane,flowcell,per_flowcell_manifest", "target_idx": 0}
{"id": "mod_pydamage_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Damage parameter estimation for ancient DNA (tools: pydamage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/pmd": null, "amps": null, "pydamage/filter": null, "dshbio/splitgff3": null, "msisensor/msi": null}}, "target": "pydamage/filter", "target_idx": 2}
{"id": "mod_bam_impute_quilt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute BAM files using QUILT software.\nVariants location to impute are obtain through the tsv file given.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: bam_impute_quilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_impute_quilt": "Subworkflow to impute BAM files using QUILT software.\nVariants location to impute are obtain through the tsv f", "sam2lca_analyze": "Calling lowest common ancestors from multi-mapped reads in SAM/BAM/CRAM files", "muscle5_super5": "Muscle is a program for creating multiple alignments of amino acid or nucleotide sequences. This particular mo", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "atlas_splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "bam_impute_quilt", "target_idx": 0}
{"id": "subworkflow_pkg_bam_dedup_stats_samtools_umicollapse_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_STATS_SAMTOOLS_UMICOLLAPSE", "modules": ["umicollapse", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_STATS_SAMTOOLS_UMICOLLAPSE (umicollapse, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_DEDUP_STATS_SAMTOOLS_UMICOLLAPSE": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_dedup_stats_samtools_umicollapse": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umicollapse", "target_idx": 3}
{"id": "resource_bamreadcount_5", "category": "resource_profiling", "state": {"process": "BAMREADCOUNT", "tool": "bamreadcount", "description": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMREADCOUNT (bam-readcount is a utility that runs on a BAM or CRAM file and generates low-lev) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_lsa_cosine_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates the cosine similarity matrix between samples based on a gene expression matrix. (tools: lsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngsbits/bedannotategc": null, "custom/clustermetrics": null, "vardictjava": null, "comebin/runcomebin": null, "lsa/cosine": null}}, "target": "lsa/cosine", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_5_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_agat_spkeeplongestisoform_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters GFF records to keep only the longest isoform per gene (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spaddintrons": "Add intron features to gtf/gff file without intron features.", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "seqkit_pair": "match up paired-end reads from two fastq files", "agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "peddy": "Manipulation, validation and exploration of pedigrees"}}, "target": "agat_spkeeplongestisoform", "target_idx": 1}
{"id": "mod_fastx_collapser_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts) (tools: fastx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunzip": "Compresses and decompresses files.", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "fastx/collapser": "Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts)", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "gridss/somaticfilter": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements."}}, "target": "fastx/collapser", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Multiplexed Oxford Nanopore run with barcode demultiplexing. Input files: Nanopore sequencing run with sample to barcode assignment and flowcell type.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Multiplexed Oxford Nanopore run with barcode demultiplexing.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_4_2", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Combinatorial split-pool barcoded FASTQs with subpool annotations?", "criteria": {"sample,bam": null, "sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_cageseq_transcription_1_5", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "template": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "intent_prepare_data_19", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "prepare_data": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 2}
{"id": "mod_paraphrase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parse and annotate paraphrase JSONs (tools: paraphrase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paraphrase": "Parse and annotate paraphrase JSONs", "anndata/barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "autocycler/resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "mcstaging/imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata."}}, "target": "paraphrase", "target_idx": 0}
{"id": "mod_perbase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Per-base metrics on BAM/CRAM files. (tools: perbase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sratools/prefetch": "Download sequencing data from the NCBI Sequence Read Archive (SRA).", "perbase": "Per-base metrics on BAM/CRAM files.", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "sushie": "Software to perform multi-ancestry SNP fine-mapping on molecular data", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "perbase", "target_idx": 1}
{"id": "mod_rasusa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Randomly subsample sequencing reads to a specified coverage (tools: rasusa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/view": "filter/convert SAM/BAM/CRAM file", "ucsc/bedtobigbed": "Convert file from bed to bigBed format", "cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "rasusa": "Randomly subsample sequencing reads to a specified coverage", "cnvkit/coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths."}}, "target": "rasusa", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_39", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_spatial_xenium_3_1", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Xenium in situ subcellular spatial RNA transcriptomics with entry step INPUT_CHECK.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "resource_bbmap_bbduk_0", "category": "resource_profiling", "state": {"process": "BBMAP_BBDUK", "tool": "bbmap/bbduk", "description": "Adapter and quality trimming of sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBDUK (Adapter and quality trimming of sequencing reads) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_adapterremovalfixprefix_1", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVALFIXPREFIX", "tool": "adapterremovalfixprefix", "description": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with DeDup."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVALFIXPREFIX (Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names a) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_checkirma_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for CHECKIRMA (custom/checkirma).", "criteria": {"Leave them out": null, "Local subworkflow CHECKIRMA": null, "Use nf-core subworkflow checkirma": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 1}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_vizgenpostprocessing_compiletilesegmentation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module compiles segmentation tiles using Vizgen's post-processing tool. (tools: vizgenpostprocessing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge/centrifuge": null, "rgi/bwt": null, "vizgenpostprocessing/compiletilesegmentation": null, "vizgenpostprocessing/runsegmentationontile": null, "cellpose": null}}, "target": "vizgenpostprocessing/compiletilesegmentation", "target_idx": 2}
{"id": "noul_exit_code_137_cause_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_5_5", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Multiplexed Oxford Nanopore run with barcode demultiplexing.", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_6_4", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen", "pipeline": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Dual RNA-seq simultaneous host and pathogen transcriptomics input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "noul_channel_collect_operator_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_pbccs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pacbio ccs - Generate Highly Accurate Single-Molecule Consensus Reads (tools: pbccs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"emmtyper": "EMM typing of Streptococcus pyogenes assemblies", "isoseq_refine": "Remove polyA tail and artificial concatemers", "pbccs": "Pacbio ccs - Generate Highly Accurate Single-Molecule Consensus Reads", "hifiadapterfilt_downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "kmcp_merge": "Merge search results from multiple databases."}}, "target": "pbccs", "target_idx": 2}
{"id": "mod_foldseek_easysearch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search for protein structural hits against a foldseek database of protein structures (tools: foldseek)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scvitools_solo": null, "gstama_merge": null, "caalm_caalm": null, "foldseek_easysearch": null, "deeptmhmm": null}}, "target": "foldseek_easysearch", "target_idx": 3}
{"id": "mod_picard_extractfingerprint_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at the fingerprinting sites. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_stringtie_merge": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a ", "picard/createsequencedictionary": "Creates a sequence dictionary for a reference sequence.", "picard/extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at", "picard/filtersamreads": "Filters SAM/BAM files to include/exclude either aligned/unaligned reads or based on a read list", "custom/matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass."}}, "target": "picard/extractfingerprint", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_11", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_42", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_bamcmp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For instance, filtering out mouse reads from patient derived xenograft mouse models (PDX). (tools: bamcmp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chopper": "Filter and trim long read data.", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bowtie_align": "Align reads to a reference genome using bowtie", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "meryl_histogram": "A genomic k-mer counter (and sequence utility) with nice features."}}, "target": "bamcmp", "target_idx": 3}
{"id": "mod_trnascanse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detection of tRNA sequences using covariance models (tools: trnascanse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/applyvarcal": null, "mmseqs/linclust": null, "seqsero2": null, "repeatmasker/rmouttogff3": null, "trnascanse": null}}, "target": "trnascanse", "target_idx": 4}
{"id": "samplesheet_arch_ont_direct_rna_se_0_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "noul_process_conditional_execution_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fgumi_clip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clip overlapping reads in a BAM file with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium", "fgumi/clip": "Clip overlapping reads in a BAM file with fgumi", "peka": "Runs PEKA CLIP peak k-mer analysis", "pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "gatk4/variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo"}}, "target": "fgumi/clip", "target_idx": 1}
{"id": "mod_vcf_annotate_ensemblvep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file (tools: vcf_annotate_ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_compare": null, "subread_featurecounts": null, "vcf_annotate_ensemblvep": null, "suppa_psiperisoform": null, "annotsv_annotsv": null}}, "target": "vcf_annotate_ensemblvep", "target_idx": 2}
{"id": "schema_std_rnastructurome_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnastructurome. Description: a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnastructurome.", "criteria": {"sample,group,ref_fasta,ref_gff,use_ref": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,fastq_1,fastq_2,rundir,tags": null, "family_id,sample,file_path,hpo_terms,sex": null}}, "target": "sample,sample_id,fastq_1,fastq_2,method", "target_idx": 1}
{"id": "mod_deeparg_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes (tools: deeparg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeparg/predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "yte": "A YAML template engine with Python expressions", "deeparg/downloaddata": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "tcoffee/alncompare": "Compares 2 alternative MSAs to evaluate them."}}, "target": "deeparg/predict", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_46", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_ataqv_ataqv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ataqv function of a corresponding ataqv tool (tools: ataqv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ataqv_ataqv": "ataqv function of a corresponding ataqv tool", "umitools_extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "macs3_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "ataqv_mkarv": "mkarv function of a corresponding ataqv tool", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications"}}, "target": "ataqv_ataqv", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "schema_std_drop_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/drop", "assay": "drop pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/drop (Pipeline to find aberrant events in RNA-Seq data, useful for)?", "criteria": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,fastq_1,fastq_2,batch,condition": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "gene_name,alignment,tree,suite,tool": null}}, "target": "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_bwaaln_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWAALN", "modules": ["bwa/aln", "bwa/sampe", "bwa/samse", "samtools/index"], "description": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWAALN (bwa/aln, bwa/sampe, bwa/samse, samtools/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_bwaaln": null, "Local subworkflow FASTQ_ALIGN_BWAALN": null}}, "target": "Use nf-core subworkflow fastq_align_bwaaln", "target_idx": 2}
{"id": "resource_abacas_4", "category": "resource_profiling", "state": {"process": "ABACAS", "tool": "abacas", "description": "Contiguate draft genome assembly"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABACAS (Contiguate draft genome assembly) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_42", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_agat_convertspgff2tsv_5", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2TSV", "tool": "agat/convertspgff2tsv", "description": "Converts a GFF/GTF file into a TSV file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2TSV (Converts a GFF/GTF file into a TSV file) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_bam_rseqc_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_RSEQC", "modules": ["rseqc", "rseqc/tin", "rseqc/readduplication", "rseqc/readdistribution", "rseqc/junctionsaturation", "rseqc/junctionannotation", "rseqc/innerdistance", "rseqc/inferexperiment", "rseqc/bamstat"], "description": "Subworkflow to run multiple commands in the RSeqC package"}, "question": {"type": "choice", "instructions": "How should BAM_RSEQC (rseqc, rseqc/tin, rseqc/readduplication, rseqc/readdistribution, rseqc/junctionsaturation, rseqc/junctionannotation, rseqc/innerdistance, rseqc/inferexperiment, rseqc/bamstat) be structured in DSL2?", "criteria": {"Local subworkflow BAM_RSEQC": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_rseqc": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_rseqc", "target_idx": 2}
{"id": "core_tool_interproscan_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Scan protein and nucleotide sequences against multiple member databases to identify structural domains, functional sites, and protein families.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"blastp": null, "eggnog": null, "hmmer": null, "interproscan": null, "diamond": null}}, "target": "interproscan", "target_idx": 3}
{"id": "mod_graphmap2_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: graphmap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusioncatcher_fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "bcftools_index": "Index VCF tools", "graphmap2_index": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "gt_stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "bowtie_build": "Create bowtie index for reference genome"}}, "target": "graphmap2_index", "target_idx": 2}
{"id": "noul_exit_code_137_cause_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "schema_std_airrflow_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/airrflow. Description: B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/airrflow.", "criteria": {"sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,fastq,cell_count": null, "sample,fasta,protein,gbk,gff": null}}, "target": "sample_id,subject_id,species,pcr_target_locus,tissue", "target_idx": 0}
{"id": "mod_picard_fastqtosam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a FASTQ file to an unaligned BAM or SAM file. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser_diff": null, "adapterremoval": null, "ariba_run": null, "picard_fastqtosam": null, "localcdsearch_download": null}}, "target": "picard_fastqtosam", "target_idx": 3}
{"id": "mod_rsem_preparereference_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare a reference genome for RSEM (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tximeta_tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages", "rsem_preparereference": "Prepare a reference genome for RSEM", "custom_tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "finaletoolkit_mds": "Comnpute the Motif Diversity Score using normalized Shannon entropy\n(Jiang et al., 2020).", "agat_sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file"}}, "target": "rsem_preparereference", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: 16S rRNA / ITS microbiome amplicon profiling)", "question": {"type": "choice", "instructions": "Which columns are standard for 16S rRNA / ITS microbiome amplicon profiling input samplesheet?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_deeptools_bamcompare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the log2 ratio, ratio, difference or other operations. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mash_screen": "Screens query sequences against large sequence databases", "ascat": "copy number profiles of tumour cells.", "deeptools_bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "vcfpgloader_load": "High-performance VCF to PostgreSQL loader using asyncpg for bulk variant ingestion", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "deeptools_bamcompare", "target_idx": 2}
{"id": "mod_canu_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. (tools: canu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ale": "ALE: assembly likelihood estimator.", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "hisat3n_build": "Build HISAT-3N index for nucleotide conversion sequencing alignment", "samtools_mpileup": "Generate text pileup output for one or multiple BAM files. Each input file produces a separate group of pileup"}}, "target": "canu", "target_idx": 1}
{"id": "noul_channel_factory_inside_process_body_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bbmap_filterbyname_5", "category": "resource_profiling", "state": {"process": "BBMAP_FILTERBYNAME", "tool": "bbmap/filterbyname", "description": "Filter out sequences by sequence header name(s)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_FILTERBYNAME (Filter out sequences by sequence header name(s)) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_bamtofastq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Converts bam or cram files to fastq format and does quality control.. Topics: bamtofastq, conversion, cramtofastq. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "seqsubmit": "nf-core pipeline for data submission to ENA", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "bamtofastq", "target_idx": 8}
{"id": "samplesheet_arch_prealigned_bam_indexed_5_4", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pre-aligned BAM variant calling pipeline.", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "local_subworkflow_prepontreads_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should PREPONTREADS (porechop, nanoplot) be built?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null, "Local subworkflow PREPONTREADS": null, "Leave them out": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 2}
{"id": "resource_angsd_realsfs_4", "category": "resource_profiling", "state": {"process": "ANGSD_REALSFS", "tool": "angsd/realsfs", "description": "Estimate site frequency spectrum from site allele frequencies"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_REALSFS (Estimate site frequency spectrum from site allele frequencies) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_pdb2pqr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g. APBS input preparation). (tools: pdb2pqr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_dedup_stats_samtools_umicollapse": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats", "pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g", "foldcomp_decompress": "Decompression tool for foldcomp compressed structures", "foldmason_easymsa": "Aligns protein structures using foldmason", "ataqv_ataqv": "ataqv function of a corresponding ataqv tool"}}, "target": "pdb2pqr", "target_idx": 1}
{"id": "resource_bismark_summary_5", "category": "resource_profiling", "state": {"process": "BISMARK_SUMMARY", "tool": "bismark/summary", "description": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_SUMMARY (Uses Bismark report files of several samples in a run folder to generate a graph) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_dynamic_resource_allocation_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_channel_collect_operator_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_16", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_14", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_bcftools_annotate_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ANNOTATE", "tool": "bcftools/annotate", "description": "Add or remove annotations."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ANNOTATE (Add or remove annotations.) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_status_1_11", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_45", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_channel_filter_operator_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "schema_std_funcscan_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/funcscan", "assay": "funcscan pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/funcscan ((Meta-)genome screening for functional and natural product g)?", "criteria": {"sample,fastq_1,fastq_2,rundir,tags": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fasta,protein,gbk,gff": null, "sample,fasta": null}}, "target": "sample,fasta,protein,gbk,gff", "target_idx": 2}
{"id": "mod_checkm2_databasedownload_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM2 database download (tools: checkm2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkv_endtoend": "Assess the quality of metagenome-assembled viral genomes.", "checkm2_predict": "CheckM2 bin quality prediction", "checkm2_databasedownload": "CheckM2 database download", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "ultraplex": "Ultraplex is an all-in-one software package for processing and demultiplexing fastq files."}}, "target": "checkm2_databasedownload", "target_idx": 2}
{"id": "field_constraint_bai_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "resource_bcftools_pluginscatter_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSCATTER", "tool": "bcftools/pluginscatter", "description": "Split VCF by chunks or regions, creating multiple VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSCATTER (Split VCF by chunks or regions, creating multiple VCFs.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_cnvkit_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl_align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection", "cnvkit_call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number", "pbbam_pbmerge": "The pbbam software package provides components to create, query, & edit PacBio BAM files and associated indice", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples).", "cnvkit_batch": "Copy number variant detection from high-throughput sequencing data"}}, "target": "cnvkit_call", "target_idx": 1}
{"id": "noul_channel_filter_operator_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_15", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bowtie2_build_5", "category": "resource_profiling", "state": {"process": "BOWTIE2_BUILD", "tool": "bowtie2/build", "description": "Builds bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_BUILD (Builds bowtie index for reference genome) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_abyss_abysspe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes. (tools: abyss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abyss/abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "agat/convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "trnascanse": "Detection of tRNA sequences using covariance models", "gcta/adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`", "abacas": "Contiguate draft genome assembly"}}, "target": "abyss/abysspe", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_5_5", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Longitudinal cancer monitoring across multiple timepoints.", "criteria": {"patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bedtools_intersect_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_INTERSECT", "tool": "bedtools/intersect", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_INTERSECT (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "assay_type": "RNA gene fusion detection (Arriba, STAR-Fusion)", "data_format": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for RNA gene fusion detection (Arriba, STAR-Fusion) with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fusion_bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "noul_multiple_script_sections_invalid_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_happy_sompy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic variations. (tools: sompy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_getchromsizes": "Generates a FASTA file of chromosome sizes and a fasta index file", "happy_sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic ", "happy_ftxpy": "Somatic VCF Feature Extraction tool from hap.y.", "mdust": "mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences", "gatk4_haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes"}}, "target": "happy_sompy", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_15", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "schema_std_methylong_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylong", "description": "Extract methylation calls from long reads (ONT/ PacBio) ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/methylong?", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "patient,sample,vcf,status,cna": null, "sample,group,path,ref,method": null, "sample,fastq_1,fastq_2,library_id,lane": null}}, "target": "sample,group,path,ref,method", "target_idx": 2}
{"id": "resource_adapterremoval_2", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVAL", "tool": "adapterremoval", "description": "Trim sequencing adapters and collapse overlapping reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVAL (Trim sequencing adapters and collapse overlapping reads) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_bcftools_pluginfilltags_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute and fill various INFO tags (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/csq": "bcftools Haplotype-aware consequence caller", "autocycler/combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "bcftools/annotate": "Add or remove annotations.", "bcftools/pluginfilltags": "Compute and fill various INFO tags", "wisecondorx/convert": "Convert and filter aligned reads to .npz"}}, "target": "bcftools/pluginfilltags", "target_idx": 3}
{"id": "mod_pbtk_pbindex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Minimalistic tool which creates an index file that enables random access into PacBio BAM files (tools: pbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "pbtk/pbindex": "Minimalistic tool which creates an index file that enables random access into PacBio BAM files", "fgumi/extract": "Extract unique molecular indices (UMIs) from FASTQ files and write an unaligned BAM file.", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "elprep/merge": "Merge split bam/sam chunks in one file"}}, "target": "pbtk/pbindex", "target_idx": 1}
{"id": "resource_bedtools_jaccard_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_JACCARD", "tool": "bedtools/jaccard", "description": "Calculate Jaccard statistic b/w two feature files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_JACCARD (Calculate Jaccard statistic b/w two feature files.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_2_0", "category": "samplesheet_schema", "state": {"technology": "Microbial Assembly", "workflow_entry": "FASTQC", "library_inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "schema_std_pixelator_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pixelator. Description: Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pixelator.", "criteria": {"sample,fastq_1,fastq_2,pool,hash_index": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample_id,idat_red,idat_green,group": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null}}, "target": "sample,fastq_1,fastq_2,pool,hash_index", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_8", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_2_5", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,well,plate": null, "sample,fastq_1": null, "sample,bam": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_invalid_process_communication_via_globals_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_mapdamage2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads generated by Next-Generation Sequencing platforms. (tools: mapdamage2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dedup": null, "atlas/pmd": null, "mapdamage2": null, "oatk": null, "repeatmodeler/repeatmodeler": null}}, "target": "mapdamage2", "target_idx": 2}
{"id": "mod_seqtk_sample_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subsample reads from FASTQ files (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqtk/sample": "Subsample reads from FASTQ files", "spaceranger/count": "Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data", "hapibd": "The hap-ibd program detects identity-by-descent (IBD) segments and homozygosity-by-descent (HBD) segments in p", "seqtk/comp": "Computes sequence statistics from FASTQ or FASTA files", "picard/positionbaseddownsamplesam": "Samples a SAM/BAM/CRAM file using flowcell position information for the best approximation of having sequenced"}}, "target": "seqtk/sample", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_49", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_default_empty_channel_behavior_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_fastq_1_0_0", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "mod_autocycler_compress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Package candidate assemblies for clustering by Autocycler. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "evigene/tr2aacds": "Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly", "dshbio/exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler."}}, "target": "autocycler/compress", "target_idx": 4}
{"id": "schema_std_funcscan_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/funcscan", "description": "(Meta-)genome screening for functional and natural product gene sequences", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/funcscan?", "criteria": {"sample,fastq_1,fastq_2,barcode": null, "sample_id,bam,vcf,library_id,lane": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,fasta,protein,gbk,gff": null}}, "target": "sample,fasta,protein,gbk,gff", "target_idx": 3}
{"id": "mod_isoseq_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: IsoSeq - Cluster - Cluster trimmed consensus sequences (tools: isoseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq/cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences", "cdhit/cdhitest": "Cluster nucleotide sequences using sequence similarity", "paraclu": "Paraclu finds clusters in data attached to sequences.", "fastq_trim_fastp_fastqc": "Read QC, fastp trimming and read qc", "biscuit/align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit."}}, "target": "isoseq/cluster", "target_idx": 0}
{"id": "mod_genmod_compound_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score compounds (tools: genmod)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trycycler/cluster": "Cluster contigs from multiple assemblies by similarity", "genmod/score": "Score the variants of a vcf based on their annotation", "rhocall/viz": "Call regions of homozygosity and make tentative UPD calls", "genmod/annotate": "for annotating regions, frequencies, cadd scores", "genmod/compound": "Score compounds"}}, "target": "genmod/compound", "target_idx": 4}
{"id": "noul_channel_mix_operator_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_binette_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools. (tools: binette)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/clumpify": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates", "medaka": "A tool to create consensus sequences and variant calls from nanopore sequencing data", "clame": "binning of metagenomic sequences", "concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "binette", "target_idx": 4}
{"id": "core_tool_cellranger_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Demultiplexing, barcode processing, alignment, and UMI counting for 10x Genomics single-cell RNA-seq libraries.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"starsolo": "STAR single-cell mode", "seurat": "R analysis package", "kallisto_bustools": "Single-cell quantifier", "alevin": "Salmon single-cell", "cellranger": "Set of analysis pipelines that process Chromium single cell data to output expression matrices"}}, "target": "cellranger", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_remove_rrna_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_REMOVE_RRNA", "modules": ["bowtie2/align", "bowtie2/build", "ribodetector", "samtools/fastq", "samtools/view", "seqkit/replace", "seqkit/stats", "sortmerna"], "description": "Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2"}, "question": {"type": "choice", "instructions": "How should FASTQ_REMOVE_RRNA (bowtie2/align, bowtie2/build, ribodetector, samtools/fastq, samtools/view, seqkit/replace, seqkit/stats, sortmerna) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_remove_rrna": null, "Local subworkflow FASTQ_REMOVE_RRNA": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_remove_rrna", "target_idx": 1}
{"id": "mod_xengsort_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast lightweight accurate xenograft sorting (tools: xengsort)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "juicertools/pre": "Create a multi-resolution .hic contact matrix for analysis with Juicer", "xengsort/index": "Fast lightweight accurate xenograft sorting", "bcftools/index": "Index VCF tools", "bcftools/convert": "Converts certain output formats to VCF"}}, "target": "xengsort/index", "target_idx": 2}
{"id": "mod_seqkit_sliding_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use seqkit to generate sliding windows of input fasta (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/replace": "Use seqkit to find/replace strings within sequences and sequence headers", "seqkit/grep": "Select sequences from a large file based on name/ID", "seqkit/sliding": "Use seqkit to generate sliding windows of input fasta", "gcta/makebksparse": "Create a sparse GRM from a dense GRM for downstream fastGWA analyses", "bcftools/query": "Extracts fields from VCF or BCF files and outputs them in user-defined format."}}, "target": "seqkit/sliding", "target_idx": 2}
{"id": "pipe_all101_sopa_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for segmentation analysis? Specific context: Nextflow version of Sopa - spatial omics pipeline and analysis. Topics: segmentation, spatial-omics, spatial-proteomics, spatial-transcriptomics, spatialdata. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]"}}, "target": "sopa", "target_idx": 7}
{"id": "subworkflow_pkg_bam_markduplicates_picard_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_PICARD", "modules": ["picard/markduplicates", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_PICARD (picard/markduplicates, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_markduplicates_picard": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_MARKDUPLICATES_PICARD": null}}, "target": "Use nf-core subworkflow bam_markduplicates_picard", "target_idx": 0}
{"id": "mod_longstitch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: \"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - Tigmint cuts the draft assembly at potentially misassembled regions\n  - ntLink is then used to scaffold the corrected assembly\n  - followed by ARKS for further scaffolding (optional)\" (tools: longstitch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_setnmmdanduqtags": null, "pairix": null, "longstitch": null, "strdust": null, "savana_run": null}}, "target": "longstitch", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_trimgalore_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_TRIMGALORE", "modules": ["fastqc", "umitools/extract", "trimgalore"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_TRIMGALORE (fastqc, umitools/extract, trimgalore) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_fastqc_umitools_trimgalore": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_FASTQC_UMITOOLS_TRIMGALORE": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_trimgalore", "target_idx": 1}
{"id": "intent_build_pipeline_8", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 2}
{"id": "resource_bowtie2_align_5", "category": "resource_profiling", "state": {"process": "BOWTIE2_ALIGN", "tool": "bowtie2/align", "description": "Align reads to a reference genome using bowtie2"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_ALIGN (Align reads to a reference genome using bowtie2) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_1_4", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_ataqv_mkarv_4", "category": "resource_profiling", "state": {"process": "ATAQV_MKARV", "tool": "ataqv/mkarv", "description": "mkarv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_MKARV (mkarv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_5_2", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate", "pipeline": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/bacass, determine the input samplesheet column structure for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_vizgenpostprocessing_runsegmentationontile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool. (tools: vizgenpostprocessing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiff_segmentation_vpt": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "vizgenpostprocessing/runsegmentationontile": "The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool.", "endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen"}}, "target": "vizgenpostprocessing/runsegmentationontile", "target_idx": 3}
{"id": "mod_scds_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use scds for doublet scoring (tools: scds)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender_removebackground": null, "bff": null, "dupblaster": null, "sourcepredict": null, "scds": null}}, "target": "scds", "target_idx": 4}
{"id": "field_constraint_expected_cells_3_2", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "mod_blast_updateblastdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads a BLAST database from NCBI (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "blast/updateblastdb": "Downloads a BLAST database from NCBI", "hostile/clean": "Removes host reads from short- and long-read FASTQ sequencing files", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "blast/updateblastdb", "target_idx": 1}
{"id": "resource_agat_convertspgff2gtf_5", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2GTF", "tool": "agat/convertspgff2gtf", "description": "Converts a GFF/GTF file into a proper GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2GTF (Converts a GFF/GTF file into a proper GTF file) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_bacass_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for assembly. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet"}}, "target": "bacass", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_36", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bedtools_shuffle_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHUFFLE", "tool": "bedtools/shuffle", "description": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a genome file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHUFFLE (bedtools shuffle will randomly permute the genomic locations of a feature file a) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_index_methylseq_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_METHYLSEQ", "modules": ["untar", "gunzip", "bismark/genomepreparation", "bwameth/index", "bwa/index", "samtools/faidx"], "description": "Generate index files from reference fasta for bismark, bwameth and bwamem aligners"}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_METHYLSEQ (untar, gunzip, bismark/genomepreparation, bwameth/index, bwa/index, samtools/faidx) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_index_methylseq": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTA_INDEX_METHYLSEQ": null}}, "target": "Use nf-core subworkflow fasta_index_methylseq", "target_idx": 0}
{"id": "resource_bigslice_downloaddb_1", "category": "resource_profiling", "state": {"process": "BIGSLICE_DOWNLOADDB", "tool": "bigslice/downloaddb", "description": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_DOWNLOADDB (Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nu) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_viralrecon_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for amplicon analysis? Specific context: Assembly and intrahost/low-frequency variant calling for viral samples. Topics: amplicon, artic, assembly, covid-19, covid19, illumina. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we"}}, "target": "viralrecon", "target_idx": 3}
{"id": "noul_exit_code_137_cause_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry). Input files: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 2}
{"id": "mod_bam_methyldackel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignments using Methyldackel. (tools: bam_methyldackel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr_grea": "Perform Gene Ratio Enrichment Analysis", "bismark_align": "Performs alignment of BS-Seq reads using bismark", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "bam_methyldackel": "Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignmen"}}, "target": "bam_methyldackel", "target_idx": 4}
{"id": "samplesheet_arch_atacseq_replicates_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "ATAC-seq chromatin accessibility with biological replicates", "data_format": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns are standard for ATAC-seq chromatin accessibility with biological replicates input samplesheet?", "criteria": {"sample,bam": null, "sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "samplesheet_arch_rare_disease_trio_3_1", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Trio exome/genome sequencing (Proband, Mother, Father) with entry step FASTQC.", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_plink_vcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analyses variant calling files using plink (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_bcf": "Analyses binary variant call format (BCF) files using plink", "plink_vcf": "Analyses variant calling files using plink", "gem3_gem3indexer": "Create a GEM index from a FASTA file", "tidk_plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "plink_bmerge": "Merge a second PLINK binary fileset into the first and write a new combined PLINK binary fileset"}}, "target": "plink_vcf", "target_idx": 1}
{"id": "field_constraint_sex_1_0", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "noul_named_process_output_emits_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "local_subworkflow_irma_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should this step (irma) be packaged: Iterative assembly step for influenza and coronavirus?", "criteria": {"Local subworkflow IRMA": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow irma": null, "Leave them out": null}}, "target": "Local subworkflow IRMA", "target_idx": 0}
{"id": "mod_deacon_indexintersect_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Intersect multiple deacon indexes (A ∩ B ...) (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon/indexintersect": null, "bowtie/build": null, "pharmcat/phenotyper": null, "octopusv/plot": null, "biscuit/qc": null}}, "target": "deacon/indexintersect", "target_idx": 0}
{"id": "mod_t1k_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create a reference database and coordinate files for T1K. (tools: t1k)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"t1k_build": "A module to create a reference database and coordinate files for T1K.", "gatk4_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "hlala_preparegraph": "Pre-compute the graph index structure."}}, "target": "t1k_build", "target_idx": 0}
{"id": "mod_fastawindows_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly compute statistics over a fasta file in windows. (tools: fastawindows)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastawindows": null, "blobtk/snail": null, "quantify_rsem": null, "agat/convertspgff2gtf": null, "agat/convertbed2gff": null}}, "target": "fastawindows", "target_idx": 0}
{"id": "mod_shapeit5_phaserare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to phase rare variants onto a scaffold of common variants (output of phase_common / ligate).\nRequire feature AVX2. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shapeit5_phaserare": "Tool to phase rare variants onto a scaffold of common variants (output of phase_common / ligate).\nRequire feat", "glimpse2_splitreference": "Tool to create a binary reference panel for quick reading time.", "khmer_trimlowabund": "Removes low abundance k-mers from FASTA/FASTQ files", "bowtie_align": "Align reads to a reference genome using bowtie", "glimpse2_phase": "Tool for imputation and phasing from vcf file or directly from bam files."}}, "target": "shapeit5_phaserare", "target_idx": 0}
{"id": "schema_std_marsseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/marsseq", "description": "MARS-seq v2 pre-processing pipeline with velocity", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/marsseq?", "criteria": {"sample_id,bam,vcf,library_id,lane": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,fastq_1,strandedness": null, "sample,seq_data,pbi,start_from": null}}, "target": "fastq_1,fastq_2,batch,amp_batches,seq_batches", "target_idx": 1}
{"id": "mod_entrezdirect_xtract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries an NCBI database using an UID (tools: entrezdirect)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect_esummary": "Queries an NCBI database using Unique Identifier(s)", "entrezdirect_xtract": "Queries an NCBI database using an UID", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline", "chewbbaca_createschema": "Create a schema to determine the allelic profiles of a genome", "hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment"}}, "target": "entrezdirect_xtract", "target_idx": 1}
{"id": "pipe_all101_denovotranscript_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq. Topics: denovo-assembly, rna-seq, transcriptome. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel"}}, "target": "denovotranscript", "target_idx": 1}
{"id": "mod_echtvar_anno_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate a decomposed (and normalized) VCF with an echtvar file (tools: echtvar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ivar/variants": "Call variants from a BAM file using iVar", "echtvar/encode": "Make (encode) a new echtvar file from decomposed vcf", "atlas/call": "generate VCF file from a BAM file using various calling methods", "lofreq/alnqual": "Lofreq subcommand to for insert base and indel alignment qualities", "echtvar/anno": "Annotate a decomposed (and normalized) VCF with an echtvar file"}}, "target": "echtvar/anno", "target_idx": 4}
{"id": "schema_std_chipseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/chipseq", "assay": "chipseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/chipseq (ChIP-seq peak-calling, QC and differential analysis pipeline)?", "criteria": {"sample,input,output_path,checksum_md5,checksum_sha": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,fastq_1,fastq_2,replicate,antibody": null}}, "target": "sample,fastq_1,fastq_2,replicate,antibody", "target_idx": 3}
{"id": "pipe_all101_rnavar_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: gatk4 RNA variant calling pipeline. Topics: gatk4, rna, rnaseq, variant-calling, worflow. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra"}}, "target": "rnavar", "target_idx": 3}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_0_1", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_19", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_haplogrep2_classify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: classification into haplogroups (tools: haplogrep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pasty": "Serogroup Pseudomonas aeruginosa assemblies", "kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "haplogrep3_classify": "classification into haplogroups", "haplogrep2_classify": "classification into haplogroups", "picard_meanqualitybycycle": "Collect metrics about the mean quality by cycle of a paired-end library."}}, "target": "haplogrep2_classify", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_12", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_sylphtax_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple taxonomic profiles from sylphtaxt/taxprof into a tsv table (tools: sylphtax)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clippy": "Runs the Clippy CLIP peak caller", "sylph/sketchgenomes": "Sylph profile command for taxonoming profiling of genomes", "sylphtax/merge": "Merge multiple taxonomic profiles from sylphtaxt/taxprof into a tsv table", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "sylphtax/taxprof": "Incorporates taxonomy into sylph metagenomic classifier"}}, "target": "sylphtax/merge", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_3_2", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "FASTQC", "library_inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral amplicon sequencing with primers with entry step FASTQC.", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_custom_gtffilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter a gtf file to keep only regions that are located on a chromosome represented in a given fasta file (tools: gtffilter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "custom_gtffilter": "Filter a gtf file to keep only regions that are located on a chromosome represented in a given fasta file", "carveme_carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "hmmer_eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi"}}, "target": "custom_gtffilter", "target_idx": 2}
{"id": "local_subworkflow_variantsofint_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should VARIANTSOFINT (custom/variantsofint) be built?", "criteria": {"Leave them out": null, "Use nf-core subworkflow variantsofint": null, "Keep the modules in the main workflow": null, "Local subworkflow VARIANTSOFINT": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 3}
{"id": "pipe_all101_nanoseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Nanopore demultiplexing, QC and alignment pipeline. Topics: alignment, demultiplexing, nanopore, qc. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"detaxizer": null, "funcscan": null, "fetchngs": null, "rnafusion": null, "eager": null, "magmap": null, "nanoseq": null, "epitopeprediction": null}}, "target": "nanoseq", "target_idx": 6}
{"id": "mod_leehom_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bayesian reconstruction of ancient DNA fragments (tools: leehom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bamsormadup": "Parallel sorting and duplicate marking", "segemehl_align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection", "malt_build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "leehom": "Bayesian reconstruction of ancient DNA fragments", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "leehom", "target_idx": 3}
{"id": "mod_cleanifier_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a Cuckoo filter or Cuckoo hash table index from reference sequences (FASTA/FASTQ) for fast contamination removal. (tools: cleanifier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "bcftools_index": "Index VCF tools", "immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods.", "cleanifier_index": "Builds a Cuckoo filter or Cuckoo hash table index from reference sequences (FASTA/FASTQ) for fast contaminatio", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, "}}, "target": "cleanifier_index", "target_idx": 3}
{"id": "noul_mix_operator_async_emission_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "schema_std_longraredisease_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/longraredisease", "assay": "longraredisease pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/longraredisease (Long read sequencing pipeline to identify variants in patien)?", "criteria": {"sample_id,bam,vcf,library_id,lane": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,vcf,tbi": null, "family_id,sample,file_path,hpo_terms,sex": null}}, "target": "family_id,sample,file_path,hpo_terms,sex", "target_idx": 3}
{"id": "pipe_all101_reportho_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: nf-core pipeline for comparative analysis of ortholog predictions. Topics: ortholog. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"molkart": null, "rnadnavar": null, "seqinspector": null, "createpanelrefs": null, "magmap": null, "reportho": null, "bamtofastq": null, "rnavar": null, "rnasplice": null, "proteinannotator": null}}, "target": "reportho", "target_idx": 5}
{"id": "subworkflow_pkg_fastq_align_dedup_bwamem_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BWAMEM", "modules": ["parabricks/fq2bam", "samtools/index", "picard/addorreplacereadgroups", "picard/markduplicates", "bam_sort_stats_samtools", "fastq_align_bwa"], "description": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BWAMEM (parabricks/fq2bam, samtools/index, picard/addorreplacereadgroups, picard/markduplicates, bam_sort_stats_samtools, fastq_align_bwa) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_DEDUP_BWAMEM": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_dedup_bwamem": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwamem", "target_idx": 3}
{"id": "mod_windowmasker_mkcounts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program to generate frequency counts of repetitive units. (tools: windowmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"windowmasker/mkcounts": null, "nextclade/datasetget": null, "agat/spextractsequences": null, "gfatools/gfa2fa": null, "agrvate": null}}, "target": "windowmasker/mkcounts", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_0_0", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "mod_metamdbg_asm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metagenome assembler for long-read sequences (HiFi and ONT). (tools: metamdbg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "seqtk/cutn": "Generates a BED file containing genomic locations of lengths of N.", "ale": "ALE: assembly likelihood estimator.", "bamutil/trimbam": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping", "metamdbg/asm": "Metagenome assembler for long-read sequences (HiFi and ONT)."}}, "target": "metamdbg/asm", "target_idx": 4}
{"id": "noul_single_hyphen_cli_params_error_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_1_4", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,vcf": null, "sample,vcf,tbi": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "field_constraint_expected_cells_0_2", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "mod_samtools_bgzip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "gunzip": "Compresses and decompresses files.", "odgi/squeeze": "Squeezes multiple graphs in ODGI format into the same file in ODGI format.", "crabz/compress": "Compress files with crabz", "traitar/pfamget": "Download PFAM database for traitar phenotype prediction"}}, "target": "samtools/bgzip", "target_idx": 0}
{"id": "resource_amulety_balmpaired_1", "category": "resource_profiling", "state": {"process": "AMULETY_BALMPAIRED", "tool": "amulety/balmpaired", "description": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_BALMPAIRED (A module to create BALM paired embeddings of antibody (BCR) amino acid sequences) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_29", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_tiddit_sv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify chromosomal rearrangements. (tools: sv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiddit_sv": null, "minimac4_compressref": null, "pbsv_discover": null, "checkm2_predict": null, "octopusv_correct": null}}, "target": "tiddit_sv", "target_idx": 0}
{"id": "mod_pangolin_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Phylogenetic Assignment of Named Global Outbreak LINeages (tools: pangolin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"minibwa_map": "Align fastq reads to a fasta reference using minibwa", "pangolin_updatedata": "Phylogenetic Assignment of Named Global Outbreak LINeages", "pangolin_run": "Phylogenetic Assignment of Named Global Outbreak LINeages", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "taxonkit_list": "Generate taxonomic subtrees based on taxonids"}}, "target": "pangolin_run", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_12", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_6_4", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control", "pipeline": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns are standard for CUT&RUN / CUT&TAG chromatin profiling with IgG control input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,fastq_1,fastq_2": null, "sample,target,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "noul_undeclared_process_file_inputs_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "field_constraint_bam_0_11", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "mod_ismapper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify insertion sites positions in bacterial genomes (tools: ismapper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr_index": "Indexes a directory of fasta files for use with CoPTR", "ariba_getref": "Download and prepare database for Ariba analysis", "ismapper": "Identify insertion sites positions in bacterial genomes", "metaphlan_metaphlan": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing", "ariba_run": "Query input FASTQs against Ariba formatted databases"}}, "target": "ismapper", "target_idx": 2}
{"id": "mod_muscle5_super5_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Muscle is a program for creating multiple alignments of amino acid or nucleotide sequences. This particular module uses the super5 algorithm for very big alignments. It can permutate the guide tree according to a set of flags. (tools: muscle -super5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_merge": "Merge BAM or CRAM file", "shapeit5_phaserare": "Tool to phase rare variants onto a scaffold of common variants (output of phase_common / ligate).\nRequire feat", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "muscle5_super5": "Muscle is a program for creating multiple alignments of amino acid or nucleotide sequences. This particular mo", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}}, "target": "muscle5_super5", "target_idx": 3}
{"id": "schema_std_sarek_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "description": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/sarek?", "criteria": {"patient,sample,fastq_1,fastq_2,bam": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_1_15", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (custom/mira-nf) for Custom MIRA-NF Influenza / SC2 pipeline. Input files: Paired-end surveillance FASTQs from respiratory pathogen panels.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_fasta_newick_epang_gappa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in nf-core/phyloplace. (tools: fasta_newick_epang_gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_newick_epang_gappa": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in ", "suppa_diffsplice": "Perform differential splicing analysis using SUPPA.", "epang_split": "splits an alignment into reference and query parts", "salsa2": "SALSA, A tool to scaffold long read assemblies with HiC", "epang_place": "phylogenetic placement of query sequences in a reference tree"}}, "target": "fasta_newick_epang_gappa", "target_idx": 0}
{"id": "local_subworkflow_prepilluminareads_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should PREPILLUMINAREADS (trimmomatic) be built?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow PREPILLUMINAREADS": null, "Use nf-core subworkflow prepilluminareads": null, "Leave them out": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_2_0", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "HIFIADAPTERFILT", "library_inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "subworkflow_pkg_tif_registration_stainwarpy_0", "category": "subworkflow_packaging", "state": {"subworkflow": "TIF_REGISTRATION_STAINWARPY", "modules": ["stainwarpy/extractchannel", "stainwarpy/register", "stainwarpy/transformsegmask"], "description": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy"}, "question": {"type": "choice", "instructions": "How should TIF_REGISTRATION_STAINWARPY (stainwarpy/extractchannel, stainwarpy/register, stainwarpy/transformsegmask) be structured in DSL2?", "criteria": {"Use nf-core subworkflow tif_registration_stainwarpy": null, "Local subworkflow TIF_REGISTRATION_STAINWARPY": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow tif_registration_stainwarpy", "target_idx": 0}
{"id": "mod_thermorawfileparser_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parses a Thermo RAW file containing mass spectra to an open file format (tools: thermorawfileparser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash_sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "openms_filefilter": "Filters peptide/protein identification results by different criteria.", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "miniasm": "A very fast OLC-based de novo assembler for noisy long reads", "thermorawfileparser": "Parses a Thermo RAW file containing mass spectra to an open file format"}}, "target": "thermorawfileparser", "target_idx": 4}
{"id": "pipe_all101_rnaseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for rna analysis? Specific context: RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.. Topics: rna, rna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]"}}, "target": "rnaseq", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_4_1", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads from tumor biopsy without matched normal?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,normal,tumor": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_samtools_coverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: produces a histogram or table of coverage per chromosome (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig ", "yte": "A YAML template engine with Python expressions", "goleft_indexcov": "Quickly estimate coverage from a whole-genome bam or cram index. A bam index has 16KB resolution so that's wha", "tesorter": "An accurate and fast method to classify LTR-retrotransposons in plant genomes", "samtools_coverage": "produces a histogram or table of coverage per chromosome"}}, "target": "samtools_coverage", "target_idx": 4}
{"id": "samplesheet_arch_spatial_xenium_0_3", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "mod_fmhfunprofiler_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references. (tools: fmhfunprofiler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "fmhfunprofiler": "Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references.", "pneumocat": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "ensemblvep_download": "Ensembl Variant Effect Predictor (VEP). The cache downloading options are controlled through `task.ext.args`."}}, "target": "fmhfunprofiler", "target_idx": 2}
{"id": "mod_merqury_merqury_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: k-mer based assembly evaluation. (tools: merqury)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"merqury/merqury": "k-mer based assembly evaluation.", "fastk/fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "mashtree": "Quickly create a tree using Mash distances", "tesorter": "An accurate and fast method to classify LTR-retrotransposons in plant genomes"}}, "target": "merqury/merqury", "target_idx": 0}
{"id": "mod_sentieon_staralign_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using Sentieon STAR (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_staralign": "Align reads to a reference genome using Sentieon STAR", "allelecounter": "Generates a count of coverage of alleles", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "ganon_report": "Generate a ganon report file from the output of ganon classify", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "sentieon_staralign", "target_idx": 0}
{"id": "mod_coptr_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge reads that were mapped to multiple indices (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr/merge": "Merge reads that were mapped to multiple indices", "coptr/index": "Indexes a directory of fasta files for use with CoPTR", "oatk": "An nf-core module for the OATK", "coverm/contig": "Map reads to contigs and estimate coverage", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "coptr/merge", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic tumor-normal calling from pre-aligned BAM files)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "resource_bbmap_sendsketch_4", "category": "resource_profiling", "state": {"process": "BBMAP_SENDSKETCH", "tool": "bbmap/sendsketch", "description": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_SENDSKETCH (Compares query sketches to reference sketches hosted on a remote server via the ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_strandedness_0_12", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"type: boolean": null, "format: file-path": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_7", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_dastool_dastool_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DAS Tool binning step. (tools: dastool)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani/dist": "Simple ANI calculation between reference and query genomes.", "clame": "binning of metagenomic sequences", "concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "catpack/reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "dastool/dastool": "DAS Tool binning step."}}, "target": "dastool/dastool", "target_idx": 4}
{"id": "noul_deprecated_file_output_syntax_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_agrvate_2", "category": "resource_profiling", "state": {"process": "AGRVATE", "tool": "agrvate", "description": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGRVATE (Rapid identification of Staphylococcus aureus agr locus type and agr operon vari) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcftools_pluginsetgt_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSETGT", "tool": "bcftools/pluginsetgt", "description": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSETGT (Sets genotypes according to the specified criteria and filtering expressions. Fo) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_amulety_antiberty_0", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTY", "tool": "amulety/antiberty", "description": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTY (A module to create antiberty embeddings of antibody (BCR) amino acid sequences u) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_4_5", "category": "samplesheet_schema", "state": {"pipeline": "custom/mira-nf", "assay_type": "Custom MIRA-NF Influenza / SC2 pipeline", "data_format": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end surveillance FASTQs from respiratory pathogen panels?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_3", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "noul_multiple_script_sections_invalid_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_summarizedexperiment_summarizedexperiment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SummarizedExperiment container (tools: summarizedexperiment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bio2zarr/vcfpartition": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing.", "summarizedexperiment/summarizedexperiment": "SummarizedExperiment container", "atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files", "cafe": "Analysis of gene family evolution", "faqcs": "Perform adapter and quality trimming on sequencing reads with reporting"}}, "target": "summarizedexperiment/summarizedexperiment", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_0_3", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_centrifuge_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build centrifuge database for taxonomic profiling (tools: centrifuge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "vcfexpress": "Filter a VCF/BCF and optionally print by template expression. If no template is given the output will be VCF/B", "antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "trnascanse": "Detection of tRNA sequences using covariance models", "centrifuge/build": "Build centrifuge database for taxonomic profiling"}}, "target": "centrifuge/build", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_34", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_mhcquant_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Identify and quantify MHC eluted peptides from mass spectrometry raw data. Topics: dda, immunopeptidomics, mass-spectrometry, mhc, openms, peptides. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, "}}, "target": "mhcquant", "target_idx": 1}
{"id": "mod_anarcii_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A language model for antigen receptor numbering (tools: anarcii)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anarcii": "A language model for antigen receptor numbering", "bwa/aln": "Find SA coordinates of the input reads for bwa short-read mapping", "gedi/indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "genmod/annotate": "for annotating regions, frequencies, cadd scores"}}, "target": "anarcii", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_scrna_multiome_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: 10x Multiome single-cell joint RNA and ATAC chromatin)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Multiome single-cell joint RNA and ATAC chromatin with entry step FASTQC.", "criteria": {"sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,matrix": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "intent_debug_error_20", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "mod_cnvpytor_view_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: view function to generate vcfs (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "cnvnator/convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "cnvpytor/view": "view function to generate vcfs", "bwamem2/index": "Create BWA-mem2 index for reference genome"}}, "target": "cnvpytor/view", "target_idx": 3}
{"id": "noul_channel_filter_operator_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_amulety_esm2_5", "category": "resource_profiling", "state": {"process": "AMULETY_ESM2", "tool": "amulety/esm2", "description": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ESM2 (A module to create esm2 embeddings of antibody (BCR) amino acid sequences using ) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_default_empty_channel_behavior_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bwa_sampe_5", "category": "resource_profiling", "state": {"process": "BWA_SAMPE", "tool": "bwa/sampe", "description": "Convert paired-end bwa SA coordinate files to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMPE (Convert paired-end bwa SA coordinate files to SAM format) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_high", "target_idx": 2}
{"id": "mod_faqcs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform adapter and quality trimming on sequencing reads with reporting (tools: faqcs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"faqcs": "Perform adapter and quality trimming on sequencing reads with reporting", "last/mafconvert": "Converts MAF alignments in another format.", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "chromap/chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes"}}, "target": "faqcs", "target_idx": 0}
{"id": "mod_savana_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify and cluster SV breakpoints from long-read alignments. (tools: savana)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"savana_run": null, "gatk4_collectsvevidence": null, "fastq_extract_kraken_krakentools": null, "caddsv_get": null, "pydamage_analyze": null}}, "target": "savana_run", "target_idx": 0}
{"id": "resource_blast_makeblastdb_1", "category": "resource_profiling", "state": {"process": "BLAST_MAKEBLASTDB", "tool": "blast/makeblastdb", "description": "Builds a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_MAKEBLASTDB (Builds a BLAST database) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_arriba_visualisation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data. (tools: arriba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bandage/image": null, "arriba/visualisation": null, "pretextsnapshot": null, "datavzrd": null, "mmseqs/databases": null}}, "target": "arriba/visualisation", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_28", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_centrifuge_centrifuge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classifies metagenomic sequence data (tools: centrifuge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_seqreformat": "Reformats files with t-coffee", "goatools_findenrichment": "Find enriched GO terms in a list of genes", "kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "conifer": "Calculate confidence scores from Kraken2 output", "centrifuge_centrifuge": "Classifies metagenomic sequence data"}}, "target": "centrifuge_centrifuge", "target_idx": 4}
{"id": "mod_bam_tumor_normal_somatic_variant_calling_strelka_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform variant calling on a paired tumor normal set of samples using strelka somatic mode.\nf1r2 output of mutect2 is run through learnreadorientationmodel to get the artifact priors.\nRun the input bam files through getpileupsummarries and then calculatecontamination to get the contamination and segmentation tables.\nFilter the mutect2 output vcf using filtermutectcalls, artifact priors and the contamination & segmentation tables for additional filtering. (tools: bam_tumor_normal_somatic_variant_calling_strelka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_tumor_normal_somatic_variant_calling_strelka": "Perform variant calling on a paired tumor normal set of samples using strelka somatic mode.\nf1r2 output of mut", "sentieon_tnscope": "TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, us", "bam_create_som_pon_gatk": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a geno", "bcl_demultiplex": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq", "minimap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences"}}, "target": "bam_tumor_normal_somatic_variant_calling_strelka", "target_idx": 0}
{"id": "mod_sylph_sketchgenomes_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sylph profile command for taxonoming profiling of genomes (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xeniumranger/rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "sylph/sketchgenomes": "Sylph profile command for taxonoming profiling of genomes", "dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "expansionhunterdenovo/profile": "Compute genome-wide STR profile"}}, "target": "sylph/sketchgenomes", "target_idx": 1}
{"id": "mod_salmon_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create index for salmon (tools: salmon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "pypgx/createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "salmon/index": "Create index for salmon", "tidk/explore": "`tidk explore` attempts to find the simple telomeric repeat unit in the genome provided.\nIt will report this r", "bowtie/build": "Create bowtie index for reference genome"}}, "target": "salmon/index", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_3_1", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Tumor-only somatic variant calling without matched normal with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_haplocheck_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial DNA. Haplocheck also works as a proxy tool for nDNA studies and provides\nusers a graphical report to investigate the contamination further. Internally, it uses the\nHaplogrep tool, that supports rCRS and RSRS mitochondrial versions. (tools: haplocheck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/happy": null, "saltshaker/call": null, "eklipse": null, "haplocheck": null, "traitar/pfamget": null}}, "target": "haplocheck", "target_idx": 3}
{"id": "samplesheet_arch_methylseq_bisulfite_5_4", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/methylseq, determine the input samplesheet column structure for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq).", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_openms_fileconverter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureXML, consensusXML, idXML). (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pridepy_downloadfile": "Download a single file from the PRIDE Archive by name using pridepy.", "openms_fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX", "mat2json": "converst matlab .mat files into json or csv files.", "datavzrd": "Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables.", "gatk4_shiftfasta": "Create a fasta with the bases shifted by offset"}}, "target": "openms_fileconverter", "target_idx": 1}
{"id": "noul_container_environment_specification_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_seqtk_subseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select only sequences that match the filtering condition (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/subtract": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining po", "bcftools/filter": "Filters VCF files", "filtlong": "Filtlong filters long reads based on quality measures or short read data.", "seqtk/subseq": "Select only sequences that match the filtering condition", "stainwarpy/transformsegmask": "Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy"}}, "target": "seqtk/subseq", "target_idx": 3}
{"id": "mod_pmdtools_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pmdtools command to filter ancient DNA molecules from others (tools: pmdtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"malt_run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "malt_build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "pmdtools_filter": "pmdtools command to filter ancient DNA molecules from others", "ltrretriever_ltrretriever": "Identifies LTR retrotransposons using LTR_retriever", "cellbender_removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data"}}, "target": "pmdtools_filter", "target_idx": 2}
{"id": "mod_rpbp_estimatemetagenebayesfactors_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of actively translating ribosomes.\nFor each candidate (read length, P-site offset) pair, Rp-Bp fits two\ncompeting Bayesian models to the count window around annotated start\ncodons: a \"periodic\" model whose signal repeats every three\nnucleotides, and a \"non-periodic\" background model. The Bayes factor\n(ratio of the two marginal likelihoods) quantifies how much the data\nprefer the periodic explanation.\n\nReturns one row per (length, offset) pair with the mean and variance of\nthe log Bayes factor across MCMC samples. Downstream,\n`rpbp/selectperiodicoffsets` picks the best offset per length from\nthis table, and `rpbp/getperiodiclengthsoffsets` filters to the\nhigh-confidence pairs that drive ORF-level scoring.\n\nUses the Stan models bundled inside the rpbp Python package. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp_extractmetageneprofiles": null, "gcta_makegrmpart": null, "taxonkit_list": null, "rpbp_estimatemetagenebayesfactors": null, "rpbp_preparegenome": null}}, "target": "rpbp_estimatemetagenebayesfactors", "target_idx": 3}
{"id": "mod_gffcompare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare, merge, annotate and estimate accuracy of generated gtf files (tools: gffcompare)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf2cytosure": "Convert VCF with structural variations to CytoSure format", "gffcompare": "Compare, merge, annotate and estimate accuracy of generated gtf files", "opt_flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple", "yara_mapper": "Align reads to a reference genome using YARA", "opt_track": "track aligns query probe sequences to any target transcriptome"}}, "target": "gffcompare", "target_idx": 1}
{"id": "resource_bio2zarr_vcfpartition_2", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCFPARTITION", "tool": "bio2zarr/vcfpartition", "description": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCFPARTITION (Outputs a set of region strings that partition indexed VCF/BCF files for paralle) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_4_2", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment?", "criteria": {"lane,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_phyloplace_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.. Topics: evolution, evolutionary-tree, phylogenetic-placement, phylogenetics, sequence-classification, taxonomy-assignment. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": null, "differentialabundance": null, "phyloplace": null, "sarek": null, "callingcards": null, "genomeassembler": null, "references": null, "bamtofastq": null}}, "target": "phyloplace", "target_idx": 2}
{"id": "mod_deepvariant_vcfstatsreport_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "atlas/call": "generate VCF file from a BAM file using various calling methods", "gatk4/composestrtablefile": "This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Drags", "deepvariant/vcfstatsreport": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "ucsc/wigtobigwig": "Convert ascii format wig file to binary big wig format"}}, "target": "deepvariant/vcfstatsreport", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_1", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_bamtools_stats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files. (tools: bamtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_stats": null, "salsa2": null, "gt_stat": null, "isoseq_cluster": null, "bamtools_stats": null}}, "target": "bamtools_stats", "target_idx": 4}
{"id": "pipe_all101_pathogensurveillance_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for biosurveillance. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqsubmit": "nf-core pipeline for data submission to ENA", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo"}}, "target": "pathogensurveillance", "target_idx": 8}
{"id": "subworkflow_pkg_archive_extract_1", "category": "subworkflow_packaging", "state": {"subworkflow": "ARCHIVE_EXTRACT", "modules": ["gunzip", "untar", "unzip"], "description": "Extract archive(s) from any format"}, "question": {"type": "choice", "instructions": "How should ARCHIVE_EXTRACT (gunzip, untar, unzip) be structured in DSL2?", "criteria": {"Local subworkflow ARCHIVE_EXTRACT": null, "Leave them out": null, "Use nf-core subworkflow archive_extract": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow archive_extract", "target_idx": 2}
{"id": "resource_baysor_preview_5", "category": "resource_profiling", "state": {"process": "BAYSOR_PREVIEW", "tool": "baysor/preview", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_PREVIEW (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_gxf_busco_plot_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_GXF_BUSCO_PLOT", "modules": ["busco/busco", "busco/plot", "gffread"], "description": "Runs BUSCO for input assemblies and their annotations in GFF/GFF3/GTF format, and creates summary plots using `busco --plot`"}, "question": {"type": "choice", "instructions": "How should FASTA_GXF_BUSCO_PLOT (busco/busco, busco/plot, gffread) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_gxf_busco_plot": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_GXF_BUSCO_PLOT": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_gxf_busco_plot", "target_idx": 0}
{"id": "resource_bcftools_reheader_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_REHEADER", "tool": "bcftools/reheader", "description": "Reheader a VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_REHEADER (Reheader a VCF file) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_epitopeprediction_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/epitopeprediction. Description: A bioinformatics best-practice analysis pipeline for epitope prediction and annotation.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/epitopeprediction.", "criteria": {"patient,sample,vcf,status,cna": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,alleles,mhc_class,filename": null, "sample,fastq,cell_count": null}}, "target": "sample,alleles,mhc_class,filename", "target_idx": 2}
{"id": "mod_purecn_intervalfile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate on and off-target intervals for PureCN from a list of targets (tools: purecn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purecn_normaldb": null, "purecn_coverage": null, "purecn_intervalfile": null, "strvctvre_strvctvre": null, "damageprofiler": null}}, "target": "purecn_intervalfile", "target_idx": 2}
{"id": "pipe_all101_differentialabundance_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for atac-seq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d"}}, "target": "differentialabundance", "target_idx": 4}
{"id": "mod_hmmer_hmmemit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: emit sequences from a profile HMM (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmfetch": "extract hmm from hmm database file or create index for hmm database", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "hmmer_hmmemit": "emit sequences from a profile HMM", "conifer": "Calculate confidence scores from Kraken2 output", "hmmer_hmmstat": "display summary statistics for each profile HMM in an HMM database file"}}, "target": "hmmer_hmmemit", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_7_0", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_7", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_phenotype_1_12", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_17", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_container_environment_specification_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_5_5", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic tumor-normal calling from pre-aligned BAM files.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "mod_deeptools_multibamsummary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes read coverage for genomic regions (bins) across the entire genome. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"repeatmasker/rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "deeptools/multibamsummary": "Computes read coverage for genomic regions (bins) across the entire genome.", "gcta/addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "deeptools/multibamsummary", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_4_3", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed single-end long reads from tiled viral amplicons?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "resource_bedops_convert2bed_4", "category": "resource_profiling", "state": {"process": "BEDOPS_CONVERT2BED", "tool": "bedops/convert2bed", "description": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_CONVERT2BED (Convert BAM/GFF/GTF/GVF/PSL files to bed) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_biohansel_0", "category": "resource_profiling", "state": {"process": "BIOHANSEL", "tool": "biohansel", "description": "Use k-mers to rapidly subtype S. enterica genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOHANSEL (Use k-mers to rapidly subtype S. enterica genomes) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_prepontreads_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should PREPONTREADS (porechop, nanoplot) be built?", "criteria": {"Use nf-core subworkflow prepontreads": null, "Local subworkflow PREPONTREADS": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Xenium in situ subcellular spatial RNA transcriptomics)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,vcf": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "resource_argnorm_5", "category": "resource_profiling", "state": {"process": "ARGNORM", "tool": "argnorm", "description": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARGNORM (Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed b) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_0_0", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral amplicon sequencing with primers?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_cafe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analysis of gene family evolution (tools: cafe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/condensedepthevidence": "Merges adjacent DepthEvidence records", "cafe": "Analysis of gene family evolution", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "nonpareil/set": "Visualise metagenome redundancy curves in PNG format from multiple Nonpareil npo files in a single image"}}, "target": "cafe", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_10", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "schema_std_rnasplice_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnasplice", "description": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnasplice?", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "sample,fastq_1,fastq_2,library_id,lane": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fastq_1,fastq_2,strandedness,condition": null}}, "target": "sample,fastq_1,fastq_2,strandedness,condition", "target_idx": 3}
{"id": "samplesheet_arch_amplicon_16s_paired_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: 16S rRNA / ITS microbiome amplicon profiling)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_ivar_consensus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a consensus sequence from a BAM file using iVar (tools: ivar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"multiqc": "Aggregate results from bioinformatics analyses across many samples into a single report", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "ivar/consensus": "Generate a consensus sequence from a BAM file using iVar", "ivar/trim": "Trim primer sequences rom a BAM file with iVar", "ucsc/bedgraphtobigwig": "Convert a bedGraph file to bigWig format."}}, "target": "ivar/consensus", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cageseq) for CAGE-seq 5-prime capped transcript end sequencing. Input files: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping.", "question": {"type": "choice", "instructions": "Which columns are standard for CAGE-seq 5-prime capped transcript end sequencing input samplesheet?", "criteria": {"sample,vcf": null, "sample,tss_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_fastq_align_star_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bowtie2 then sort with samtools (tools: fastq_align_star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "purecn_normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as", "fastq_align_star": "Align reads to a reference genome using bowtie2 then sort with samtools", "wipertools_fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files"}}, "target": "fastq_align_star", "target_idx": 3}
{"id": "mod_rseqc_splitbam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split BAM file based on gene list in BED format (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvnator/convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ensemblvep/vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "rseqc/splitbam": "Split BAM file based on gene list in BED format"}}, "target": "rseqc/splitbam", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_2_48", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "noul_single_hyphen_cli_params_error_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_last_lastdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare sequences for subsequent alignment with lastal. (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_lastdb": null, "paraphrase": null, "last_dotplot": null, "last_postmask": null, "coverm_genome": null}}, "target": "last_lastdb", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_44", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_goleft_indexsplit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly generate evenly sized (by amount of data) regions across a number of bam/cram files (tools: goleft)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files", "ascat": "copy number profiles of tumour cells.", "seqkit/replace": "Use seqkit to find/replace strings within sequences and sequence headers", "goleft/indexsplit": "Quickly generate evenly sized (by amount of data) regions across a number of bam/cram files", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "goleft/indexsplit", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Visium spatial transcriptomics with histology image. Input files: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates.", "question": {"type": "choice", "instructions": "Which columns are standard for 10x Visium spatial transcriptomics with histology image input samplesheet?", "criteria": {"sample,fastq_1,image": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_5_2", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: 16S rRNA / ITS microbiome amplicon profiling.", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,otu_table": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/bacass --input samplesheet.csv (Assay: Hybrid bacterial assembly combining short Illumina and long Nanopore reads)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/bacass, determine the input samplesheet column structure for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "intent_debug_error_23", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "prepare_data": null, "ask_question": null}}, "target": "debug_error", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_10", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_fastq_decontaminate_deacon_hostile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile (tools: fastq_decontaminate_deacon_hostile)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_decontaminate_deacon_hostile": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "osfclient/fetch": "A python library and a command-line client for up- and downloading files to and from your Open Science Framewo", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bcftools/reheader": "Reheader a VCF file"}}, "target": "fastq_decontaminate_deacon_hostile", "target_idx": 0}
{"id": "mod_gatk4_concordance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate concordance of an input VCF against a validated truth VCF (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rrnatranscripts": "Ribosomal RNA extraction from a GTF file.", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4/concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "bacphlip": "A bacteriophage lifestyle prediction tool"}}, "target": "gatk4/concordance", "target_idx": 2}
{"id": "schema_std_methylseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/methylseq. Description: Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/methylseq.", "criteria": {"sample,fastq_1,fastq_2,bam,cram": null, "sample,fastq_1,fastq_2,genome": null, "sample,fastq_1,fastq_2,barcode_details": null, "sample,fastq_1,fastq_2,library_id,lane": null}}, "target": "sample,fastq_1,fastq_2,genome", "target_idx": 1}
{"id": "mod_untar_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract files from tar, tar.gz, tar.bz2, tar.xz archives (tools: untar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives", "picard_extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at", "svync": "A tool to standardize VCF files from structural variant callers", "tar": "Compress directories into tarballs with various compression options", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo"}}, "target": "untar", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_37", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_aria2_2", "category": "resource_profiling", "state": {"process": "ARIA2", "tool": "aria2", "description": "CLI Download utility"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIA2 (CLI Download utility) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_spatialaxe_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay": "spatialaxe pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/spatialaxe (A bioinformatics best-practice processing and quality contro)?", "criteria": {"seeds,network,perturbed_networks": null, "sample,bundle,image": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,type,level,msfile": null}}, "target": "sample,bundle,image", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_28", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_49", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "field_constraint_bai_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_0_2", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Tumor-only somatic variant calling without matched normal?", "criteria": {"patient,normal,tumor": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_duckdb_table2parquet_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a delimited text table (CSV or TSV, gzipped or not) to Parquet (tools: duckdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"duckdb/table2parquet": "Convert a delimited text table (CSV or TSV, gzipped or not) to Parquet", "manta/germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "rseqc/readduplication": "Calculate read duplication rate", "csvtk/join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "thermorawfileparser": "Parses a Thermo RAW file containing mass spectra to an open file format"}}, "target": "duckdb/table2parquet", "target_idx": 0}
{"id": "mod_fastq_create_umi_consensus_fgbio_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads\nconvert them to unmapped BAM file, map them to the reference genome,\nand finally use the mapped information to group UMIs and generate consensus reads in each group (tools: fastq_create_umi_consensus_fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "diann_insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "fgbio_filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "fastq_create_umi_consensus_fgbio": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads\nconvert them to unmapped B"}}, "target": "fastq_create_umi_consensus_fgbio", "target_idx": 4}
{"id": "pipe_all101_mnaseseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze MNase-seq analysis pipeline using BWA and DANPOS2.. Topics: mnase-seq, nucleosome, nucleosome-maps, nucleosome-positioning. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi"}}, "target": "mnaseseq", "target_idx": 0}
{"id": "mod_polypolish_polish_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Polishing genome assemblies with short reads. (tools: polypolish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fast2q": "A program that counts sequence occurrences in FASTQ files.", "modkit/pileup": "A bioinformatics tool for working with modified bases", "seqkit/sana": "Sanitize broken single line FASTQ files", "modkit/repair": "Repair the MM/ML tags on trimmed or hard-clipped ONT reads using untrimmed ONT reads.", "polypolish/polish": "Polishing genome assemblies with short reads."}}, "target": "polypolish/polish", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_19", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_bcftools_query_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts fields from VCF or BCF files and outputs them in user-defined format. (tools: query)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mash_dist": "Calculate Mash distances between reference and query sequences", "entrezdirect_esummary": "Queries an NCBI database using Unique Identifier(s)", "mifaser": "Functional annotation of metagenomic reads by assigning enzyme commission (EC) numbers", "bcftools_query": "Extracts fields from VCF or BCF files and outputs them in user-defined format.", "bio2zarr_vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}}, "target": "bcftools_query", "target_idx": 3}
{"id": "field_constraint_fastq_2_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "schema_std_sopa_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sopa", "assay": "sopa pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/sopa (Nextflow version of Sopa - spatial omics pipeline and analys)?", "criteria": {"sample,id,data_path,fastq_dir,cytaimage": null, "sample_id,bam,vcf,library_id,lane": null, "id,path": null, "sample,input,output_path,checksum_md5,checksum_sha": null}}, "target": "sample,id,data_path,fastq_dir,cytaimage", "target_idx": 0}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/diaproteomics) for Data-Independent Acquisition (DIA) quantitative mass spectrometry. Input files: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null, "sample,mzml": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "mod_viralconsensus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast and memory-efficient viral consensus genome sequence generation from read alignments (tools: viralconsensus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/createtaxdb": "Adds taxonomy information to an existing MMseqs2 database", "checkv/updatedatabase": "Construct the database necessary for checkv's quality assessment", "checkv/downloaddatabase": "Construct the database necessary for checkv's quality assessment", "gatk4/printsvevidence": "WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end an", "viralconsensus": "Fast and memory-efficient viral consensus genome sequence generation from read alignments"}}, "target": "viralconsensus", "target_idx": 4}
{"id": "pipe_all101_proteogenomicsdb_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for cosmic analysis? Specific context: The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis.. Topics: cosmic, gnomad, protein-databases, proteogenomics, proteomics, pypgatk. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-"}}, "target": "proteogenomicsdb", "target_idx": 0}
{"id": "mod_fastk_fastk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast K-mer counter for high-fidelity shotgun datasets (tools: fastk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eautils_fastqstats": null, "blast_blastdbcmd": null, "ganon_report": null, "ganon_table": null, "fastk_fastk": null}}, "target": "fastk_fastk", "target_idx": 4}
{"id": "mod_mitohifi_findmitoreference_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download a mitochondrial genome to be used as reference for MitoHiFi.\n\nNOTE: An optional NCBI API key can be supplied to MITOHIFI_FINDMITOREFERENCE.\nThis should be set using Nextflow's secrets functionality:\n\n`nextflow secrets set NCBI_API_KEY <key>`\n\nSee https://www.nextflow.io/docs/latest/secrets.html for more information. (tools: findMitoReference.py)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svdss_index": null, "custom_sratoolsncbisettings": null, "shapeit5_switch": null, "mitohifi_findmitoreference": null, "coverm_genome": null}}, "target": "mitohifi_findmitoreference", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_44", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_4_3", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "template": "nf-core/hic"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bed": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_39", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_seqtk_cutn_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a BED file containing genomic locations of lengths of N. (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "bcftools/filter": "Filters VCF files", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "seqtk/cutn": "Generates a BED file containing genomic locations of lengths of N.", "viber": "Multisample subclonal deconvolution of cancer genome sequencing data."}}, "target": "seqtk/cutn", "target_idx": 3}
{"id": "noul_channel_factory_inside_process_body_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_bam_variant_calling_mpileup_bcftools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS", "modules": ["gawk", "tabix/bgzip", "bcftools/mpileup", "bcftools/merge", "bcftools/annotate", "bcftools/concat", "vcf_gather_bcftools"], "description": "Subworkflow to compute genotype likelihoods from BAM files using"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS (gawk, tabix/bgzip, bcftools/mpileup, bcftools/merge, bcftools/annotate, bcftools/concat, vcf_gather_bcftools) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_variant_calling_mpileup_bcftools": null}}, "target": "Use nf-core subworkflow bam_variant_calling_mpileup_bcftools", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pre-aligned BAM variant calling pipeline", "data_format": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_13", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_fetch_clean_hostile_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FETCH_CLEAN_HOSTILE", "modules": ["hostile/fetch", "hostile/clean"], "description": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files"}, "question": {"type": "choice", "instructions": "How should FASTQ_FETCH_CLEAN_HOSTILE (hostile/fetch, hostile/clean) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_fetch_clean_hostile": null, "Leave them out": null, "Local subworkflow FASTQ_FETCH_CLEAN_HOSTILE": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_fetch_clean_hostile", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_1_2", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_bcftools_concat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenate VCF files (tools: concat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmemit": "emit sequences from a profile HMM", "bcftools_concat": "Concatenate VCF files", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "portello": "Transfer HiFi read mappings from their own assembly contigs to a standard reference", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "bcftools_concat", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_25", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_40", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_bowtie2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BOWTIE2", "modules": ["bowtie2/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bowtie2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BOWTIE2 (bowtie2/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_BOWTIE2": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_bowtie2": null}}, "target": "Use nf-core subworkflow fastq_align_bowtie2", "target_idx": 3}
{"id": "mod_emmtyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: EMM typing of Streptococcus pyogenes assemblies (tools: emmtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "rsem_preparereference": "Prepare a reference genome for RSEM", "emmtyper": "EMM typing of Streptococcus pyogenes assemblies", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "emmtyper", "target_idx": 2}
{"id": "resource_bedgovcf_0", "category": "resource_profiling", "state": {"process": "BEDGOVCF", "tool": "bedgovcf", "description": "Convert a BED file to a VCF file according to a YAML config"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDGOVCF (Convert a BED file to a VCF file according to a YAML config) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_ensemblvep_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ensembl Variant Effect Predictor (VEP). The cache downloading options are controlled through `task.ext.args`. (tools: ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vclust_cluster": null, "atlasgeneannotationmanipulation_gtf2featureannotation": null, "ensemblvep_download": null, "annosine": null, "deeptools_plotcorrelation": null}}, "target": "ensemblvep_download", "target_idx": 2}
{"id": "mod_genescopefk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A derivative of GenomeScope2.0 modified to work with FastK (tools: genescopefk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"phyloflash": "phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illum", "openms/idripper": "Split a merged identification file into their originating identification files", "ganon/report": "Generate a ganon report file from the output of ganon classify", "genescopefk": "A derivative of GenomeScope2.0 modified to work with FastK", "ganon/buildcustom": "Build ganon database using custom reference sequences."}}, "target": "genescopefk", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_4_2", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "mod_rmats_prep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data. (tools: rmats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lofreq_viterbi": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl", "regtools_junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.", "varlociraptor_callvariants": "Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlocira", "rmats_prep": "MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data.", "ctatsplicing_prepgenomelib": "Reference preparation for CTAT-splicing"}}, "target": "rmats_prep", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_0_2", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,matrix": null, "plate,sample,bam": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_atlas_recal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gives an estimation of the sequencing bias based on known invariant sites (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sratools/prefetch": null, "atlas/recal": null, "atlas/call": null, "vembrane/filter": null, "cnvkit/fix": null}}, "target": "atlas/recal", "target_idx": 1}
{"id": "subworkflow_pkg_bam_ngscheckmate_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_NGSCHECKMATE", "modules": ["bcftools/mpileup", "ngscheckmate/ncm"], "description": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs."}, "question": {"type": "choice", "instructions": "How should BAM_NGSCHECKMATE (bcftools/mpileup, ngscheckmate/ncm) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow bam_ngscheckmate": null, "Local subworkflow BAM_NGSCHECKMATE": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_ngscheckmate", "target_idx": 1}
{"id": "resource_artic_aligntrim_3", "category": "resource_profiling", "state": {"process": "ARTIC_ALIGNTRIM", "tool": "artic/aligntrim", "description": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_ALIGNTRIM (Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme ) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_5_3", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents).", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Tumor-only somatic variant calling without matched normal", "data_format": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns are standard for Tumor-only somatic variant calling without matched normal input samplesheet?", "criteria": {"patient,normal,tumor": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bcftools_plotvcfstats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots the output of bcftools stats (tools: plot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqe": "fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data.", "cooltools_eigscis": "Perform eigen value decomposition on a cooler matrix to calculate compartment signal by finding the eigenvecto", "jvarkit_wgscoverageplotter": "Plot whole genome coverage from BAM/CRAM file as SVG", "gcta_grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`", "bcftools_plotvcfstats": "Plots the output of bcftools stats"}}, "target": "bcftools_plotvcfstats", "target_idx": 4}
{"id": "mod_rtgtools_format_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts the contents of sequence data files (FASTA/FASTQ/SAM/BAM) into the RTG Sequence Data File (SDF) format. (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "samplesheetparser/info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "rtgtools/format": "Converts the contents of sequence data files (FASTA/FASTQ/SAM/BAM) into the RTG Sequence Data File (SDF) forma", "fastani": "Alignment-free computation of Average Nucleotide Identity (ANI)"}}, "target": "rtgtools/format", "target_idx": 3}
{"id": "samplesheet_arch_cutandrun_pe_8_3", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "template": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null, "sample,spikein,fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_6_4", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns are standard for Viral genome sequencing on Oxford Nanopore MinION / GridION input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "intent_build_pipeline_1", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "prepare_data": null, "ask_question": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "resource_bedtools_nuc_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_NUC", "tool": "bedtools/nuc", "description": "Profiles the nucleotide content of intervals in a fasta file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_NUC (Profiles the nucleotide content of intervals in a fasta file.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_11", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_goatools_findenrichment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find enriched GO terms in a list of genes (tools: goatools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"decoupler_decoupler": null, "agat_spextractsequences": null, "mmseqs_cluster": null, "goatools_findenrichment": null, "deeptools_computematrix": null}}, "target": "goatools_findenrichment", "target_idx": 3}
{"id": "mod_hificnv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number variant calling from PacBio HiFi reads (tools: hificnv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hificnv": "Copy number variant calling from PacBio HiFi reads", "amulety_antiberty": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety.", "cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions.", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "wisecondorx_predict": "Find copy number aberrations"}}, "target": "hificnv", "target_idx": 0}
{"id": "noul_module_metadata_propagation_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_11", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_savana_classify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classify structural variants using SAVANA (tools: savana)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tabix_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files", "savana_classify": "Classify structural variants using SAVANA", "ganon_classify": "Classify FASTQ files against ganon database", "centrifuge_centrifuge": "Classifies metagenomic sequence data", "meryl_histogram": "A genomic k-mer counter (and sequence utility) with nice features."}}, "target": "savana_classify", "target_idx": 1}
{"id": "mod_sentieon_varcal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module for Sentieons VarCal. The VarCal algorithm calculates the Variant Quality Score Recalibration (VQSR).\nVarCal builds a recalibration model for scoring variant quality.\nhttps://support.sentieon.com/manual/usages/general/#varcal-algorithm (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"traitar/run": null, "optitype": null, "sentieon/varcal": null, "sentieon/bwaindex": null, "sentieon/coveragemetrics": null}}, "target": "sentieon/varcal", "target_idx": 2}
{"id": "mod_amplify_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: AMPlify is an attentive deep learning model for antimicrobial peptide prediction. (tools: amplify)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macrel_contigs": null, "sniffles": null, "amplify_predict": null, "ampcombi2_cluster": null, "circularmapper_realignsamfile": null}}, "target": "amplify_predict", "target_idx": 2}
{"id": "noul_module_metadata_propagation_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_bbmap_sendsketch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compares query sketches to reference sketches hosted on a remote server via the Internet. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm", "bbmap/sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "gappa/examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "sentieon/rsemcalculateexpression": "Calculate expression with RSEM", "ganon/buildcustom": "Build ganon database using custom reference sequences."}}, "target": "bbmap/sendsketch", "target_idx": 1}
{"id": "mod_bismark_deduplicate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes alignments to the same position in the genome\nfrom the Bismark mapping output. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "finaletoolkit/endmotifs": "Measure the frequency of 5' k-mer end motifs.", "yak/count": "a tool to build k-mer hash table for fasta and fastq files", "bismark/coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts."}}, "target": "bismark/deduplicate", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_11", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_bam_subsampledepth_samtools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subsample a BAM/CRAM/SAM file using samtools to a given mean depth.\n\"region\", \"subsample_fraction\", \"mean_depth\" and \"depth\" keys will be added to the meta\nmap to distinguish the different file generated and therefore shouldn't be used.\nThe `depth` key will be added to the meta map of the output channel. (tools: bam_subsampledepth_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vg/construct": null, "bam_subsampledepth_samtools": null, "fastq_subsample_fq_salmon": null, "fq/subsample": null, "jellyfish/dump": null}}, "target": "bam_subsampledepth_samtools", "target_idx": 1}
{"id": "resource_amulety_antiberty_4", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTY", "tool": "amulety/antiberty", "description": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTY (A module to create antiberty embeddings of antibody (BCR) amino acid sequences u) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_nonpareil_set_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualise metagenome redundancy curves in PNG format from multiple Nonpareil npo files in a single image (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vuegen": "The VueGen nf-core module is designed to automate report generation from outputs produced by other modules, su", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "t1k/run": "write your description here", "nonpareil/set": "Visualise metagenome redundancy curves in PNG format from multiple Nonpareil npo files in a single image"}}, "target": "nonpareil/set", "target_idx": 4}
{"id": "samplesheet_arch_prealigned_cram_indexed_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Genome analysis from reference-compressed CRAM files)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Genome analysis from reference-compressed CRAM files.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,cram,crai": null, "sample,bam,bai": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_0_4", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_27", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_slimfastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, efficient, lossless compression of FASTQ files. (tools: slimfastq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba_getref": null, "slimfastq": null, "hmmer_eslalipid": null, "seqtk_sample": null, "adapterremoval": null}}, "target": "slimfastq", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_46", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "noul_deprecated_file_output_syntax_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_gatk4_splitncigarreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits reads that contain Ns in their cigar string (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_splitncigarreads": "Splits reads that contain Ns in their cigar string", "rclone_copy": "Copy files or directories between local and/or remote storage using Rclone", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "sentieon_rsempreparereference": "Prepare a reference genome for RSEM"}}, "target": "gatk4_splitncigarreads", "target_idx": 0}
{"id": "mod_abundance_differential_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A subworkflow for filtering differential abundance results (tools: abundance_differential_filter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abundance_differential_filter": "A subworkflow for filtering differential abundance results", "dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "bwafastalign_index": "Create BWA-FASTALIGN index for reference genome", "pbptyper": "Assign PBP type of Streptococcus pneumoniae assemblies", "shinyngs_app": "build and deploy Shiny apps for interactively mining differential abundance data"}}, "target": "abundance_differential_filter", "target_idx": 0}
{"id": "mod_star_genomegenerate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create index for STAR (tools: star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star_genomegenerate": "Create index for STAR", "lofreq_alnqual": "Lofreq subcommand to for insert base and indel alignment qualities", "bcftools_index": "Index VCF tools", "angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}}, "target": "star_genomegenerate", "target_idx": 0}
{"id": "mod_star_genomegenerate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create index for STAR (tools: star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie/build": "Create bowtie index for reference genome", "qcat": "Demultiplexer for Nanopore samples", "star/genomegenerate": "Create index for STAR", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "custom/matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass."}}, "target": "star/genomegenerate", "target_idx": 2}
{"id": "mod_mlst_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run Torsten Seemann's classic MLST on a genome assembly (tools: mlst)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "mlst": "Run Torsten Seemann's classic MLST on a genome assembly", "srst2_srst2": "Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLS", "saltshaker_classify": "mtDNA deletion and duplication classification downstream of mitosalt", "cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions."}}, "target": "mlst", "target_idx": 1}
{"id": "mod_xeniumranger_relabel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngscheckmate/vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "xeniumranger/relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts.", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "xeniumranger/relabel", "target_idx": 2}
{"id": "schema_std_rnastructurome_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnastructurome", "description": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnastructurome?", "criteria": {"sample,fastq_1,fastq_2,strandedness,condition": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,sample_id,fastq_1,fastq_2,method": null, "patient,vcf,tbi,dataset,tumour_sample": null}}, "target": "sample,sample_id,fastq_1,fastq_2,method", "target_idx": 2}
{"id": "resource_amrfinderplus_run_3", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_RUN", "tool": "amrfinderplus/run", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_RUN (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_status_0_0", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "noul_single_hyphen_cli_params_error_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_gatk4_getpileupsummaries_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarizes counts of reads that support reference, alternate and other alleles for given sites. Results can be used with CalculateContamination. Requires a common germline variant sites file, such as from gnomAD. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "svaba": "SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide ", "gatk4/baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "gatk4/getpileupsummaries": "Summarizes counts of reads that support reference, alternate and other alleles for given sites. Results can be", "nanoq": "Nanoq implements ultra-fast read filters and summary reports for high-throughput nanopore reads."}}, "target": "gatk4/getpileupsummaries", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_cram_indexed_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Genome analysis from reference-compressed CRAM files", "data_format": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Genome analysis from reference-compressed CRAM files with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,cram": null, "sample,cram,crai": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "mod_bam_dedup_stats_samtools_umitools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats (tools: bam_dedup_stats_samtools_umitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_dedup_stats_samtools_umitools": "UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats", "lofreq/callparallel": "It predicts variants using multiple processors", "fgbio/copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "fgbio/groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, "}}, "target": "bam_dedup_stats_samtools_umitools", "target_idx": 0}
{"id": "mod_prinseqplusplus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PRINSEQ++ is a C++ implementation of the prinseq-lite.pl program. It can be used to filter, reformat or trim genomic and metagenomic sequence data (tools: prinseqplusplus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/run": null, "fastq_sanitise_seqkit": null, "ariba/getref": null, "prinseqplusplus": null, "gatk4/composestrtablefile": null}}, "target": "prinseqplusplus", "target_idx": 3}
{"id": "pipe_core10_taxprofiler_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Multi-tool taxonomic classification and profiling across Kraken2, MetaPhlAn, Centrifuge, and mOTUs for shotgun metagenomic data.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": null, "atacseq": null, "rnaseq": null, "sarek": null, "ampliseq": null, "viralrecon": null, "chipseq": null, "eager": null, "mag": null, "scrnaseq": null}}, "target": "taxprofiler", "target_idx": 0}
{"id": "schema_std_seqinspector_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/seqinspector. Description: Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput. .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/seqinspector.", "criteria": {"sample,fastq_1,fastq_2,genome": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2,rundir,tags": null}}, "target": "sample,fastq_1,fastq_2,rundir,tags", "target_idx": 3}
{"id": "resource_bcftools_query_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_QUERY", "tool": "bcftools/query", "description": "Extracts fields from VCF or BCF files and outputs them in user-defined format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_QUERY (Extracts fields from VCF or BCF files and outputs them in user-defined format.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_5_4", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: FAIRE-seq / DNAse-seq open chromatin profiling.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_fgbio_filterconsensusreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDuplexConsensusReads. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio/callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "fasta_binning_concoct": "Runs the CONCOCT workflow of contig binning", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "fgbio/groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "staphopiasccmec": "Predicts Staphylococcus aureus SCCmec type based on primers."}}, "target": "fgbio/filterconsensusreads", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_6", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_any2fasta_4", "category": "resource_profiling", "state": {"process": "ANY2FASTA", "tool": "any2fasta", "description": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input files may be gzip, bzip2, zip, or zstd compressed."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANY2FASTA (Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_confusing_combine_with_mix_semantics_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bamutil_clipoverlap_4", "category": "resource_profiling", "state": {"process": "BAMUTIL_CLIPOVERLAP", "tool": "bamutil/clipoverlap", "description": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_CLIPOVERLAP (clips overlapping read pairs. When two mates overlap, this tool will clip the re) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_proteinfold_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/proteinfold. Description: Protein 3D structure prediction pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/proteinfold.", "criteria": {"id,fasta,sequence": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,bundle,image": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "id,fasta,sequence", "target_idx": 0}
{"id": "pipe_all101_rangeland_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple steps to arrive at a set of trend files related to land-cover changes.. Topics: earth-observation, landsat, satellite-imagery, spectral-unmixing, trend-analysis, trends. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]"}}, "target": "rangeland", "target_idx": 2}
{"id": "mod_catpack_contigs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"longphase_phase": null, "catpack_summarise": null, "catpack_contigs": null, "snapaligner_align": null, "catpack_download": null}}, "target": "catpack_contigs", "target_idx": 2}
{"id": "resource_bcftools_pluginimputeinfo_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINIMPUTEINFO", "tool": "bcftools/pluginimputeinfo", "description": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINIMPUTEINFO (Adds imputation information metrics to the INFO field based on selected FORMAT t) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_samtools_samples_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Write sample names and path to reference genome of an alignment to a text file. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_pmd": null, "atlas_splitmerge": null, "plink2_vcf2bgen": null, "quilt_quilt2": null, "samtools_samples": null}}, "target": "samtools_samples", "target_idx": 4}
{"id": "mod_propr_propd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform differential proportionality analysis (tools: propr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms/peptideindexer": "Refreshes the protein references for all peptide hits.", "dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "propr/propd": "Perform differential proportionality analysis", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}}, "target": "propr/propd", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_6_0", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns are standard for Metagenomic MAG assembly with comparative groups input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "samplesheet_arch_scrna_multiome_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for 10x Multiome single-cell joint RNA and ATAC chromatin. Input files: Paired FASTQs for both GEX and ATAC modalities per nucleus.", "question": {"type": "choice", "instructions": "Which columns are standard for 10x Multiome single-cell joint RNA and ATAC chromatin input samplesheet?", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "mod_regtools_junctionsextract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format. (tools: regtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "fgumi_simplexmetrics": "Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data", "deeptools_bigwigcompare": "Compare two bigWig files based on the number of mapped reads", "fusioninspector": "Validation of Fusion Transcript Predictions", "regtools_junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format."}}, "target": "regtools_junctionsextract", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_1", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_artic_aligntrim_1", "category": "resource_profiling", "state": {"process": "ARTIC_ALIGNTRIM", "tool": "artic/aligntrim", "description": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_ALIGNTRIM (Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme ) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bwa_aln_5", "category": "resource_profiling", "state": {"process": "BWA_ALN", "tool": "bwa/aln", "description": "Find SA coordinates of the input reads for bwa short-read mapping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_ALN (Find SA coordinates of the input reads for bwa short-read mapping) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "mod_bam2fastx_bam2fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data (tools: bam2fastx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "gcta_fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "mmseqs_createtsv": "Create a tsv file from a query and a target database as well as the result database", "hifiadapterfilt_downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "bam2fastx_bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}}, "target": "bam2fastx_bam2fastq", "target_idx": 4}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/dualrnaseq) for Dual RNA-seq simultaneous host and pathogen transcriptomics. Input files: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen.", "question": {"type": "choice", "instructions": "Which columns are standard for Dual RNA-seq simultaneous host and pathogen transcriptomics input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,host_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_8", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_dshbio_filterbed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter features in gzipped BED format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedgovcf": null, "pureclip": null, "dshbio/filterbed": null, "cooler/makebins": null, "agat/convertbed2gff": null}}, "target": "dshbio/filterbed", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_0_4", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fastq_1,fastq_2": null, "sample,otu_table": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_fastq_1_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "samplesheet_arch_scrna_10x_v3_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry))", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1,fastq_2": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "pipe_all101_nanostring_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: An analysis pipeline for Nanostring nCounter expression data.. Topics: nanostring, nanostringnorm. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"oncoanalyser": null, "nanostring": null, "phaseimpute": null, "variantprioritization": null, "viralintegration": null, "proteinannotator": null, "seqsubmit": null, "genomeassembler": null}}, "target": "nanostring", "target_idx": 1}
{"id": "resource_bedtools_subtract_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SUBTRACT", "tool": "bedtools/subtract", "description": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining portion of A."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SUBTRACT (Finds overlaps between two sets of regions (A and B), removes the overlaps from ) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_raredisease_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay": "raredisease pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/raredisease (Call and score variants from WGS/WES of rare disease patient)?", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,vcf,tbi": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 2}
{"id": "mod_gapseq_medium_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict growth medium from a draft model and pathway predictions (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_calibratedragstrmodel": "estimates the parameters for the DRAGstr model", "deepmased_predict": "DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED", "gapseq_fill": "Perform gap filling on draft metabolic model", "memote_report": "Generate HTML quality report snapshot for genome-scale metabolic models", "gapseq_medium": "Predict growth medium from a draft model and pathway predictions"}}, "target": "gapseq_medium", "target_idx": 4}
{"id": "pipe_all101_airrflow_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for airr analysis? Specific context: B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework. Topics: airr, b-cell, immcantation, immunorepertoire, repseq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, "}}, "target": "airrflow", "target_idx": 2}
{"id": "pipe_all101_variantbenchmarking_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research. Topics: benchmark, small-variants, structural-variants, variant-calling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralrecon": null, "circdna": null, "demultiplex": null, "longraredisease": null, "rnastructurome": null, "fastquorum": null, "cageseq": null, "variantbenchmarking": null, "raredisease": null, "taxprofiler": null}}, "target": "variantbenchmarking", "target_idx": 7}
{"id": "mod_malt_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics. (tools: malt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_idripper": "Split a merged identification file into their originating identification files", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "alignoth": "Creating alignment plots from bam files", "deeptools_plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "malt_run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h"}}, "target": "malt_run", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_1_8", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_mira_influenza_sc2_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (custom/mira-nf) for Custom MIRA-NF Influenza / SC2 pipeline. Input files: Paired-end surveillance FASTQs from respiratory pathogen panels.", "question": {"type": "choice", "instructions": "In Nextflow pipeline custom/mira-nf, determine the input samplesheet column structure for: Custom MIRA-NF Influenza / SC2 pipeline.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "subworkflow_pkg_bam_tumor_only_somatic_variant_calling_gatk_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a single tumor sample using mutect2 tumor only mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk": null, "Leave them out": null, "Local subworkflow BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK": null}}, "target": "Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk", "target_idx": 1}
{"id": "resource_bwa_index_0", "category": "resource_profiling", "state": {"process": "BWA_INDEX", "tool": "bwa/index", "description": "Create BWA index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_INDEX (Create BWA index for reference genome) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "10x Multiome single-cell joint RNA and ATAC chromatin", "data_format": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Multiome single-cell joint RNA and ATAC chromatin input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,matrix": null, "sample,bam": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_0_0", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform", "pipeline": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_clair3_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clair3 is a germline small variant caller for long-reads (tools: clair3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_index_filter_deacon": null, "clair3": null, "parabricks/dbsnp": null, "entrezdirect/xtract": null, "parabricks/deepvariant": null}}, "target": "clair3", "target_idx": 1}
{"id": "mod_finaletoolkit_aggbw_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregates a bigWig signal over constant-length intervals\ndefined in a BED file. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmcopy_readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows", "finaletoolkit_aggbw": "Aggregates a bigWig signal over constant-length intervals\ndefined in a BED file.", "windowmasker_ustat": "A program to take a counts file and creates a file of genomic co-ordinates to be masked.", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "finaletoolkit_aggbw", "target_idx": 1}
{"id": "mod_plasmidfinder_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify plasmids in bacterial sequences and assemblies (tools: plasmidfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plasmidfinder": null, "meningotype": null, "amrfinderplus/update": null, "abritamr/run": null, "macrel/contigs": null}}, "target": "plasmidfinder", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_5_3", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline custom/mira-nf, determine the input samplesheet column structure for: Custom MIRA-NF Influenza / SC2 pipeline.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_0_39", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_named_output_channel_access_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_pychopper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify, orient and trim nanopore cDNA reads (tools: pychopper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "percolator": "Rescore peptide-spectrum matches and estimate false discovery rates using the Percolator semi-supervised learn", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "pychopper": "Identify, orient and trim nanopore cDNA reads", "cnvkit_batch": "Copy number variant detection from high-throughput sequencing data"}}, "target": "pychopper", "target_idx": 3}
{"id": "mod_gatk4_denoisereadcounts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Denoises read counts to produce denoised copy ratios (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_learnreadorientationmodel": null, "gatk4_denoisereadcounts": null, "hiphase": null, "gatk4_applyvqsr": null, "gatk4_modelsegments": null}}, "target": "gatk4_denoisereadcounts", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_31", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_pasty_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serogroup Pseudomonas aeruginosa assemblies (tools: pasty)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pasty": "Serogroup Pseudomonas aeruginosa assemblies", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "mirtop_stats": "mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category.", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "pasty", "target_idx": 0}
{"id": "mod_genomad_endtoend_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify mobile genetic elements present in genomic assemblies (tools: genomad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": null, "svaba": null, "ensemblvep_vep": null, "biomformat_convert": null, "genomad_endtoend": null}}, "target": "genomad_endtoend", "target_idx": 4}
{"id": "mod_samtools_import_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converts FASTQ files to unmapped SAM/BAM/CRAM (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/import": null, "entrezdirect/esummary": null, "maltextract": null, "plink2/vcf": null, "art/illumina": null}}, "target": "samtools/import", "target_idx": 0}
{"id": "mod_angsd_dosaf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate site allele frequencies from BAM files. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastx_collapser": "Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts)", "angsd_soapsnpcalibration": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments.", "angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "angsd_dosaf": "Estimate site allele frequencies from BAM files.", "bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "angsd_dosaf", "target_idx": 3}
{"id": "mod_vembrane_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter VCF files with vembrane (tools: vembrane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vembrane_filter": "Filter VCF files with vembrane", "mmseqs_easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "bbmap_filterbyname": "Filter out sequences by sequence header name(s)", "ensemblvep_filtervep": "Filter variants based on Ensembl Variant Effect Predictor (VEP) annotations.", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in"}}, "target": "vembrane_filter", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_6_5", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multiplexed Oxford Nanopore run with barcode demultiplexing input samplesheet?", "criteria": {"sample,barcode": null, "sample,fastq_1,fastq_2": null, "sample,barcode,flowcell,kit,fastq": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "noul_include_modular_process_syntax_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_bam_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "schema_std_abotyper_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/abotyper", "description": "A pipeline for characterising the Human Blood Group and Red Cell Antigens using Oxford Nanopore third-generation sequencing data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/abotyper?", "criteria": {"sample,nuclear_image,spot_table,membrane_image": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_biscuit_qc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform basic quality control on a BAM file generated with Biscuit (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hisat2/build": "Builds HISAT2 index for reference genome", "biscuit/mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "pairtools/flip": "Flip pairs to get an upper-triangular matrix"}}, "target": "biscuit/qc", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_0_0", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_4_0", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform", "pipeline": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Short or long reads with run accession and library instrument platform?", "criteria": {"sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bcftools_rohviz_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualise the output of bcftools roh (tools: roh-viz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"datavzrd": null, "xeniumranger/resegment": null, "tcoffee/align": null, "drep/compare": null, "bcftools/rohviz": null}}, "target": "bcftools/rohviz", "target_idx": 4}
{"id": "field_constraint_strandedness_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"format: file-path": null, "pattern: ^[0-9]+$": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "pipe_all101_proteinfold_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Protein 3D structure prediction pipeline. Topics: alphafold2, colabfold, esmfold, protein-fold-prediction, protein-folding, protein-sequences. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]"}}, "target": "proteinfold", "target_idx": 9}
{"id": "mod_sequenzautils_bam2seqz_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sequenza-utils bam2seqz process BAM and Wiggle files to produce a seqz file (tools: sequenzautils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequenzautils_bam2seqz": null, "ascat": null, "cnaqc": null, "lima": null, "happy_sompy": null}}, "target": "sequenzautils_bam2seqz", "target_idx": 0}
{"id": "mod_famsa_guidetree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Renders a guidetree in famsa (tools: famsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clustalo_align": "Align sequences using Clustal Omega", "picard_renamesampleinvcf": "changes name of sample in the vcf file", "emboss_cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "famsa_guidetree": "Renders a guidetree in famsa", "dastool_dastool": "DAS Tool binning step."}}, "target": "famsa_guidetree", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_5_3", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Xenium in situ subcellular spatial RNA transcriptomics.", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,image": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_explore_search_plot_tidk_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_EXPLORE_SEARCH_PLOT_TIDK", "modules": ["seqkit/seq", "seqkit/sort", "tidk/explore", "tidk/plot", "tidk/search"], "description": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats"}, "question": {"type": "choice", "instructions": "How should FASTA_EXPLORE_SEARCH_PLOT_TIDK (seqkit/seq, seqkit/sort, tidk/explore, tidk/plot, tidk/search) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTA_EXPLORE_SEARCH_PLOT_TIDK": null, "Use nf-core subworkflow fasta_explore_search_plot_tidk": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_explore_search_plot_tidk", "target_idx": 2}
{"id": "mod_vclust_prefilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by filtering out dissimilar sequences before the alignment step. (tools: vclust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity", "vclust_prefilter": "The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by ", "humid": "HUMID is a tool to quickly and easily remove duplicate reads from FASTQ files, with or without UMIs.", "vsearch_dereplicate": "Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same l", "cdhit_cdhit": "Cluster protein sequences using sequence similarity"}}, "target": "vclust_prefilter", "target_idx": 1}
{"id": "intent_build_pipeline_8", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 2}
{"id": "mod_deeptools_bigwigcompare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare two bigWig files based on the number of mapped reads (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/bigwigcompare": null, "ucsc/bedgraphtobigwig": null, "stadeniolib/scramble": null, "mirtop/counts": null, "ucsc/wigtobigwig": null}}, "target": "deeptools/bigwigcompare", "target_idx": 0}
{"id": "mod_cellrangerarc_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's ARC pipelines analyze sequencing data produced from Chromium Single Cell ARC. Uses the cellranger-arc count command. (tools: cellrangerarc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifitrimmer/filterbam": "Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLA", "viennarna/rnafold": "Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary str", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "cellrangerarc/count": "Module to use Cell Ranger's ARC pipelines analyze sequencing data produced from Chromium Single Cell ARC. Uses", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin"}}, "target": "cellrangerarc/count", "target_idx": 3}
{"id": "mod_samtools_cat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenate BAM or CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "samtools_cat": "Concatenate BAM or CRAM file"}}, "target": "samtools_cat", "target_idx": 4}
{"id": "field_constraint_fastq_1_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "field_constraint_phenotype_1_13", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "enum: [normal, tumor]": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "mod_qcat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplexer for Nanopore samples (tools: qcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/seqreformat": "Reformats files with t-coffee", "samtools/fasta": "Converts a SAM/BAM/CRAM file to FASTA", "bclconvert": "Demultiplex Illumina BCL files", "bases2fastq": "Demultiplex Element Biosciences bases files", "qcat": "Demultiplexer for Nanopore samples"}}, "target": "qcat", "target_idx": 4}
{"id": "mod_cnvkit_reference_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compile a coverage reference from the given files (normal samples). (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ilastik/multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "cnvkit/call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples).", "cnvkit/batch": "Copy number variant detection from high-throughput sequencing data", "last/split": "Find split or spliced alignments in a MAF file"}}, "target": "cnvkit/reference", "target_idx": 2}
{"id": "mod_ncbigenomedownload_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to quickly download assemblies from NCBI's Assembly database (tools: ncbigenomedownload)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krona/ktupdatetaxonomy": "KronaTools Update Taxonomy downloads a taxonomy database", "ncbigenomedownload": "A tool to quickly download assemblies from NCBI's Assembly database", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "multiseqdemux": "Identify singlets, doublets and negative cells from multiplexing experiments. Annotate singlets by tags.", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "ncbigenomedownload", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_5_5", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "template": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/bacass, determine the input samplesheet column structure for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "pipe_all101_rnastructurome_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data. Topics: dms, map, rna-structure, rnacentral, rnaframework, rt-stop. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": null, "rnasplice": null, "mhcquant": null, "demo": null, "atacseq": null, "taxprofiler": null, "rnastructurome": null, "proteinfamilies": null, "oncoanalyser": null, "mag": null}}, "target": "rnastructurome", "target_idx": 6}
{"id": "samplesheet_arch_cageseq_transcription_2_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,tss_bed": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_channel_join_operator_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "field_constraint_phenotype_0_3", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_7_1", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_eager_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A fully reproducible and state-of-the-art ancient DNA analysis pipeline. Topics: adna, ancient-dna-analysis, ancientdna, genome, metagenomics, pathogen-genomics. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "metapep": "From metagenomes to epitopes and beyond", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG."}}, "target": "eager", "target_idx": 2}
{"id": "mod_malt_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics. (tools: malt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ashlar": null, "osfclient_fetch": null, "fq_lint": null, "alignoth": null, "malt_build": null}}, "target": "malt_build", "target_idx": 4}
{"id": "resource_bcftools_index_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_INDEX", "tool": "bcftools/index", "description": "Index VCF tools"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_INDEX (Index VCF tools) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_genomicrelatedness_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomicrelatedness", "description": "Bioinformatics pipeline for estimating genetic relatedness from low-coverage whole-genome sequencing (sWGS) data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/genomicrelatedness?", "criteria": {"sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample_id,bam,vcf,library_id,lane": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "sample,fastq_1,fastq_2,bam,cram", "target_idx": 3}
{"id": "mod_ensemblvep_vep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`. (tools: ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc_mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkref c", "annotsv_installannotations": "Install the AnnotSV annotations", "atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "ensemblvep_vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`.", "strvctvre_strvctvre": "a structural variant classifier for exonic deletions and duplications"}}, "target": "ensemblvep_vep", "target_idx": 3}
{"id": "mod_fastcov_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a coverage plot from one or more bam files (tools: fastcov)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem2_gemindexer": "Create a GEM index from a FASTA file", "bbmap_pileup": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file.", "allelecounter": "Generates a count of coverage of alleles", "fastcov": "Generate a coverage plot from one or more bam files", "fasta_newick_epang_gappa": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in "}}, "target": "fastcov", "target_idx": 3}
{"id": "resource_braker3_3", "category": "resource_profiling", "state": {"process": "BRAKER3", "tool": "braker3", "description": "Gene prediction in novel genomes using RNA-seq and protein homology information"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRAKER3 (Gene prediction in novel genomes using RNA-seq and protein homology information) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_fastquorum_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs). Topics: consensus, umi, umis, unique-molecular-identifier. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]"}}, "target": "fastquorum", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_41", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "field_constraint_strandedness_0_14", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"type: boolean": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_angsd_dosaf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate site allele frequencies from BAM files. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd/gl": null, "rseqc/junctionannotation": null, "angsd/dosaf": null, "busco/busco": null, "angsd/soapsnpcalibration": null}}, "target": "angsd/dosaf", "target_idx": 2}
{"id": "pipe_all101_mcmicro_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data.. Topics: bioformats, image-analysis, image-processing, microscopy, multiplexed-imaging, ome-tiff. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro"}}, "target": "mcmicro", "target_idx": 1}
{"id": "mod_plasmidid_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: assembles bacterial plasmids (tools: plasmidid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "opt/stat": "stat summarizes opt binding predictions", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "plasmidid": "assembles bacterial plasmids", "fgumi/codec": "Call CODEC consensus reads from a UMI-grouped BAM with fgumi"}}, "target": "plasmidid", "target_idx": 3}
{"id": "schema_std_isoseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/isoseq. Description: Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences and produce a bed annotation. .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/isoseq.", "criteria": {"vcf,fasta,genome,site,source": null, "sample,seq_data,pbi,start_from": null, "sample_id,name,description,path,path_2": null, "sample,fasta": null}}, "target": "sample,seq_data,pbi,start_from", "target_idx": 1}
{"id": "pipe_all101_genomeassembler_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for genome-assembly. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "metapep": "From metagenomes to epitopes and beyond", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]"}}, "target": "genomeassembler", "target_idx": 8}
{"id": "samplesheet_arch_taxprofiler_shotgun_6_5", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multi-taxonomic profiling of complex metagenomic shotgun reads input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_eagle2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform phasing of genotyped data with or without a reference panel (tools: eagle2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamaps_classify": null, "shapeit5_phasecommon": null, "hifiasm": null, "eagle2": null, "lissero": null}}, "target": "eagle2", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_3_2", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Multiome single-cell joint RNA and ATAC chromatin with entry step FASTQC.", "criteria": {"sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "pipe_all101_rangeland_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple steps to arrive at a set of trend files related to land-cover changes.. Topics: earth-observation, landsat, satellite-imagery, spectral-unmixing, trend-analysis, trends. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcscan": null, "cageseq": null, "imcyto": null, "circdna": null, "lsmquant": null, "multiplesequencealign": null, "rnadnavar": null, "proteinfamilies": null, "rangeland": null, "differentialabundance": null}}, "target": "rangeland", "target_idx": 8}
{"id": "mod_gatk4_composestrtablefile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Dragstr model during single sample auto calibration CalibrateDragstrModel. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "gatk4/composestrtablefile": "This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Drags", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje"}}, "target": "gatk4/composestrtablefile", "target_idx": 1}
{"id": "mod_ucsc_bedclip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove lines from bed file that refer to off-chromosome locations. (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "svtk/standardize": "Convert SV calls to a standardized format.", "ucsc/bedclip": "Remove lines from bed file that refer to off-chromosome locations.", "pharmcat/reporter": "The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescri", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "ucsc/bedclip", "target_idx": 2}
{"id": "mod_amulety_translate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety_embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "gridss_generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "vsearch_sintax": "Taxonomic classification using the sintax algorithm.", "amulety_translate": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast.", "amulety_antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}}, "target": "amulety_translate", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_1_5", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "10x Multiome single-cell joint RNA and ATAC chromatin", "data_format": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,matrix": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay_type": "Long-read Pacific Biosciences HiFi sequencing", "data_format": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "pipe_all101_scnanoseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics. Topics: 10xgenomics, long-read-sequencing, nanopore, rna-seq, rnaseq, scrna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": null, "reportho": null, "differentialabundance": null, "proteinfamilies": null, "variantprioritization": null}}, "target": "scnanoseq", "target_idx": 0}
{"id": "field_constraint_expected_cells_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"pattern: ^\\S+\\.csv$": null, "format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "noul_undeclared_process_file_inputs_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_phaseimpute_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A bioinformatics pipeline to phase and impute genetic data. Topics: genomics, genotype, imputation, low-pass-sequencing, phasing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"imcyto": null, "viralmetagenome": null, "multiplesequencealign": null, "rnafusion": null, "differentialabundance": null, "rnavar": null, "mag": null, "phaseimpute": null, "rnadnavar": null, "bacass": null}}, "target": "phaseimpute", "target_idx": 7}
{"id": "noul_include_modular_process_syntax_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_cadd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions variants in the human genome. (tools: cadd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cadd": null, "circexplorer2_annotate": null, "ampcombi2_complete": null, "pypolca_run": null, "anarcii": null}}, "target": "cadd", "target_idx": 0}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_6_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Which columns are standard for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cutandrun_pe_5_5", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "template": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cutandrun, determine the input samplesheet column structure for: CUT&RUN / CUT&TAG chromatin profiling with IgG control.", "criteria": {"sample,target,control": null, "sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_17", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_gridss_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignments. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"survivor_simsv": "Simulate an SV VCF file based on a reference genome", "gridss_preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and ", "gridss_call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment", "autocycler_subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "gridss_generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements."}}, "target": "gridss_call", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_8_0", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,vcf": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "mod_meryl_unionsum_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A genomic k-mer counter (and sequence utility) with nice features. (tools: meryl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribotish/predict": "Quality control of riboseq bam data", "meryl/unionsum": "A genomic k-mer counter (and sequence utility) with nice features.", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "fastk/merge": "A tool to merge FastK histograms", "bio2zarr/vcf2zarrexplode": "Convert VCF(s) to intermediate columnar format (ICF)"}}, "target": "meryl/unionsum", "target_idx": 1}
{"id": "mod_clame_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: binning of metagenomic sequences (tools: clame)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"phyloflash": "phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illum", "elprep/filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "clame": "binning of metagenomic sequences", "crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "numorph/intensity": "performs shading correction and intensity normalization between tile stacks"}}, "target": "clame", "target_idx": 2}
{"id": "pipe_all101_bacass_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Simple bacterial assembly and annotation pipeline. Topics: assembly, bacterial-genomes, denovo, denovo-assembly, genome-assembly, hybrid-assembly. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeassembler": null, "phaseimpute": null, "hgtseq": null, "bacass": null, "nanostring": null, "mcmicro": null, "magmap": null, "fastquorum": null}}, "target": "bacass", "target_idx": 3}
{"id": "mod_biscuit_pileup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/pileup": null, "picard/sortvcf": null, "bismark/report": null, "bismark/coverage2cytosine": null, "qualimap/rnaseq": null}}, "target": "biscuit/pileup", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_33", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_spatialaxe_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data. Topics: 10x-genomics, atera, image-processing, spatial, spatial-data-analysis, spatial-transcriptomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]"}}, "target": "spatialaxe", "target_idx": 2}
{"id": "resource_bam2fastx_bam2fastq_0", "category": "resource_profiling", "state": {"process": "BAM2FASTX_BAM2FASTQ", "tool": "bam2fastx/bam2fastq", "description": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAM2FASTX_BAM2FASTQ (Conversion of PacBio BAM files into gzipped fastq files, including splitting of ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "core_tool_multiqc_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Aggregate and summarize quality control metrics and analysis logs across FastQC, Cutadapt, and STAR into a single interactive HTML report.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"trimmomatic": "Flexible read trimming tool", "fastp": "All-in-one FASTQ preprocessor", "multiqc": "Aggregate bioinformatics analysis results across multiple tools into a single report", "picard": "Command-line tools for manipulating high-throughput sequencing data", "fastqc": "Quality control tool for high throughput sequence data"}}, "target": "multiqc", "target_idx": 2}
{"id": "resource_authentict_deam2cont_0", "category": "resource_profiling", "state": {"process": "AUTHENTICT_DEAM2CONT", "tool": "authentict/deam2cont", "description": "Use deamination patterns to estimate contamination in single-stranded libraries"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTHENTICT_DEAM2CONT (Use deamination patterns to estimate contamination in single-stranded libraries) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_blast_blastp_3", "category": "resource_profiling", "state": {"process": "BLAST_BLASTP", "tool": "blast/blastp", "description": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTP (BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (prot) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_bacmodel_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacmodel", "description": "Systems-based bacterial functional modeling pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/bacmodel?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "id,fasta,query": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_45", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_pmdtools_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pmdtools command to filter ancient DNA molecules from others (tools: pmdtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "pneumocat": null, "lissero": null, "mapad/map": null, "pmdtools/filter": null}}, "target": "pmdtools/filter", "target_idx": 4}
{"id": "intent_prepare_data_7", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "prepare_data": null, "ask_question": null}}, "target": "prepare_data", "target_idx": 2}
{"id": "resource_adapterremoval_3", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVAL", "tool": "adapterremoval", "description": "Trim sequencing adapters and collapse overlapping reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVAL (Trim sequencing adapters and collapse overlapping reads) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Trio exome/genome sequencing (Proband, Mother, Father)", "data_format": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_7_0", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_ctatsplicing_startocancerintrons_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detection and annotation of aberrant splicing isoforms in cancer transcriptomes (tools: ctatsplicing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "taxonkit/list": "Generate taxonomic subtrees based on taxonids", "modkit/bedmethyltobigwig": "Convert a bedMethyl file to bigWig format using modkit", "leafcutter/clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter"}}, "target": "ctatsplicing/startocancerintrons", "target_idx": 1}
{"id": "pipe_all101_hgtseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for bwa-mem analysis? Specific context: A pipeline to investigate horizontal gene transfer from NGS data. Topics: bwa-mem, bwa-mem2, fastqc, genomics-visualization, ggbio, horizontal-gene-transfer. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]"}}, "target": "hgtseq", "target_idx": 7}
{"id": "samplesheet_arch_pacbio_hifi_wgs_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/genomeassembler) for Long-read Pacific Biosciences HiFi sequencing. Input files: Single HiFi BAM or FastQ.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/genomeassembler, determine the input samplesheet column structure for: Long-read Pacific Biosciences HiFi sequencing.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Tumor-only somatic variant calling without matched normal. Input files: Paired-end FASTQ reads from tumor biopsy without matched normal.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Tumor-only somatic variant calling without matched normal?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_refsolver_score_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score a query sequence dictionary against a reference using ref-solver (tools: refsolver)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/filtervarianttranches": "Apply tranche filtering", "refsolver/score": "Score a query sequence dictionary against a reference using ref-solver", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "biscuit/index": "Indexes a reference genome for use with Biscuit", "find/concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size"}}, "target": "refsolver/score", "target_idx": 1}
{"id": "mod_bwa_aln_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find SA coordinates of the input reads for bwa short-read mapping (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "bwa/aln": "Find SA coordinates of the input reads for bwa short-read mapping", "bwamem2/mem": "Performs fastq alignment to a fasta reference using BWA", "orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics.", "bwamem3/mem": "Align fastq reads to a fasta reference using bwa-mem3"}}, "target": "bwa/aln", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_27", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "noul_default_empty_channel_behavior_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "schema_std_taxprofiler_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "description": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/taxprofiler?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,group,path,ref,method": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 1}
{"id": "noul_publishdir_directive_usage_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_11", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_publishdir_directive_usage_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_mmseqs_contig_taxonomy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assign taxonomy to contigs using the MMseqs2 workflow. (tools: mmseqs_contig_taxonomy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_contig_taxonomy": "Assign taxonomy to contigs using the MMseqs2 workflow.", "samclip": "Filters SAM/BAM/CRAM files for soft and hard clipped alignments", "ribocode_gtfupdate": "Update GTF annotation file for RiboCode compatibility", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}}, "target": "mmseqs_contig_taxonomy", "target_idx": 0}
{"id": "mod_ampcombi2_parsetables_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A submodule that parses and standardizes the results from various antimicrobial peptide identification tools. (tools: ampcombi2/parsetables)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amplify_predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "irescue": "Quantification of transposable elements expression in scRNA-seq", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "ampcombi2_parsetables", "target_idx": 2}
{"id": "mod_angsd_gl_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculated genotype likelihoods from BAM files. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd/gl": "Calculated genotype likelihoods from BAM files.", "angsd/realsfs": "Estimate site frequency spectrum from site allele frequencies", "angsd/dosaf": "Estimate site allele frequencies from BAM files.", "regtools/junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.", "tabix/tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,"}}, "target": "angsd/gl", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral genome sequencing on Oxford Nanopore MinION / GridION. Input files: Demultiplexed single-end long reads from tiled viral amplicons.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_rsem_calculateexpression_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate expression with RSEM (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tximeta_tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages", "custom_rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "rsem_calculateexpression": "Calculate expression with RSEM", "subread_featurecounts": "Count reads that map to genomic features", "vembrane_filter": "Filter VCF files with vembrane"}}, "target": "rsem_calculateexpression", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_8_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_31", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "field_constraint_fastq_1_0_7", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_25", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_singlecell_parse_splitseq_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Parse Biosciences Split-seq combinatorial barcoding)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Parse Biosciences Split-seq combinatorial barcoding with entry step FASTQC.", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_minimac4_impute_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Imputation of genotypes using a reference panel (tools: minimac4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba/visualisation": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "centrifuger/build": "Build centrifuger database for taxonomic profiling", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "minimac4/impute": "Imputation of genotypes using a reference panel"}}, "target": "minimac4/impute", "target_idx": 4}
{"id": "samplesheet_arch_pediatric_trio_somatic_5_4", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents).", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_stare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Framework that scores enhancer–gene interactions using the Activity-By-Contact model and derives transcription factor affinities on gene level (tools: stare)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genin2": "Genin2 is a lightining-fast bioinformatic tool to predict genotypes for H5 viruses belonging to the European c", "parabricks_mutectcaller": "NVIDIA Clara Parabricks GPU-accelerated somatic variant calling, replicating GATK Mutect2.", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "stare": "Framework that scores enhancer–gene interactions using the Activity-By-Contact model and derives transcription", "alignoth": "Creating alignment plots from bam files"}}, "target": "stare", "target_idx": 3}
{"id": "mod_gatk4_estimatelibrarycomplexity_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimates the numbers of unique molecules in a sequencing library. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proovframe_map": "frame-shift correction for long read (meta)genomics - maps proteins to reads", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "busco_plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "gatk4_estimatelibrarycomplexity": "Estimates the numbers of unique molecules in a sequencing library."}}, "target": "gatk4_estimatelibrarycomplexity", "target_idx": 4}
{"id": "samplesheet_arch_faire_seq_chromatin_2_4", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bed": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_gatk_indelrealigner_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs local realignment around indels to correct for mapping errors (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk/indelrealigner": "Performs local realignment around indels to correct for mapping errors", "eagle2": "Perform phasing of genotyped data with or without a reference panel", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "jvarkit/sam2tsv": "Convert sam files to tsv files"}}, "target": "gatk/indelrealigner", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_6_5", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment input samplesheet?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_oncoanalyser_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay": "oncoanalyser pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/oncoanalyser (A comprehensive cancer DNA/RNA analysis and reporting pipeli)?", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,fastq_1,fastq_2,replicate,antibody": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,fastq_2,batch,condition": null}}, "target": "sample_id,group_id,subject_id,sample_type,sequence_type", "target_idx": 0}
{"id": "field_constraint_phenotype_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"enum: [normal, tumor]": null, "format: file-path": null, "type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_49", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_fastq_fastqc_umitools_fastp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read QC, UMI extraction and trimming (tools: fastq_fastqc_umitools_fastp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats", "fastq_fastqc_umitools_fastp": "Read QC, UMI extraction and trimming", "shovill": "Assemble bacterial isolate genomes from Illumina paired-end reads", "ariba_run": "Query input FASTQs against Ariba formatted databases", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon"}}, "target": "fastq_fastqc_umitools_fastp", "target_idx": 1}
{"id": "noul_channel_collect_operator_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_odgi_squeeze_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Squeezes multiple graphs in ODGI format into the same file in ODGI format. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/sana": "Sanitize broken single line FASTQ files", "odgi/squeeze": "Squeezes multiple graphs in ODGI format into the same file in ODGI format.", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format", "odgi/build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1.", "gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA"}}, "target": "odgi/squeeze", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wes_pe_3_1", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Whole Exome Sequencing (WES) target capture with entry step FASTQC.", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_shinyngs_staticexploratory_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots (tools: shinyngs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seroba/run": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "transdecoder/predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "blobtk/plot": "Creates differing styles of blobplots depending on provided arguments.", "shinyngs/staticexploratory": "Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots", "deeptools/plotheatmap": "plots values produced by deeptools_computematrix as a heatmap"}}, "target": "shinyngs/staticexploratory", "target_idx": 3}
{"id": "resource_amulety_translate_1", "category": "resource_profiling", "state": {"process": "AMULETY_TRANSLATE", "tool": "amulety/translate", "description": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_TRANSLATE (A module to translate BCR and TCR nucleotide sequences into amino acid sequences) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bacphlip_1", "category": "resource_profiling", "state": {"process": "BACPHLIP", "tool": "bacphlip", "description": "A bacteriophage lifestyle prediction tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACPHLIP (A bacteriophage lifestyle prediction tool) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_0_4", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "INPUT_CHECK", "library_inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_oncoanalyser_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/oncoanalyser. Description: A comprehensive cancer DNA/RNA analysis and reporting pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/oncoanalyser.", "criteria": {"sample,group,path,ref,method": null, "sample,bam,bai": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "sample_id,group_id,subject_id,sample_type,sequence_type", "target_idx": 3}
{"id": "schema_std_pathogensurveillance_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pathogensurveillance. Description: Surveillance of pathogens using population genomics and sequencing.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pathogensurveillance.", "criteria": {"id,fasta": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample_id,name,description,path,path_2": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null}}, "target": "sample_id,name,description,path,path_2", "target_idx": 2}
{"id": "pipe_all101_hic_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Analysis of Chromosome Conformation Capture data (Hi-C). Topics: chromosome-conformation-capture, hi-c. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phyloplace": null, "imcyto": null, "drop": null, "methylong": null, "scrnaseq": null, "genomeqc": null, "cageseq": null, "hic": null}}, "target": "hic", "target_idx": 7}
{"id": "mod_igvreports_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A Python application to generate self-contained HTML reports for variant review and other genomic applications (tools: igvreports)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_call": null, "svaba": null, "glnexus": null, "bcftools_call": null, "igvreports": null}}, "target": "igvreports", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_1_15", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_bcl_demultiplex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Illumina BCL data using bcl-convert or bcl2fastq (tools: bcl_demultiplex)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd/contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome.", "samplesheetparser/info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "bcl_demultiplex": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq", "cellrangerarc/mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma", "hicap": "Identify cap locus serotype and structure in your Haemophilus influenzae assemblies"}}, "target": "bcl_demultiplex", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_30", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bcftools_pluginimputeinfo_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINIMPUTEINFO", "tool": "bcftools/pluginimputeinfo", "description": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINIMPUTEINFO (Adds imputation information metrics to the INFO field based on selected FORMAT t) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_bcftools_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily lost in the process of transition under htslib, but will be added back on popular demand.\nThe original calling model can be invoked with the -c option. (tools: view)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bcftools/filter": "Filters VCF files", "foldcomp/compress": "Efficient compression tool for protein structures", "bcftools/consensus": "Compresses VCF files", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "bcftools/call", "target_idx": 0}
{"id": "mod_virusrecom_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Information-theory-based method for recombination detection of viral lineages using weighted information content (WIC). (tools: virusrecom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lofreq_somatic": null, "virusrecom": null, "cobrameta": null, "pasty": null, "clonalframeml": null}}, "target": "virusrecom", "target_idx": 1}
{"id": "mod_homer_annotatepeaks_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate peaks with HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer/makeucscfile": "Create a UCSC bed graph with the HOMER suite", "homer/maketagdirectory": "Create a tag directory with the HOMER suite", "custom/tabulartogseachip": "Make a GSEA class file (.chip) from tabular inputs", "homer/annotatepeaks": "Annotate peaks with HOMER suite", "svim/alignment": "Structural variant detection from long-read sequencing alignments using SVIM."}}, "target": "homer/annotatepeaks", "target_idx": 3}
{"id": "mod_plink_indeppairwise_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of variants in the current window with squared correlation greater than the threshold are noted and variants are greedily pruned from the window until no such pairs remain. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp_extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "plink_extract": "Subset plink bfiles with a text file of variant identifiers", "plink_indeppairwise": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of varia", "gatk4_calculatecontamination": "Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummari", "plink_genome": "Calculates identity-by-descent over autosomal SNPs"}}, "target": "plink_indeppairwise", "target_idx": 2}
{"id": "resource_bcftools_rohviz_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROHVIZ", "tool": "bcftools/rohviz", "description": "Visualise the output of bcftools roh"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROHVIZ (Visualise the output of bcftools roh) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_methylong_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Extract methylation calls from long reads (ONT/ PacBio). Topics: dna-methylation, fiber-seq, long-read, ont, pacbio. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]"}}, "target": "methylong", "target_idx": 1}
{"id": "noul_channel_operator_map_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "core_tool_minimap2_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Long-read mapping of Oxford Nanopore and PacBio HiFi sequencing reads against human and microbial reference assemblies.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bwa_mem": null, "bowtie2": null, "minimap2": null, "subread": null, "star": null}}, "target": "minimap2", "target_idx": 2}
{"id": "resource_authentict_deam2cont_2", "category": "resource_profiling", "state": {"process": "AUTHENTICT_DEAM2CONT", "tool": "authentict/deam2cont", "description": "Use deamination patterns to estimate contamination in single-stranded libraries"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTHENTICT_DEAM2CONT (Use deamination patterns to estimate contamination in single-stranded libraries) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_mobster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subclonal deconvolution of cancer genome sequencing data. (tools: mobster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/dbsnp": "NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database", "viber": "Multisample subclonal deconvolution of cancer genome sequencing data.", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "metamaps/classify": "Strain-level metagenomic assignment", "mobster": "Subclonal deconvolution of cancer genome sequencing data."}}, "target": "mobster", "target_idx": 4}
{"id": "mod_hisat3n_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align nucleotide conversion sequencing reads (e.g., bisulfite-seq, SLAM-seq) to a reference genome with HISAT-3N (tools: hisat-3n)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_align": null, "stardist": null, "ampcombi": null, "hisat3n_align": null, "concoct_concoctcoveragetable": null}}, "target": "hisat3n_align", "target_idx": 3}
{"id": "mod_parabricks_applybqsr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR). (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi_viz": "Visualize a variation graph in 1D.", "parabricks_applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "gatk4_gatherbqsrreports": "Gathers scattered BQSR recalibration reports into a single file", "sylphtax_taxprof": "Incorporates taxonomy into sylph metagenomic classifier", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)"}}, "target": "parabricks_applybqsr", "target_idx": 1}
{"id": "mod_scanpy_hashsolo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Probabilistic demultiplexing of cell hashing data (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy_hashsolo": "Probabilistic demultiplexing of cell hashing data", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "kmcp_profile": "Generate taxonomic profile from search results", "bedtools_subtract": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining po"}}, "target": "scanpy_hashsolo", "target_idx": 0}
{"id": "mod_cellrangeratac_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC. (tools: cellranger-atac)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_recode": "Recodes plink bfiles into a new text fileset applying different modifiers", "icountmini_segment": "Formats a GTF file for use with iCount sigxls", "cellrangeratac_count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}}, "target": "cellrangeratac_count", "target_idx": 2}
{"id": "mod_ltrfinder_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Finds full-length LTR retrotranspsons in genome sequences using the\nparallel version of LTR_Finder (tools: LTR_FINDER_parallel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "ltrfinder": "Finds full-length LTR retrotranspsons in genome sequences using the\nparallel version of LTR_Finder", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "ribocode/gtfupdate": "Update GTF annotation file for RiboCode compatibility"}}, "target": "ltrfinder", "target_idx": 2}
{"id": "mod_manta_convertinversion_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. This script reformats inversions into single inverted sequence junctions which was the format used in Manta versions <= 1.4.0. (tools: manta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/filterintervals": "Filters intervals based on annotations and/or count statistics.", "dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "manta/convertinversion": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. This script reformat", "homer/makeucscfile": "Create a UCSC bed graph with the HOMER suite"}}, "target": "manta/convertinversion", "target_idx": 3}
{"id": "samplesheet_arch_pediatric_trio_somatic_3_0", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) with entry step FASTQC.", "criteria": {"sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_fastq_align_bwaaln_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed BAM files (tools: fastq_align_bwaaln)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xengsort/index": "Fast lightweight accurate xenograft sorting", "bwamem2/mem": "Performs fastq alignment to a fasta reference using BWA", "fastq_align_bwaaln": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed ", "bwa/aln": "Find SA coordinates of the input reads for bwa short-read mapping", "catpack/download": "Downloads the required files for either Nr or GTDB for building into a CAT database"}}, "target": "fastq_align_bwaaln", "target_idx": 2}
{"id": "noul_executor_support_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_rnasplice_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis. Topics: alternative-splicing, rna, rna-seq, splicing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phaseimpute": null, "spatialaxe": null, "marsseq": null, "molkart": null, "fetchngs": null, "hgtseq": null, "scrnaseq": null, "dualrnaseq": null, "rnasplice": null, "longraredisease": null}}, "target": "rnasplice", "target_idx": 8}
{"id": "mod_cellranger_mkref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkref command. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kmergenie": "KmerGenie estimates the best k-mer length for genome de novo assembly", "cellranger/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkref command.", "bbmap/bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "repeatmasker/rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}}, "target": "cellranger/mkref", "target_idx": 1}
{"id": "mod_foldmason_easymsa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns protein structures using foldmason (tools: foldmason)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco/phylogenomics": null, "amps": null, "affy/justrma": null, "deepmased/predict": null, "foldmason/easymsa": null}}, "target": "foldmason/easymsa", "target_idx": 4}
{"id": "noul_default_empty_channel_behavior_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_wgsim_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: simulating sequence reads from a reference genome (tools: wgsim)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "perbase": "Per-base metrics on BAM/CRAM files.", "wgsim": "simulating sequence reads from a reference genome", "fastq_qc_stats": "Generate statistics for short read sequencing data using multiple tools", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}}, "target": "wgsim", "target_idx": 2}
{"id": "resource_bedtools_maskfasta_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MASKFASTA", "tool": "bedtools/maskfasta", "description": "masks sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MASKFASTA (masks sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_telescope_assign_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The telescope assign program finds overlapping reads between an alignment (SAM/BAM) and an annotation (GTF) then reassigns reads using a statistical model. (tools: telescope)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/learnreadorientationmodel": "Uses f1r2 counts collected during mutect2 to Learn the prior probability of read orientation artifacts", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "telescope/assign": "The telescope assign program finds overlapping reads between an alignment (SAM/BAM) and an annotation (GTF) th", "cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "proseg/proseg": "Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics."}}, "target": "telescope/assign", "target_idx": 2}
{"id": "mod_sentieon_gvcftyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform joint genotyping on one or more samples pre-called with Sentieon's Haplotyper. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_collectalignmentsummarymetrics": "Collect metrics about the alignment summary of a paired-end library.", "gatk4_genotypegvcfs": "Perform joint genotyping on one or more samples pre-called with HaplotypeCaller.", "infernal_cmsearch": "Search covariance models against a sequence database", "sentieon_gvcftyper": "Perform joint genotyping on one or more samples pre-called with Sentieon's Haplotyper.", "bcftools_pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c"}}, "target": "sentieon_gvcftyper", "target_idx": 3}
{"id": "resource_bcftools_stats_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_STATS", "tool": "bcftools/stats", "description": "Generates stats from VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_STATS (Generates stats from VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_pacvar_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "description": "Longread PacBio sequencing processing for WGS and PureTarget", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pacvar?", "criteria": {"sample,bam,pbi,fail,repeat_id": null, "sample,fastq_1,fastq_2,bam,cram": null, "sample,fastq_1,fastq_2": null, "sample,sample_id,fastq_1,fastq_2,method": null}}, "target": "sample,bam,pbi,fail,repeat_id", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_49", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bismark_methylationextractor_3", "category": "resource_profiling", "state": {"process": "BISMARK_METHYLATIONEXTRACTOR", "tool": "bismark/methylationextractor", "description": "Extracts methylation information for individual cytosines from alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_METHYLATIONEXTRACTOR (Extracts methylation information for individual cytosines from alignments.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_35", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_misopy_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build an indexed representation of a GFF for efficient retrieval of genes (tools: misopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "misopy/index": "Build an indexed representation of a GFF for efficient retrieval of genes", "sentieon/tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.", "bowtie/build": "Create bowtie index for reference genome", "gatk4/splitintervals": "Split intervals into sub-interval files."}}, "target": "misopy/index", "target_idx": 1}
{"id": "intent_build_pipeline_7", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "ask_question": null, "prepare_data": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_gatk4_svcluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clusters structural variants based on coordinates, event type, and supporting algorithms (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"icountmini_segment": "Formats a GTF file for use with iCount sigxls", "sexdeterrmine": "Calculate the relative coverage on the Gonosomes vs Autosomes from the output of samtools depth, with error ba", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "gatk4_svcluster": "Clusters structural variants based on coordinates, event type, and supporting algorithms", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content"}}, "target": "gatk4_svcluster", "target_idx": 3}
{"id": "pipe_all101_hgtseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline to investigate horizontal gene transfer from NGS data. Topics: bwa-mem, bwa-mem2, fastqc, genomics-visualization, ggbio, horizontal-gene-transfer. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "hgtseq", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_0_38", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_summarizedexperiment_summarizedexperiment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SummarizedExperiment container (tools: summarizedexperiment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani_sketch": "Storing skani sketches/indices on disk.", "summarizedexperiment_summarizedexperiment": "SummarizedExperiment container", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics.", "pydamage_filter": "Damage parameter estimation for ancient DNA"}}, "target": "summarizedexperiment_summarizedexperiment", "target_idx": 1}
{"id": "schema_std_mhcquant_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mhcquant", "assay": "mhcquant pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/mhcquant (Identify and quantify MHC eluted peptides from mass spectrom)?", "criteria": {"sample,sample_id,fastq_1,fastq_2,method": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,seq_data,pbi,start_from": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "ID,Sample,Condition,ReplicateFileName,Fasta", "target_idx": 3}
{"id": "mod_mgikit_demultiplex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex MGI fastq files (tools: mgikit demultiplex)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bclconvert": "Demultiplex Illumina BCL files", "deeptools/alignmentsieve": "This tool filters alignments in a BAM/CRAM file according the the specified parameters.", "rseqc/readdistribution": "Calculate how mapped reads are distributed over genomic features", "bases2fastq": "Demultiplex Element Biosciences bases files", "mgikit/demultiplex": "Demultiplex MGI fastq files"}}, "target": "mgikit/demultiplex", "target_idx": 4}
{"id": "samplesheet_arch_ont_direct_rna_se_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Single-end Oxford Nanopore direct RNA", "data_format": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,fast5": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_atlas_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: generate VCF file from a BAM file using various calling methods (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/recal": "Gives an estimation of the sequencing bias based on known invariant sites", "simpleaf/quant": "simpleaf is a program to simplify and customize the running and configuration of single-cell processing with a", "samtools/samples": "Write sample names and path to reference genome of an alignment to a text file.", "atlas/call": "generate VCF file from a BAM file using various calling methods", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "atlas/call", "target_idx": 3}
{"id": "mod_plink2_indeppairwise_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produce pruned set of variants in approximatelinkage equilibrium (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium", "nonpareil_set": "Visualise metagenome redundancy curves in PNG format from multiple Nonpareil npo files in a single image", "plink2_filter": "Filters plink bfiles or pfiles with filters such as maf or var", "opt_track": "track aligns query probe sequences to any target transcriptome", "plink2_extract": "Subset plink pfiles with a text file of variant identifiers"}}, "target": "plink2_indeppairwise", "target_idx": 0}
{"id": "core_tool_deepvariant_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Deep neural network-based variant caller transforming aligned reads into pileup tensor images for high-accuracy SNP/indel detection.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"gatk_haplotypecaller": "GATK caller", "freebayes": "Bayesian caller", "clair3": "Neural caller", "deepvariant": "Deep learning-based variant caller that calls genetic variants using neural networks", "varscan2": "Variant caller"}}, "target": "deepvariant", "target_idx": 3}
{"id": "mod_amulety_embed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety/esm2": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety.", "mafft_align": "Multiple sequence alignment using MAFFT", "amulety/embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "clonalframeml": "Predict recomination events in bacterial genomes", "custom/pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi"}}, "target": "amulety/embed", "target_idx": 2}
{"id": "resource_bam2fastx_bam2fastq_5", "category": "resource_profiling", "state": {"process": "BAM2FASTX_BAM2FASTQ", "tool": "bam2fastx/bam2fastq", "description": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAM2FASTX_BAM2FASTQ (Conversion of PacBio BAM files into gzipped fastq files, including splitting of ) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_0_2", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Small RNA / miRNA sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_default_empty_channel_behavior_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_nascent_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for gro-seq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "metapep": "From metagenomes to epitopes and beyond", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]"}}, "target": "nascent", "target_idx": 4}
{"id": "subworkflow_pkg_bam_variant_calling_mpileup_bcftools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS", "modules": ["gawk", "tabix/bgzip", "bcftools/mpileup", "bcftools/merge", "bcftools/annotate", "bcftools/concat", "vcf_gather_bcftools"], "description": "Subworkflow to compute genotype likelihoods from BAM files using"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS (gawk, tabix/bgzip, bcftools/mpileup, bcftools/merge, bcftools/annotate, bcftools/concat, vcf_gather_bcftools) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow bam_variant_calling_mpileup_bcftools": null, "Local subworkflow BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_variant_calling_mpileup_bcftools", "target_idx": 1}
{"id": "mod_samblaster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This module combines samtools and samblaster in order to use\nsamblaster capability to filter or tag SAM files, with the advantage\nof maintaining both input and output in BAM format.\nSamblaster input must contain a sequence header: for this reason it has been piped\nwith the \"samtools view -h\" command.\nAdditional desired arguments for samtools can be passed using:\noptions.args2 for the input bam file\noptions.args3 for the output bam file (tools: samblaster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/orfnormalise": null, "biobambam/bamsormadup": null, "samblaster": null, "deeptmhmm": null, "csvtk/sort": null}}, "target": "samblaster", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_3_2", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-lane Illumina sequencing run of clinical samples with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "local_subworkflow_preparereports_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should this step (custom/preparereports, multiqc) be packaged: Custom aggregation and MultiQC reporting?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow preparereports": null, "Local subworkflow PREPAREREPORTS": null, "Leave them out": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_1_5", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "resource_arriba_arriba_3", "category": "resource_profiling", "state": {"process": "ARRIBA_ARRIBA", "tool": "arriba/arriba", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_ARRIBA (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcftools_merge_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MERGE", "tool": "bcftools/merge", "description": "Merge VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MERGE (Merge VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Single-end Oxford Nanopore direct RNA)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Single-end Oxford Nanopore direct RNA.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fast5": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_retry_errorstrategy_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: 16S rRNA / ITS microbiome amplicon profiling)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: 16S rRNA / ITS microbiome amplicon profiling.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,primer_fwd,primer_rev": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_3_0", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Multiome single-cell joint RNA and ATAC chromatin with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_complexity_filter_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_COMPLEXITY_FILTER", "modules": ["prinseqplusplus", "bbmap/bbduk", "fastp"], "description": "Perform low-complexity filtering of FASTQ reads using a selectable tool."}, "question": {"type": "choice", "instructions": "How should FASTQ_COMPLEXITY_FILTER (prinseqplusplus, bbmap/bbduk, fastp) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_COMPLEXITY_FILTER": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_complexity_filter": null}}, "target": "Use nf-core subworkflow fastq_complexity_filter", "target_idx": 3}
{"id": "mod_agat_convertspgff2tsv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a GFF/GTF file into a TSV file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": null, "agat_convertspgff2tsv": null, "samtools_depth": null, "agat_convertspgff2gtf": null, "picard_collecthsmetrics": null}}, "target": "agat_convertspgff2tsv", "target_idx": 1}
{"id": "mod_bcftools_norm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalize VCF file (tools: norm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"taxpasta/merge": "Standardise and merge two or more taxonomic profiles into a single table", "bcftools/norm": "Normalize VCF file", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "pypgx/preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "atlas/call": "generate VCF file from a BAM file using various calling methods"}}, "target": "bcftools/norm", "target_idx": 1}
{"id": "mod_estsfs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: estimation of the unfolded site frequency spectrum (tools: estsfs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "estsfs": "estimation of the unfolded site frequency spectrum", "duckdb_table2parquet": "Convert a delimited text table (CSV or TSV, gzipped or not) to Parquet", "meryl_histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "bio2zarr_vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}}, "target": "estsfs", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_1_5", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "template": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_23", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_spatial_visium_2_0", "category": "samplesheet_schema", "state": {"technology": "Spatial Transcriptomics", "workflow_entry": "FASTQC", "library_inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_27", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_3_1", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pre-aligned BAM variant calling pipeline with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "mod_leviosam2_lift_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converting aligned short and long reads records from one reference to another (tools: leviosam2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmod_models": "annotate models of inheritance", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "biscuit_index": "Indexes a reference genome for use with Biscuit", "samtools_fixmate": "Samtools fixmate is a tool that can fill in information (insert size, cigar, mapq) about paired end reads onto", "leviosam2_lift": "Converting aligned short and long reads records from one reference to another"}}, "target": "leviosam2_lift", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_2_32", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_14", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_29", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_parsnp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection. (tools: parsnp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm_qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "parsnp": "Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection.", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "kleborate": "Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "parsnp", "target_idx": 1}
{"id": "noul_deprecated_file_output_syntax_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_atlasgeneannotationmanipulation_gtf2featureannotation_2", "category": "resource_profiling", "state": {"process": "ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION", "tool": "atlasgeneannotationmanipulation/gtf2featureannotation", "description": "Generate tables of feature metadata from GTF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION (Generate tables of feature metadata from GTF files) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bamtools_split_2", "category": "resource_profiling", "state": {"process": "BAMTOOLS_SPLIT", "tool": "bamtools/split", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_SPLIT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_anndata_barcodes_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to subset AnnData object to cells with matching barcodes from the csv file (tools: anndata)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "mlst": "Run Torsten Seemann's classic MLST on a genome assembly", "s4pred_runmodel": "Prediction of a protein's secondary structure from its amino acid sequence", "bff": "Generating cell hashing calls from a matrix of count data.", "cellbender_removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data"}}, "target": "anndata_barcodes", "target_idx": 0}
{"id": "subworkflow_pkg_quantify_pseudo_alignment_3", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_PSEUDO_ALIGNMENT", "modules": ["kallisto/quant", "quant_tximport_summarizedexperiment", "salmon/quant"], "description": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_PSEUDO_ALIGNMENT (kallisto/quant, quant_tximport_summarizedexperiment, salmon/quant) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow QUANTIFY_PSEUDO_ALIGNMENT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow quantify_pseudo_alignment": null}}, "target": "Use nf-core subworkflow quantify_pseudo_alignment", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_31", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_2_30", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_all101_detaxizer_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for de-identification. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "callingcards": "A pipeline for processing calling cards data", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d"}}, "target": "detaxizer", "target_idx": 1}
{"id": "pipe_all101_bacass_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Simple bacterial assembly and annotation pipeline. Topics: assembly, bacterial-genomes, denovo, denovo-assembly, genome-assembly, hybrid-assembly. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": null, "genomeassembler": null, "viralintegration": null, "pixelator": null, "sarek": null, "scrnaseq": null, "bacass": null, "circdna": null}}, "target": "bacass", "target_idx": 6}
{"id": "qc_adapt_illumina_novaseq_1_18", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_skani_triangle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: All-to-all ANI computation. (tools: skani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"calder2": null, "argnorm": null, "skani_triangle": null, "amps": null, "dssp_mkdssp": null}}, "target": "skani_triangle", "target_idx": 2}
{"id": "resource_bio2zarr_vcfpartition_3", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCFPARTITION", "tool": "bio2zarr/vcfpartition", "description": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCFPARTITION (Outputs a set of region strings that partition indexed VCF/BCF files for paralle) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_biobambam_bammarkduplicates2_2", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMARKDUPLICATES2", "tool": "biobambam/bammarkduplicates2", "description": "Locate and tag duplicate reads in a BAM file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMARKDUPLICATES2 (Locate and tag duplicate reads in a BAM file) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_5_3", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/taxprofiler, determine the input samplesheet column structure for: Multi-taxonomic profiling of complex metagenomic shotgun reads.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,kraken_db": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_popscle_freemuxlet_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing and external genotyping data for each sample is not available. (tools: popscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vardictjava": "The Java port of the VarDict variant caller", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "bff": "Generating cell hashing calls from a matrix of count data.", "hasheddrops": "Generating cell hashing calls from a matrix of count data.", "popscle/freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s"}}, "target": "popscle/freemuxlet", "target_idx": 4}
{"id": "mod_plink_ld_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LD analysis in PLINK examines genetic variant associations within populations (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"humann3/renorm": "Normalizing RPKs to relative abundance", "mafft_align": "Multiple sequence alignment using MAFFT", "gcta/bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "gcta/addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "plink/ld": "LD analysis in PLINK examines genetic variant associations within populations"}}, "target": "plink/ld", "target_idx": 4}
{"id": "samplesheet_arch_epigenomics_hic_1_5", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "template": "nf-core/hic"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hi-C chromosome conformation capture mapping?", "criteria": {"sample,fastq_1": null, "sample,matrix,contacts": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_channel_join_operator_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_1_5", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,bed": null, "sample,vcf,tbi": null}}, "target": "sample,vcf,tbi", "target_idx": 3}
{"id": "mod_cellbender_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use CellBender to remove ambient RNA from single-cell RNA-seq data (tools: cellbender)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bff": "Generating cell hashing calls from a matrix of count data.", "clair3": "Clair3 is a germline small variant caller for long-reads", "cellbender/merge": "Module to use CellBender to remove ambient RNA from single-cell RNA-seq data", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "bcftools/csq": "bcftools Haplotype-aware consequence caller"}}, "target": "cellbender/merge", "target_idx": 2}
{"id": "resource_agrvate_1", "category": "resource_profiling", "state": {"process": "AGRVATE", "tool": "agrvate", "description": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGRVATE (Rapid identification of Staphylococcus aureus agr locus type and agr operon vari) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_4_4", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads with library strandedness?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "schema_std_hadge_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hadge", "assay": "hadge pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/hadge (Comprehensive pipeline for donor demultiplexing in single ce)?", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,seed": null, "sample,fastq_1,fastq_2,bam,seq_type": null}}, "target": "sample,bam,vcf,rna_matrix,hto_matrix", "target_idx": 1}
{"id": "mod_percolator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rescore peptide-spectrum matches and estimate false discovery rates using the Percolator semi-supervised learning algorithm. (tools: percolator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_rmdup": null, "gatk4_printsvevidence": null, "diamond_cluster": null, "percolator": null, "diamond_deepclust": null}}, "target": "percolator", "target_idx": 3}
{"id": "schema_std_fastquorum_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/fastquorum", "description": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/fastquorum?", "criteria": {"ID,R1,R2,LongFastQ,Fast5": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,fastq_1,fastq_2,library_id,lane": null, "sample,bam,vcf,rna_matrix,hto_matrix": null}}, "target": "sample,fastq_1,fastq_2,library_id,lane", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_8", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_portcullis_full_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run all Portcullis steps in one go (tools: portcullis)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser_validate": "Validate an Illumina SampleSheet.csv (V1 or V2) for index, adapter, and\nstructural issues. Format is auto-dete", "vembrane_sort": "Sort VCF/BCF files by custom Python expressions for variant prioritization", "ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "portcullis_full": "Run all Portcullis steps in one go", "ctatsplicing_prepgenomelib": "Reference preparation for CTAT-splicing"}}, "target": "portcullis_full", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_24", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_methylseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair. Topics: bisulfite-sequencing, dna-methylation, em-seq, epigenome, epigenomics, methyl-seq. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "seqsubmit": "nf-core pipeline for data submission to ENA", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "methylseq", "target_idx": 1}
{"id": "mod_fastq_complexity_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform low-complexity filtering of FASTQ reads using a selectable tool.\nOne of PRINSEQ++, BBDuk, or fastp is executed based on the provided tool name.\nOnly complexity filtering is applied; no adapter trimming, read merging, or\nquality trimming is performed. (tools: fastq_complexity_filter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_complexity_filter": "Perform low-complexity filtering of FASTQ reads using a selectable tool.\nOne of PRINSEQ++, BBDuk, or fastp is ", "pmdtools/filter": "pmdtools command to filter ancient DNA molecules from others", "braker3": "Gene prediction in novel genomes using RNA-seq and protein homology information", "ariba/getref": "Download and prepare database for Ariba analysis", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads"}}, "target": "fastq_complexity_filter", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_3_1", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) with entry step FASTQC.", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_agat_spflagshortintrons_0", "category": "resource_profiling", "state": {"process": "AGAT_SPFLAGSHORTINTRONS", "tool": "agat/spflagshortintrons", "description": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting the data to EBI.\n(Typical EBI error message: ********ERROR: Intron usually expected to be at least 10 nt long. Please check the accuracy)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFLAGSHORTINTRONS (The script flags the short introns with the attribute <pseudo>. Is is usefull to) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_scimap_mcmicro_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SCIMAP is a suite of tools that enables spatial single-cell analyses (tools: scimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scimap/mcmicro": null, "bedtools/slop": null, "biobambam/bamsormadup": null, "plastid/makewiggle": null, "crisprcleanr/normalize": null}}, "target": "scimap/mcmicro", "target_idx": 0}
{"id": "mod_gapseq_requestdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download gapseq reference sequence database for metabolic pathway prediction (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq/requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "interproscan": "Produces protein annotations and predictions from an amino acids FASTA file", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo", "plink/vcf": "Analyses variant calling files using plink"}}, "target": "gapseq/requestdb", "target_idx": 0}
{"id": "mod_humann3_renorm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalizing RPKs to relative abundance (tools: humann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"humann3/renorm": "Normalizing RPKs to relative abundance", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "force/tileextent": "Compute valid tiles for a given datacube definition and area of interest.\nThis list can be used by downstream ", "humann3/humann": "Functional analysis of metagenome or metatranscriptome data"}}, "target": "humann3/renorm", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_medaka_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to create consensus sequences and variant calls from nanopore sequencing data (tools: medaka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylph_sketch": "Sketching/indexing sequencing reads", "msisensor_scan": "Scan a reference genome to get microsatellite & homopolymer information", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "abacas": "Contiguate draft genome assembly", "medaka": "A tool to create consensus sequences and variant calls from nanopore sequencing data"}}, "target": "medaka", "target_idx": 4}
{"id": "mod_optitype_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform HLA-I typing of sequencing data (tools: optitype)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sortmerna": "Local sequence alignment tool for filtering, mapping and clustering.", "optitype": "Perform HLA-I typing of sequencing data", "rpbp/selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ", "fastq_qc_trim_filter_setstrandedness": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files,", "splitubam": "split one ubam into multiple, per line, fast"}}, "target": "optitype", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_46", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_snpeff_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "ensemblvep/vep", "snpeff/download", "snpeff/snpeff", "htslib/bgziptabix", "bcftools/pluginscatter", "bcftools/concat", "bcftools/sort"], "description": "Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkflow uses the scatter-gather method to run VEP/snpEff in parallel to increase throughput. The input VCF is split into multiple smaller VCFs of fixed size, which are annotated separately and concatenated back together to a single output file per sample. Only VCF/BCF outputs are currently supported."}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP_SNPEFF (ensemblvep/download, ensemblvep/vep, snpeff/download, snpeff/snpeff, htslib/bgziptabix, bcftools/pluginscatter, bcftools/concat, bcftools/sort) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow VCF_ANNOTATE_ENSEMBLVEP_SNPEFF": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_1_3", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/eager) for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment. Input files: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_abritamr_run_1", "category": "resource_profiling", "state": {"process": "ABRITAMR_RUN", "tool": "abritamr/run", "description": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRITAMR_RUN (A NATA accredited tool for reporting the presence of antimicrobial resistance ge) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_mmseqs_taxonomy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the lowest common ancestor by identifying the query sequence homologs against the target database. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xz/compress": null, "mmseqs/cluster": null, "mmseqs/createtaxdb": null, "mmseqs/taxonomy": null, "myloasm": null}}, "target": "mmseqs/taxonomy", "target_idx": 3}
{"id": "schema_std_hicar_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/hicar. Description: Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/hicar.", "criteria": {"sample,nuclear_image,spot_table,membrane_image": null, "sample,bam,pbi,fail,repeat_id": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "fastq_1,fastq_2,group,replicate,md5_1", "target_idx": 2}
{"id": "mod_miniprot_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides fasta index required by miniprot alignment. (tools: miniprot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"miniprot_index": "Provides fasta index required by miniprot alignment.", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "biscuit_index": "Indexes a reference genome for use with Biscuit", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs"}}, "target": "miniprot_index", "target_idx": 0}
{"id": "intent_debug_error_3", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "prepare_data": null, "debug_error": null}}, "target": "debug_error", "target_idx": 3}
{"id": "mod_orfm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A simple and not slow open reading frame (ORF) caller. The goal is to return a FASTA file of open reading frames over a certain length from a FASTA/Q file of nucleotide sequences. (tools: orfm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gedi_price": null, "muse_sump": null, "orfm": null, "gedi_indexgenome": null, "mashmap": null}}, "target": "orfm", "target_idx": 2}
{"id": "mod_agat_convertspgxf2gxf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "cooltools_insulation": "Calculate the diamond insulation scores and call insulating boundaries", "gatk4_intervallisttools": "Splits the interval list file into unique, equally-sized interval files and place it under a directory", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "agat_convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}}, "target": "agat_convertspgxf2gxf", "target_idx": 4}
{"id": "resource_biscuit_pileup_1", "category": "resource_profiling", "state": {"process": "BISCUIT_PILEUP", "tool": "biscuit/pileup", "description": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_PILEUP (Computes cytosine methylation and callable SNV mutations, optionally in referenc) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_fasta_gtf_bam_rpbp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). Ribo-seq sequences the short mRNA\nfootprints protected by translating ribosomes; Rp-Bp uses a Bayesian model\nto score which open reading frames (ORFs) on the transcriptome show the\ncharacteristic 3-nucleotide periodicity of active translation.\n\nGiven a genome FASTA, annotation GTF and one or more pre-aligned Ribo-seq\nBAMs, the subworkflow:\n  1. Builds the per-ORF reference (rpbp/preparegenome) once per run -\n     enumerates candidate ORFs from the GTF.\n  2. For each sample, builds per-read-length metagene profiles around\n     annotated start codons (extract-metagene-profiles), scores their\n     three-nucleotide periodicity with Bayesian models\n     (estimate-metagene-profile-bayes-factors), picks the best P-site\n     offset per periodic read length (select-periodic-offsets), and\n     filters down to the high-confidence read-length/offset pairs that\n     will drive ORF-level scoring (get-periodic-lengths-offsets).\n  3. Builds per-ORF P-site count vectors with those selected offsets\n     (extract-orf-profiles), scores each ORF as \"translated\" vs\n     \"untranslated\" with a Bayesian model (estimate-orf-bayes-factors),\n     and emits the final filtered set of predicted translated ORFs as\n     BED + DNA FASTA + protein FASTA (select-final-prediction-set).\n\nEach Rp-Bp step is a separate Nextflow process so `-resume` only re-runs\nwhat changed, and STAR/bowtie alignment is supplied via the BAM input\n(this subworkflow does not realign). (tools: fasta_gtf_bam_rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bakta_bakta": "Annotation of bacterial genomes (isolates, MAGs) and plasmids", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "nail_search": "nail search is a fast and scalable tool for searching protein sequences against protein databases", "fasta_gtf_bam_rpbp": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). R", "rpbp_extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR"}}, "target": "fasta_gtf_bam_rpbp", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_16", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for 10x Multiome single-cell joint RNA and ATAC chromatin. Input files: Paired FASTQs for both GEX and ATAC modalities per nucleus.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: 10x Multiome single-cell joint RNA and ATAC chromatin.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,matrix": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "mod_whatshap_haplotag_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tag reads by haplotype (tools: whatshap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/vcf": null, "links": null, "bio2zarr/vcfpartition": null, "whatshap/haplotag": null, "glimpse/sample": null}}, "target": "whatshap/haplotag", "target_idx": 3}
{"id": "mod_parabricks_genotypegvcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/convert": "Converts certain output formats to VCF", "parabricks/genotypegvcf": "NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs", "gatk4/genotypegvcfs": "Perform joint genotyping on one or more samples pre-called with HaplotypeCaller.", "deepmased/predict": "DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED", "mmseqs_fasta_cluster": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file."}}, "target": "parabricks/genotypegvcf", "target_idx": 1}
{"id": "pipe_all101_molkart_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). Topics: fish, image-processing, imaging, molecularcartography, segmentation, single-cell. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": "Read-based functional profiling of microbiome sequencing data", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]"}}, "target": "molkart", "target_idx": 1}
{"id": "mod_bcl_demultiplex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Illumina BCL data using bcl-convert or bcl2fastq (tools: bcl_demultiplex)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma", "bedtools_intersect": "Allows one to screen for overlaps between two sets of genomic features.", "bcl_demultiplex": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq", "samplesheetparser_validate": "Validate an Illumina SampleSheet.csv (V1 or V2) for index, adapter, and\nstructural issues. Format is auto-dete", "utils_nfcore_pipeline": "Subworkflow with utility functions specific to the nf-core pipeline template"}}, "target": "bcl_demultiplex", "target_idx": 2}
{"id": "mod_samtools_fastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a SAM/BAM/CRAM file to FASTQ (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/fastq": "Converts a SAM/BAM/CRAM file to FASTQ", "bamclipper": "This module is used to clip primer sequences from your alignments.", "strobealign": "Align short reads using dynamic seed size with strobemers", "parabricks/dbsnp": "NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "samtools/fastq", "target_idx": 0}
{"id": "intent_build_pipeline_17", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "build_pipeline": null, "prepare_data": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_41", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_vcf_annotate_ensemblvep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file (tools: vcf_annotate_ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "narfmap/hashtable": "Create DRAGEN hashtable for reference genome", "vcf_annotate_ensemblvep": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "salmon/quant": "gene/transcript quantification with Salmon"}}, "target": "vcf_annotate_ensemblvep", "target_idx": 2}
{"id": "mod_concoct_concoct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage data for multiple samples (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dastool/dastool": "DAS Tool binning step.", "oncocnv": "Calls CNVs in bam files from tumor patients", "gatk4/preprocessintervals": "Prepares bins for coverage collection.", "concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "concoct/extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT"}}, "target": "concoct/concoct", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_3", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_blobtk_snail_0", "category": "resource_profiling", "state": {"process": "BLOBTK_SNAIL", "tool": "blobtk/snail", "description": "Creates blobtk snail plots."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_SNAIL (Creates blobtk snail plots.) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_busco_phylogenomics_1", "category": "resource_profiling", "state": {"process": "BUSCO_PHYLOGENOMICS", "tool": "busco/phylogenomics", "description": "Construct species phylogenies using BUSCO proteins"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PHYLOGENOMICS (Construct species phylogenies using BUSCO proteins) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_fastq_2_1_14", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "mod_viennarna_rnacofold_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculate secondary structures of two RNAs with dimerization (tools: viennarna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastk/histex": "A fast K-mer counter for high-fidelity shotgun datasets", "viennarna/rnacofold": "calculate secondary structures of two RNAs with dimerization", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "glimpse2/chunk": "Defines chunks where to run imputation", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing"}}, "target": "viennarna/rnacofold", "target_idx": 1}
{"id": "local_subworkflow_irma_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should this step (irma) be packaged: Iterative assembly step for influenza and coronavirus?", "criteria": {"Local subworkflow IRMA": null, "Use nf-core subworkflow irma": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow IRMA", "target_idx": 0}
{"id": "resource_agat_sqstatbasic_5", "category": "resource_profiling", "state": {"process": "AGAT_SQSTATBASIC", "tool": "agat/sqstatbasic", "description": "Provides basic statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SQSTATBASIC (Provides basic statistics in text format from a GFF/GTF annotation file) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_varlociraptor_estimatealignmentproperties_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In order to judge about candidate indel and structural variants, Varlociraptor needs to know about certain properties of the underlying sequencing experiment in combination with the used read aligner. (tools: varlociraptor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "gatk4/concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "varlociraptor/estimatealignmentproperties": "In order to judge about candidate indel and structural variants, Varlociraptor needs to know about certain pro", "sentieon/readwriter": "Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality S", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "varlociraptor/estimatealignmentproperties", "target_idx": 2}
{"id": "mod_snpeff_snpeff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genetic variant annotation and functional effect prediction toolbox (tools: snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkref c", "chewbbaca/createschema": "Create a schema to determine the allelic profiles of a genome", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "snpeff/snpeff": "Genetic variant annotation and functional effect prediction toolbox", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "snpeff/snpeff", "target_idx": 3}
{"id": "samplesheet_arch_proteomics_dia_4_4", "category": "samplesheet_schema", "state": {"technology": "Mass Spectrometry", "workflow_entry": "INPUT_CHECK", "library_inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null, "sample,mzml": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "schema_std_sarek_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "description": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/sarek?", "criteria": {"sample,fastq_1,fastq_2,replicate,antibody": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "sample,fastq,cell_count": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 3}
{"id": "resource_amrfinderplus_run_0", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_RUN", "tool": "amrfinderplus/run", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_RUN (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_regenie_runl1_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Finish REGENIE step 1 from split level-0 prediction files (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_runl0": "Run one REGENIE step 1 level-0 job from a split master file", "gcta_fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "mcstaging_macsima2mc": "Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO.", "regenie_runl1": "Finish REGENIE step 1 from split level-0 prediction files", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3"}}, "target": "regenie_runl1", "target_idx": 3}
{"id": "mod_purgedups_purgedups_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Purge haplotigs and overlaps for an assembly (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "pharmcat_phenotyper": "The PharmCAT Phenotyper is a core module of the Pharmacogenomics Clinical Annotation Tool\nthat translates pati", "purgedups_purgedups": "Purge haplotigs and overlaps for an assembly", "narfmap_align": "Performs fastq alignment to a reference using NARFMAP", "purgedups_getseqs": "Separates out sequences purged of falsely duplicated sequences."}}, "target": "purgedups_purgedups", "target_idx": 2}
{"id": "subworkflow_pkg_bam_stats_samtools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STATS_SAMTOOLS", "modules": ["samtools/stats", "samtools/idxstats", "samtools/flagstat"], "description": "Produces comprehensive statistics from SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_STATS_SAMTOOLS (samtools/stats, samtools/idxstats, samtools/flagstat) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_stats_samtools": null, "Local subworkflow BAM_STATS_SAMTOOLS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_stats_samtools", "target_idx": 1}
{"id": "mod_gem3_gem3mapper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using using gem3-mapper (tools: gem3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "jellyfish_count": "Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm", "gem3_gem3mapper": "Performs fastq alignment to a fasta reference using using gem3-mapper", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference."}}, "target": "gem3_gem3mapper", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic cancer variant calling with tumor-normal pairs. Input files: Paired-end FASTQs for patient tumor and germline normal tissue.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_mhcquant_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for dda analysis? Specific context: Identify and quantify MHC eluted peptides from mass spectrometry raw data. Topics: dda, immunopeptidomics, mass-spectrometry, mhc, openms, peptides. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "mhcquant", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_1_31", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_bam_tumor_normal_somatic_variant_calling_gatk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode.\nf1r2 output of mutect2 is run through learnreadorientationmodel to get the artifact priors.\nRun the input bam files through getpileupsummarries and then calculatecontamination to get the contamination and segmentation tables.\nFilter the mutect2 output vcf using filtermutectcalls, artifact priors and the contamination & segmentation tables for additional filtering. (tools: bam_tumor_normal_somatic_variant_calling_gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "bam_tumor_normal_somatic_variant_calling_gatk": "Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode.\nf1r2 output o", "bwa/index": "Create BWA index for reference genome"}}, "target": "bam_tumor_normal_somatic_variant_calling_gatk", "target_idx": 3}
{"id": "field_constraint_status_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"format: file-path": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "mod_manta_convertinversion_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. This script reformats inversions into single inverted sequence junctions which was the format used in Manta versions <= 1.4.0. (tools: manta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"manta_convertinversion": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. This script reformat", "annotsv_installannotations": "Install the AnnotSV annotations", "mitohifi_findmitoreference": "Download a mitochondrial genome to be used as reference for MitoHiFi.\n\nNOTE: An optional NCBI API key can be s", "rpbp_preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont"}}, "target": "manta_convertinversion", "target_idx": 0}
{"id": "mod_hisat3n_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build HISAT-3N index for nucleotide conversion sequencing alignment (tools: hisat-3n)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hisat2/build": null, "cnvpytor/histogram": null, "hisat3n/build": null, "bowtie2/build": null, "estsfs": null}}, "target": "hisat3n/build", "target_idx": 2}
{"id": "mod_rseqc_readdistribution_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate how mapped reads are distributed over genomic features (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genometester4/glistmaker": "Create and count k-mer lists from nucelotide sequences.", "happy/sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic ", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "rseqc/readdistribution": "Calculate how mapped reads are distributed over genomic features", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "rseqc/readdistribution", "target_idx": 3}
{"id": "mod_cnvpytor_histogram_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculates read depth histograms (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"goat_taxonsearch": "Query metadata for any taxon across the tree of life.", "bedtools_coverage": "computes both the depth and breadth of coverage of features in file B on the features in file A", "cnvpytor_histogram": "calculates read depth histograms", "cnvpytor_partition": "Calculate segmentation for specified bin size (multiple bin sizes separate by space)", "limma_differential": "runs a differential expression analysis with Limma"}}, "target": "cnvpytor_histogram", "target_idx": 2}
{"id": "mod_cellrangeratac_mkref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkref command. (tools: cellranger-atac)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leviosam2_index": null, "cellrangeratac_mkref": null, "last_lastdb": null, "bowtie_build": null, "bowtie_align": null}}, "target": "cellrangeratac_mkref", "target_idx": 1}
{"id": "intent_build_pipeline_23", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "prepare_data": null, "build_pipeline": null}}, "target": "build_pipeline", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_bamcmp_bwa_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BAMCMP_BWA", "modules": ["bamcmp", "bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better to the first genome, then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BAMCMP_BWA (bamcmp, bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_BAMCMP_BWA": null, "Use nf-core subworkflow fastq_align_bamcmp_bwa": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_align_bamcmp_bwa", "target_idx": 1}
{"id": "resource_artic_minion_5", "category": "resource_profiling", "state": {"process": "ARTIC_MINION", "tool": "artic/minion", "description": "Run the alignment/variant-call/consensus logic of the artic pipeline"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_MINION (Run the alignment/variant-call/consensus logic of the artic pipeline) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_5_5", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "template": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/diaproteomics, determine the input samplesheet column structure for: Data-Independent Acquisition (DIA) quantitative mass spectrometry.", "criteria": {"sample,fasta": null, "sample,raw_file,condition": null, "sample,fastq_1,fastq_2": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "mod_fgumi_duplex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls duplex consensus sequences from reads generated from the same double-stranded\nsource molecule. This is a high-performance replacement for fgbio CallDuplexConsensusReads. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_tcs": "Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just", "fgbio_zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "fgumi_duplex": "Calls duplex consensus sequences from reads generated from the same double-stranded\nsource molecule. This is a", "rundbcan_easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ"}}, "target": "fgumi_duplex", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_24", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "subworkflow_pkg_archive_extract_2", "category": "subworkflow_packaging", "state": {"subworkflow": "ARCHIVE_EXTRACT", "modules": ["gunzip", "untar", "unzip"], "description": "Extract archive(s) from any format"}, "question": {"type": "choice", "instructions": "How should ARCHIVE_EXTRACT (gunzip, untar, unzip) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow ARCHIVE_EXTRACT": null, "Use nf-core subworkflow archive_extract": null}}, "target": "Use nf-core subworkflow archive_extract", "target_idx": 3}
{"id": "noul_subworkflow_structural_blocks_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay_type": "Long-read Pacific Biosciences HiFi sequencing", "data_format": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single HiFi BAM or FastQ?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_ribotricer_prepareorfs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accurate detection of short and long active ORFs using Ribo-seq data (tools: ribotricer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"survivor/merge": "Compare or merge VCF files to generate a consensus or multi sample VCF files.", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "ribotricer/prepareorfs": "Accurate detection of short and long active ORFs using Ribo-seq data", "mafft/align": "Multiple sequence alignment using MAFFT", "plastid/metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere"}}, "target": "ribotricer/prepareorfs", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Metagenomic MAG assembly with comparative groups)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Metagenomic MAG assembly with comparative groups with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "mod_orfm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A simple and not slow open reading frame (ORF) caller. The goal is to return a FASTA file of open reading frames over a certain length from a FASTA/Q file of nucleotide sequences. (tools: orfm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c", "faa_seqfu_seqkit": "Subworkflow that optionally preprocesses amino acid FASTA sequences\n(seqkit seq/replace/rmdup), computes seque", "custom/orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom", "orfm": "A simple and not slow open reading frame (ORF) caller. The goal is to return a FASTA file of open reading fram", "chewbbaca/createschema": "Create a schema to determine the allelic profiles of a genome"}}, "target": "orfm", "target_idx": 3}
{"id": "mod_tabix_tabix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file, or extract regions from a bgzipped VCF file\nusing an optional regions file. (tools: tabix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "tabix_tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,", "gatk4_mergebamalignment": "Merge unmapped with mapped BAM files", "bases2fastq": "Demultiplex Element Biosciences bases files"}}, "target": "tabix_tabix", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Tumor-only somatic variant calling without matched normal", "data_format": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Tumor-only somatic variant calling without matched normal?", "criteria": {"patient,normal,tumor": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_1_5", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_cnvpytor_callcnvs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Command line tool for calling CNVs in whole genome sequencing data (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tabix/tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,", "cnvpytor/callcnvs": "Command line tool for calling CNVs in whole genome sequencing data", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples).", "canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "openms/textexporter": "Exports various OpenMS XML formats (featureXML, consensusXML, idXML, mzML) to a human-readable text format."}}, "target": "cnvpytor/callcnvs", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_6_5", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns are standard for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq input samplesheet?", "criteria": {"sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_6_5", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns are standard for Metagenomic MAG assembly with comparative groups input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "field_constraint_status_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_8", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Single-end Oxford Nanopore direct RNA. Input files: Single fastq per sample.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Single-end Oxford Nanopore direct RNA.", "criteria": {"sample,fast5": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "subworkflow_pkg_homer_groseq_0", "category": "subworkflow_packaging", "state": {"subworkflow": "HOMER_GROSEQ", "modules": ["unzip", "homer/maketagdirectory", "homer/makeucscfile", "homer/findpeaks", "homer/pos2bed"], "description": "Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.ucsd.edu/homer/ngs/groseq/groseq.html)."}, "question": {"type": "choice", "instructions": "How should HOMER_GROSEQ (unzip, homer/maketagdirectory, homer/makeucscfile, homer/findpeaks, homer/pos2bed) be structured in DSL2?", "criteria": {"Local subworkflow HOMER_GROSEQ": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow homer_groseq": null, "Leave them out": null}}, "target": "Use nf-core subworkflow homer_groseq", "target_idx": 2}
{"id": "mod_rseqc_innerdistance_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate inner distance between read pairs. (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc_innerdistance": "Calculate inner distance between read pairs.", "macs2_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "bedtools_intersect": "Allows one to screen for overlaps between two sets of genomic features.", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "orfipy": "orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner."}}, "target": "rseqc_innerdistance", "target_idx": 0}
{"id": "resource_allelecounter_3", "category": "resource_profiling", "state": {"process": "ALLELECOUNTER", "tool": "allelecounter", "description": "Generates a count of coverage of alleles"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALLELECOUNTER (Generates a count of coverage of alleles) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_metaboigniter_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data.. Topics: identification, mass-spectrometry, metabolomics, ms1, ms2, quantification. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylong": null, "metaboigniter": null, "hicar": null, "lsmquant": null, "riboseq": null, "demultiplex": null, "mhcquant": null, "nanostring": null}}, "target": "metaboigniter", "target_idx": 1}
{"id": "core_tool_deepvariant_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Deep neural network-based variant caller transforming aligned reads into pileup tensor images for high-accuracy SNP/indel detection.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"gatk_haplotypecaller": null, "deepvariant": null, "clair3": null, "varscan2": null, "freebayes": null}}, "target": "deepvariant", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_bamcmp_bwa_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BAMCMP_BWA", "modules": ["bamcmp", "bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better to the first genome, then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BAMCMP_BWA (bamcmp, bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_BAMCMP_BWA": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_bamcmp_bwa": null}}, "target": "Use nf-core subworkflow fastq_align_bamcmp_bwa", "target_idx": 3}
{"id": "field_constraint_sample_0_4", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null, "enum: [0, 1]": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "mod_tsebra_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extrisic evidence support (tools: tsebra)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "sourmash_pairwise": "Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch.", "alignoth": "Creating alignment plots from bam files", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris"}}, "target": "tsebra", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_0_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_gatk4_sitedepthtobaf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: EXPERIMENTAL TOOL! Convert SiteDepth to BafEvidence (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr/estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4/sitedepthtobaf": "EXPERIMENTAL TOOL! Convert SiteDepth to BafEvidence", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th"}}, "target": "gatk4/sitedepthtobaf", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_4", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_ampcombi_0", "category": "resource_profiling", "state": {"process": "AMPCOMBI", "tool": "ampcombi", "description": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI (A tool to parse and summarise results from antimicrobial peptides tools and pres) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_authentict_deam2cont_4", "category": "resource_profiling", "state": {"process": "AUTHENTICT_DEAM2CONT", "tool": "authentict/deam2cont", "description": "Use deamination patterns to estimate contamination in single-stranded libraries"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTHENTICT_DEAM2CONT (Use deamination patterns to estimate contamination in single-stranded libraries) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_38", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_agat_convertbed2gff_4", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTBED2GFF", "tool": "agat/convertbed2gff", "description": "Takes a bed12 file and converts to a GFF3 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTBED2GFF (Takes a bed12 file and converts to a GFF3 file) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_14", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_antismash_antismashlitedownloaddatabases_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs. (tools: antismash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "bismark/report": "Collects bismark alignment reports", "deepbgc/pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "diamond/makedb": "Builds a DIAMOND database"}}, "target": "antismash/antismashlitedownloaddatabases", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_6_0", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "FASTQC", "library_inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Viral amplicon sequencing with primers input samplesheet?", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_0_3", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "template": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "samplesheet_arch_vcf_annotation_pipeline_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/raredisease) for Downstream functional annotation of pre-called VCF files. Input files: BGZF-compressed VCF files with companion Tabix index files.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Downstream functional annotation of pre-called VCF files with entry step ENSEMBLVEP.", "criteria": {"sample,vcf,tbi": null, "sample,bed": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_26", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_bcftools_roh_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROH", "tool": "bcftools/roh", "description": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROH (A program for detecting runs of homo/autozygosity. Only bi-allelic sites are con) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gatk4_germlinecnvcaller_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPloidy. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "gatk4_concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "gatk4_germlinecnvcaller": "Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPlo", "custom_addmostseverepli": "Annotate a VEP annotated VCF with the most severe pLi field", "cnvkit_call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number"}}, "target": "gatk4_germlinecnvcaller", "target_idx": 2}
{"id": "samplesheet_arch_pediatric_trio_somatic_1_3", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_odgi_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone_checksum": "Check files in a destination path against a checksum SUM file", "odgi_draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "odgi_sort": "Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm.", "topas_gencons": "Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage presen", "odgi_build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1."}}, "target": "odgi_sort", "target_idx": 2}
{"id": "mod_bcftools_consensus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses VCF files (tools: consensus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_consensus": null, "bcftools_filter": null, "seqtk_rename": null, "seqkit_replace": null, "aardvark_merge": null}}, "target": "bcftools_consensus", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_hackgap_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, JIT-compiled k-mer counter supporting both contiguous and gapped k-mers using multi-way bucketed Cuckoo hash tables. (tools: hackgap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hackgap/count": null, "ganon/report": null, "fastq_shortreads_preprocess_qc": null, "fastq_find_mirna_mirdeep2": null, "ganon/classify": null}}, "target": "hackgap/count", "target_idx": 0}
{"id": "noul_container_environment_specification_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_9", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_28", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_glnexus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: merge gVCF files and perform joint variant calling (tools: glnexus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file.", "glnexus": "merge gVCF files and perform joint variant calling", "bedtools_nuc": "Profiles the nucleotide content of intervals in a fasta file.", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "biobambam_bammerge": "Merge a list of sorted bam files"}}, "target": "glnexus", "target_idx": 1}
{"id": "mod_pairtools_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort a .pairs/.pairsam file (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "pairtools/sort": "Sort a .pairs/.pairsam file", "bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "vembrane/filter": "Filter VCF files with vembrane", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler."}}, "target": "pairtools/sort", "target_idx": 1}
{"id": "mod_bioawk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats. (tools: bioawk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety/embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "bioawk": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats.", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "cooler/merge": "Merge multiple coolers with identical axes", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "bioawk", "target_idx": 1}
{"id": "pipe_all101_crisprseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for crispr. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "metapep": "From metagenomes to epitopes and beyond", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step"}}, "target": "crisprseq", "target_idx": 2}
{"id": "noul_confusing_combine_with_mix_semantics_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_openms_idmerger_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges several idXML files into one idXML file. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "openms_idmerger": "Merges several idXML files into one idXML file.", "starfusion_detect": "Fast and Accurate Fusion Transcript Detection from RNA-Seq", "biobambam_bammerge": "Merge a list of sorted bam files", "oncocnv": "Calls CNVs in bam files from tumor patients"}}, "target": "openms_idmerger", "target_idx": 1}
{"id": "pipe_all101_clipseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for clip analysis? Specific context: CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling options.. Topics: clip, clip-seq, peak-calling, rna-rbp-interactions. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i"}}, "target": "clipseq", "target_idx": 5}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_4_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FastQ reads per sample?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_cellranger_mkgtf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build a filtered GTF needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkgtf command. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie_align": "Align reads to a reference genome using bowtie", "cellranger_mkgtf": "Module to build a filtered GTF needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkgtf command.", "biscuit_index": "Indexes a reference genome for use with Biscuit", "resfinder_run": "ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteri", "autocycler_trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}}, "target": "cellranger_mkgtf", "target_idx": 1}
{"id": "mod_hmmcopy_gccounter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta reference (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmcopy/mapcounter": "mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a big", "hmmcopy/readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows", "hmmcopy/gccounter": "gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta", "atlas/recal": "Gives an estimation of the sequencing bias based on known invariant sites", "artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}}, "target": "hmmcopy/gccounter", "target_idx": 2}
{"id": "pipe_all101_genomeqc_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for genome-assembly-evaluation. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": "Read-based functional profiling of microbiome sequencing data", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]"}}, "target": "genomeqc", "target_idx": 5}
{"id": "mod_fasta_build_add_kraken2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KRAKEN2 build custom database subworkflow (tools: fasta_build_add_kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "fasta_build_add_kraken2": "KRAKEN2 build custom database subworkflow", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "vsearch_fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format.", "ganon_report": "Generate a ganon report file from the output of ganon classify"}}, "target": "fasta_build_add_kraken2", "target_idx": 1}
{"id": "mod_picard_fastqtosam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a FASTQ file to an unaligned BAM or SAM file. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/getref": "Download and prepare database for Ariba analysis", "cnvkit/export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "picard/fastqtosam": "Converts a FASTQ file to an unaligned BAM or SAM file.", "deeparg/predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes"}}, "target": "picard/fastqtosam", "target_idx": 3}
{"id": "mod_gtdbtk_gtdbtoncbimajorityvote_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy (tools: gtdbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gtdbtk/classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "gtdbtk/gtdbtoncbimajorityvote": "Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "bio2zarr/vcf2zarrexplode": "Convert VCF(s) to intermediate columnar format (ICF)", "catpack/download": "Downloads the required files for either Nr or GTDB for building into a CAT database"}}, "target": "gtdbtk/gtdbtoncbimajorityvote", "target_idx": 1}
{"id": "pipe_all101_drugresponseeval_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pipeline for testing drug response prediction models in a statistically and biologically sound way.. Topics: cell-lines, cross-validation, deep-learning, drug-response, drug-response-prediction, drugs. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"molkart": null, "bamtofastq": null, "magmap": null, "chipseq": null, "circdna": null, "references": null, "proteinfold": null, "slamseq": null, "fastquorum": null, "drugresponseeval": null}}, "target": "drugresponseeval", "target_idx": 9}
{"id": "mod_tcoffee_irmsd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the irmsd score for a given alignment and the structures. (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "tcoffee/irmsd": null, "picard/meanqualitybycycle": null, "bwa/mem": null, "abra2": null}}, "target": "tcoffee/irmsd", "target_idx": 1}
{"id": "mod_mmseqs_createdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create an MMseqs database from an existing FASTA/Q file (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/createdb": "Create an MMseqs database from an existing FASTA/Q file", "mmseqs/createindex": "Creates sequence index for mmseqs database", "mmseqs/cluster": "Cluster sequences using MMSeqs2 cluster.", "bam2fastx/bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "strvctvre/strvctvre": "a structural variant classifier for exonic deletions and duplications"}}, "target": "mmseqs/createdb", "target_idx": 0}
{"id": "resource_bedtools_coverage_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COVERAGE", "tool": "bedtools/coverage", "description": "computes both the depth and breadth of coverage of features in file B on the features in file A"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COVERAGE (computes both the depth and breadth of coverage of features in file B on the fea) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_seqkit_rmdup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...) (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wipertools_reportgather": "A tool of the wipertools suite that merges wiping reports generated by wipertools_fastqwiper", "seqkit_rmdup": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "epang_place": "phylogenetic placement of query sequences in a reference tree", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID"}}, "target": "seqkit_rmdup", "target_idx": 1}
{"id": "pipe_core10_viralrecon_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Targeted ARTIC amplicon sequencing for reconstructing viral genomes and identifying emerging variant mutations.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)"}}, "target": "viralrecon", "target_idx": 4}
{"id": "mod_varscan_fpfilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, and copy number variations in both somatic and germline samples. It is particularly useful for analyzing tumor/normal sample pairs. Subtool fpfilter is used to filter a set of SNPs/indels based on coverage, reads, p-value, etc. (tools: varscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"varscan_fpfilter": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "atlas_call": "generate VCF file from a BAM file using various calling methods", "plink_bcf": "Analyses binary variant call format (BCF) files using plink", "bcftools_concat": "Concatenate VCF files"}}, "target": "varscan_fpfilter", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wgs_pe_6_5", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for Standard Paired-end Whole Genome Sequencing (WGS) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "local_subworkflow_prepontreads_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should this step (porechop, nanoplot) be packaged: Nanopore adapter trimming and read quality visualization?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null, "Leave them out": null, "Local subworkflow PREPONTREADS": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 3}
{"id": "pipe_all101_nanoseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for alignment analysis? Specific context: Nanopore demultiplexing, QC and alignment pipeline. Topics: alignment, demultiplexing, nanopore, qc. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]"}}, "target": "nanoseq", "target_idx": 2}
{"id": "resource_bowtie2_align_3", "category": "resource_profiling", "state": {"process": "BOWTIE2_ALIGN", "tool": "bowtie2/align", "description": "Align reads to a reference genome using bowtie2"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_ALIGN (Align reads to a reference genome using bowtie2) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_marsseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: MARS-seq v2 pre-processing pipeline with velocity. Topics: facs-sorting, mars-seq, single-cell, single-cell-rna-seq, star-solo, transcriptional-dynamics. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]"}}, "target": "marsseq", "target_idx": 1}
{"id": "noul_include_modular_process_syntax_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_build_pipeline_9", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "debug_error": null, "build_pipeline": null}}, "target": "build_pipeline", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "data_format": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,bam": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "subworkflow_pkg_bam_sort_stats_samtools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SORT_STATS_SAMTOOLS", "modules": ["samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Sort SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_SORT_STATS_SAMTOOLS (samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_sort_stats_samtools": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_SORT_STATS_SAMTOOLS": null}}, "target": "Use nf-core subworkflow bam_sort_stats_samtools", "target_idx": 0}
{"id": "mod_bam_impute_stitch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute BAM files using STITCH software.\nVariants location to impute are obtain through the legend file given.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: bam_impute_stitch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunc/downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "last/dotplot": "Makes a dotplot (Oxford Grid) of pair-wise sequence alignments", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bamclipper": "This module is used to clip primer sequences from your alignments.", "bam_impute_stitch": "Subworkflow to impute BAM files using STITCH software.\nVariants location to impute are obtain through the lege"}}, "target": "bam_impute_stitch", "target_idx": 4}
{"id": "samplesheet_arch_faire_seq_chromatin_6_4", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for FAIRE-seq / DNAse-seq open chromatin profiling input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_6_4", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "resource_bamtools_stats_4", "category": "resource_profiling", "state": {"process": "BAMTOOLS_STATS", "tool": "bamtools/stats", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_STATS (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_hicar_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for atac analysis? Specific context: Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.. Topics: atac, atac-seq, hic, hicar, multi-omics, transcriptome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom"}}, "target": "hicar", "target_idx": 4}
{"id": "samplesheet_arch_mira_influenza_sc2_1_2", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels", "pipeline": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_custom_clustervisualization_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates UMAP and t-SNE visualizations colored by cluster (tools: scikit-learn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dragen_germline": "The DRAGEN DNA Germline Pipeline accelerates the secondary analysis of NGS data by harnessing the tremendous p", "custom_orfmerge": "Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `cus", "custom_clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "samtools_flagstat": "Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type", "custom_clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy"}}, "target": "custom_clustervisualization", "target_idx": 2}
{"id": "subworkflow_pkg_abundance_differential_filter_1", "category": "subworkflow_packaging", "state": {"subworkflow": "ABUNDANCE_DIFFERENTIAL_FILTER", "modules": ["limma/differential", "deseq2/differential", "propr/propd", "custom/filterdifferentialtable", "variancepartition/dream"], "description": "A subworkflow for filtering differential abundance results"}, "question": {"type": "choice", "instructions": "How should ABUNDANCE_DIFFERENTIAL_FILTER (limma/differential, deseq2/differential, propr/propd, custom/filterdifferentialtable, variancepartition/dream) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow abundance_differential_filter": null, "Local subworkflow ABUNDANCE_DIFFERENTIAL_FILTER": null, "Leave them out": null}}, "target": "Use nf-core subworkflow abundance_differential_filter", "target_idx": 1}
{"id": "mod_trtools_dumpstr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a filtered VCF file. (tools: trtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trtools/dumpstr": "DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a fi", "expansionhunterdenovo/merge": "Merge STR profiles into a multi-sample STR profile", "rseqc/innerdistance": "Calculate inner distance between read pairs.", "motus/preplong": "Taxonomic meta-omics profiling using universal marker genes", "hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data"}}, "target": "trtools/dumpstr", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_1_5", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "template": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_raredisease_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Call and score variants from WGS/WES of rare disease patients.. Topics: diagnostics, rare-disease, snv, structural-variants, variant-annotation, variant-calling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]"}}, "target": "raredisease", "target_idx": 4}
{"id": "local_subworkflow_positionsofint_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should this step (custom/positionsofint) be packaged: Position of interest depth extraction?", "criteria": {"Leave them out": null, "Local subworkflow POSITIONSOFINT": null, "Use nf-core subworkflow positionsofint": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 1}
{"id": "schema_std_reportho_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/reportho", "assay": "reportho pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/reportho (nf-core pipeline for comparative analysis of ortholog predic)?", "criteria": {"id,fasta,query": null, "sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,group": null, "sample,tools,file,index": null}}, "target": "id,fasta,query", "target_idx": 0}
{"id": "mod_wisecondorx_newref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a new reference using healthy reference samples (tools: wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "wisecondorx_newref": "Create a new reference using healthy reference samples", "panaroo_run": "A fast and scalable tool for bacterial pangenome analysis", "emboss_seqret": "Reads in one or more sequences, converts, filters, or transforms them and writes them out again", "bowtie_align": "Align reads to a reference genome using bowtie"}}, "target": "wisecondorx_newref", "target_idx": 1}
{"id": "subworkflow_pkg_bam_dedup_stats_samtools_umitools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS", "modules": ["umitools/dedup", "samtools/index", "samtools/view", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS (umitools/dedup, samtools/index, samtools/view, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS": null, "Use nf-core subworkflow bam_dedup_stats_samtools_umitools": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umitools", "target_idx": 3}
{"id": "noul_channel_join_operator_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_binette_0", "category": "resource_profiling", "state": {"process": "BINETTE", "tool": "binette", "description": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BINETTE (A fast and accurate binning refinement tool to construct high quality MAGs from ) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_demultiplex_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/demultiplex. Description: Demultiplexing pipeline for sequencing data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/demultiplex.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,seq_data,pbi,start_from": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,bundle,image": null}}, "target": "id,samplesheet,lane,flowcell,per_flowcell_manifest", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_1_4", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "mod_svdb_query_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Query a structural variant database, using a vcf file as query (tools: svdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svdb/query": "Query a structural variant database, using a vcf file as query", "dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "tmb/pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "metaphlan3/mergemetaphlantables": "Merges output abundance tables from MetaPhlAn3", "caddsv/run": "Score structural variants with CADD-SV."}}, "target": "svdb/query", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_35", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_bedtools_bamtobed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a bam file to a bed12 file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "msisensorpro/baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "ascat": "copy number profiles of tumour cells.", "bedtools/bamtobed": "Converts a bam file to a bed12 file."}}, "target": "bedtools/bamtobed", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_1_46", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bcftools_merge_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MERGE", "tool": "bcftools/merge", "description": "Merge VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MERGE (Merge VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_tcoffee_tcs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just the total TCS score. (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "tcoffee/tcs": "Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just", "gridss/annotate": "Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmaske", "samshee": "Module to validate illumina® Sample Sheet v2 files."}}, "target": "tcoffee/tcs", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_bgzip_index_dict_samtools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BGZIP_INDEX_DICT_SAMTOOLS", "modules": ["htslib/bgziptabix", "samtools/dict", "samtools/faidx"], "description": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA file."}, "question": {"type": "choice", "instructions": "How should FASTA_BGZIP_INDEX_DICT_SAMTOOLS (htslib/bgziptabix, samtools/dict, samtools/faidx) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_bgzip_index_dict_samtools": null, "Local subworkflow FASTA_BGZIP_INDEX_DICT_SAMTOOLS": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_bgzip_index_dict_samtools", "target_idx": 0}
{"id": "pipe_all101_nanostring_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for nanostring. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]"}}, "target": "nanostring", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_0_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "PBMM2_ALIGN", "library_inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_15", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_mtnucratio_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A small Java tool to calculate ratios between MT and nuclear sequencing reads in a given BAM file. (tools: mtnucratio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_head": null, "holodeck_simulate": null, "picard_renamesampleinvcf": null, "mtnucratio": null, "deeptools_plotpca": null}}, "target": "mtnucratio", "target_idx": 3}
{"id": "mod_vclust_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like ANI and coverage (alignment fraction) (tools: vclust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "rseqc_readduplication": "Calculate read duplication rate", "opt_flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple", "vclust_align": "The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like", "isoseq_cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences"}}, "target": "vclust_align", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_dedup_bismark_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BISMARK", "modules": ["bismark/align", "samtools/sort", "samtools/index", "bismark/deduplicate", "bismark/methylationextractor", "bismark/coverage2cytosine", "bismark/report", "bismark/summary"], "description": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BISMARK (bismark/align, samtools/sort, samtools/index, bismark/deduplicate, bismark/methylationextractor, bismark/coverage2cytosine, bismark/report, bismark/summary) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_dedup_bismark": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_DEDUP_BISMARK": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bismark", "target_idx": 1}
{"id": "resource_bedtools_merge_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MERGE", "tool": "bedtools/merge", "description": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MERGE (combines overlapping or “book-ended” features in an interval file into a single ) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_mageck_test_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mageck test performs a robust ranking aggregation (RRA) to identify positively or negatively selected genes in functional genomics screens. (tools: mageck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "bedtools/unionbedg": "Combines multiple BedGraph files into a single file", "picard/liftovervcf": "Lifts over a VCF file from one reference build to another.", "biobambam/bamsormadup": "Parallel sorting and duplicate marking", "mageck/test": "Mageck test performs a robust ranking aggregation (RRA) to identify positively or negatively selected genes in"}}, "target": "mageck/test", "target_idx": 4}
{"id": "mod_oarfish_alignmentmode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quantify pre-computed alignments of reads to the transcriptome (a name-sorted BAM, e.g. from minimap2/pbmm2). (tools: oarfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromap_chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "oarfish_alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "samplesheetparser_diff": "Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff cove"}}, "target": "oarfish_alignmentmode", "target_idx": 3}
{"id": "mod_ucsc_liftover_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: convert between genome builds (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leviosam2/index": null, "bedops/convert2bed": null, "adapterremovalfixprefix": null, "annotsv/annotsv": null, "ucsc/liftover": null}}, "target": "ucsc/liftover", "target_idx": 4}
{"id": "pipe_all101_funcprofiler_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Read-based functional profiling of microbiome sequencing data. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "funcprofiler": "Read-based functional profiling of microbiome sequencing data"}}, "target": "funcprofiler", "target_idx": 7}
{"id": "resource_bcl2fastq_4", "category": "resource_profiling", "state": {"process": "BCL2FASTQ", "tool": "bcl2fastq", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCL2FASTQ (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_ribotricer_detectorfs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accurate detection of short and long active ORFs using Ribo-seq data (tools: ribotricer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scvitools_solo": "Detect doublets in single-cell RNA-Seq data", "ribotricer_detectorfs": "Accurate detection of short and long active ORFs using Ribo-seq data", "bam_variant_calling_mpileup_bcftools": "Subworkflow to compute genotype likelihoods from BAM files using\nbcftools/mpileup and bcftools/call variants b", "plastid_metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "gedi_indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction"}}, "target": "ribotricer_detectorfs", "target_idx": 1}
{"id": "resource_bedtools_multiinter_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MULTIINTER", "tool": "bedtools/multiinter", "description": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MULTIINTER (Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_sample_0_7", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "noul_channel_factory_inside_process_body_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "schema_std_atacseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay": "atacseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/atacseq (ATAC-seq peak-calling and QC analysis pipeline)?", "criteria": {"sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,fastq_1,fastq_2,replicate,control": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate,control", "target_idx": 1}
{"id": "mod_sylphtax_taxprof_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Incorporates taxonomy into sylph metagenomic classifier (tools: sylphtax)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/sendsketch": null, "muse/call": null, "sylphtax/taxprof": null, "ganon/buildcustom": null, "plastid/psite": null}}, "target": "sylphtax/taxprof", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_classify_catpack_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CLASSIFY_CATPACK", "modules": ["catpack/addnames", "catpack/bins", "catpack/contigs", "catpack/download", "catpack/prepare", "catpack/summarise", "untar"], "description": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack)."}, "question": {"type": "choice", "instructions": "How should FASTA_CLASSIFY_CATPACK (catpack/addnames, catpack/bins, catpack/contigs, catpack/download, catpack/prepare, catpack/summarise, untar) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_CLASSIFY_CATPACK": null, "Use nf-core subworkflow fasta_classify_catpack": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_classify_catpack", "target_idx": 1}
{"id": "resource_amps_1", "category": "resource_profiling", "state": {"process": "AMPS", "tool": "amps", "description": "Post-processing script of the MaltExtract component of the HOPS package"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPS (Post-processing script of the MaltExtract component of the HOPS package) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_default_empty_channel_behavior_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_gapseq_draft_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create draft metabolic model from pathway and transporter predictions (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pindel/pindel": "Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and", "gapseq/requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "shigeifinder": "Determine Shigella serotype from assemblies or Illumina paired-end reads", "gapseq/draft": "Create draft metabolic model from pathway and transporter predictions", "gapseq/fill": "Perform gap filling on draft metabolic model"}}, "target": "gapseq/draft", "target_idx": 3}
{"id": "pipe_all101_coproid_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for adna analysis? Specific context: Coprolite host Identification pipeline. Topics: adna, ancient-dna, coprolite, microbiome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "callingcards": "A pipeline for processing calling cards data", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]"}}, "target": "coproid", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wgs_pe_4_3", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Raw paired-end Illumina WGS FASTQs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "field_constraint_bam_0_7", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_43", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "subworkflow_pkg_dia_proteomics_analysis_1", "category": "subworkflow_packaging", "state": {"subworkflow": "DIA_PROTEOMICS_ANALYSIS", "modules": ["diann", "quantmsutils/dianncfg", "quantmsutils/mzmlstatistics", "quantmsutils/diann2mztab"], "description": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,"}, "question": {"type": "choice", "instructions": "How should DIA_PROTEOMICS_ANALYSIS (diann, quantmsutils/dianncfg, quantmsutils/mzmlstatistics, quantmsutils/diann2mztab) be structured in DSL2?", "criteria": {"Local subworkflow DIA_PROTEOMICS_ANALYSIS": null, "Leave them out": null, "Use nf-core subworkflow dia_proteomics_analysis": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow dia_proteomics_analysis", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_1", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_snpeff_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genetic variant annotation and functional effect prediction toolbox (tools: snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "fgumi/downsample": "Downsample a BAM by UMI family using streaming with fgumi", "snpeff/download": "Genetic variant annotation and functional effect prediction toolbox", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "busco/busco": "Benchmarking Universal Single Copy Orthologs"}}, "target": "snpeff/download", "target_idx": 2}
{"id": "resource_bcftools_reheader_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_REHEADER", "tool": "bcftools/reheader", "description": "Reheader a VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_REHEADER (Reheader a VCF file) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_gatk4_shiftfasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a fasta with the bases shifted by offset (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output", "gatk4_shiftfasta": "Create a fasta with the bases shifted by offset", "elprep_split": "Split bam file into manageable chunks", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a"}}, "target": "gatk4_shiftfasta", "target_idx": 1}
{"id": "mod_bbmap_pileup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_group": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "bbmap_pileup": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file.", "ultraplex": "Ultraplex is an all-in-one software package for processing and demultiplexing fastq files.", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "bbmap_pileup", "target_idx": 1}
{"id": "schema_std_multiplesequencealign_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/multiplesequencealign", "description": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/multiplesequencealign?", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "id,fasta,reference,optional_data,template": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "id,fasta,reference,optional_data,template", "target_idx": 2}
{"id": "pipe_all101_stableexpression_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for expression analysis? Specific context: This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). The ideal use case is for determining the most suitable RT-qPCR reference genes for a given species.. Topics: expression, housekeeping-genes, qpcr-analysis. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "funcprofiler": "Read-based functional profiling of microbiome sequencing data"}}, "target": "stableexpression", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_fastp_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_FASTP", "modules": ["fastqc", "umitools/extract", "fastp"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_FASTP (fastqc, umitools/extract, fastp) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_fastqc_umitools_fastp": null, "Local subworkflow FASTQ_FASTQC_UMITOOLS_FASTP": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_fastp", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_0_0", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_bcftools_reheader_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reheader a VCF file (tools: reheader)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"traitar_run": "Traitar3 - predict microbial phenotypes from genomic sequences using protein families", "bcftools_reheader": "Reheader a VCF file", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bcftools_annotate": "Add or remove annotations.", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "bcftools_reheader", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_5_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_named_output_channel_access_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral amplicon sequencing with primers. Input files: Paired-end tiled viral amplicon FASTQs per clinical swab sample.", "question": {"type": "choice", "instructions": "Which columns are standard for Viral amplicon sequencing with primers input samplesheet?", "criteria": {"sample,fasta": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_executor_support_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_43", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_ont_metagenome_single_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Long-read Oxford Nanopore environmental metagenomic sequencing. Input files: High molecular weight environmental metagenomic long reads per sampling site.", "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Oxford Nanopore environmental metagenomic sequencing input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cutandrun) for CUT&RUN / CUT&TAG chromatin profiling with IgG control. Input files: Paired-end low-input fragment FASTQs with target antibody and IgG negative control.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_8", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_core10_eager_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Archaeological skeletal sample sequencing for DNA degradation estimation, deamination analysis, and mitochondrial consensus reconstruction.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"eager": null, "ampliseq": null, "sarek": null, "viralrecon": null, "scrnaseq": null, "atacseq": null, "mag": null, "chipseq": null, "taxprofiler": null, "rnaseq": null}}, "target": "eager", "target_idx": 0}
{"id": "local_subworkflow_prepontreads_2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPONTREADS (porechop, nanoplot).", "criteria": {"Leave them out": null, "Use nf-core subworkflow prepontreads": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPONTREADS": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 3}
{"id": "noul_named_process_output_emits_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_fastq_1_0_1", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "mod_biscuit_bsconv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarize and/or filter reads based on bisulfite conversion rate (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/biscuitblaster": null, "biscuit/align": null, "strdrop/build": null, "arriba/arriba": null, "biscuit/bsconv": null}}, "target": "biscuit/bsconv", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_34", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_airrflow_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/airrflow", "assay": "airrflow pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/airrflow (B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR))?", "criteria": {"sample_id,subject_id,species,pcr_target_locus,tissue": null, "id,raw_file": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "sample_id,subject_id,species,pcr_target_locus,tissue", "target_idx": 0}
{"id": "mod_vcf2zarr_explode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF(s) to intermediate columnar format (tools: vcf2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_fasta_cluster": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file.", "atlas/call": "generate VCF file from a BAM file using various calling methods", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "vcf2zarr/explode": "Convert VCF(s) to intermediate columnar format", "wisecondorx/convert": "Convert and filter aligned reads to .npz"}}, "target": "vcf2zarr/explode", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_15", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_ribotricer_prepareorfs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accurate detection of short and long active ORFs using Ribo-seq data (tools: ribotricer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"manta_convertinversion": null, "ribowaltz": null, "ribotricer_prepareorfs": null, "anota2seq_anota2seqrun": null, "gedi_indexgenome": null}}, "target": "ribotricer_prepareorfs", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: FAIRE-seq / DNAse-seq open chromatin profiling)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,bed": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bamutil_clipoverlap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality. (tools: bamutil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fast2q": "A program that counts sequence occurrences in FASTQ files.", "deepmased_features": "DeepMAsED features subcommand: extracts alignment-based features from BAM and assembly FASTA for each contig, ", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "bamclipper": "This module is used to clip primer sequences from your alignments.", "bamutil_clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo"}}, "target": "bamutil_clipoverlap", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_0_5", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/cageseq --input samplesheet.csv (Assay: CAGE-seq 5-prime capped transcript end sequencing)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cageseq, determine the input samplesheet column structure for: CAGE-seq 5-prime capped transcript end sequencing.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_plink_recode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Recodes plink bfiles into a new text fileset applying different modifiers (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq3_tag": null, "plink_genome": null, "plink_extract": null, "plink_recode": null, "bismark_summary": null}}, "target": "plink_recode", "target_idx": 3}
{"id": "core_tool_deepvariant_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Deep neural network-based variant caller transforming aligned reads into pileup tensor images for high-accuracy SNP/indel detection.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"gatk_haplotypecaller": "GATK caller", "varscan2": "Variant caller", "deepvariant": "Deep learning-based variant caller that calls genetic variants using neural networks", "clair3": "Neural caller", "freebayes": "Bayesian caller"}}, "target": "deepvariant", "target_idx": 2}
{"id": "mod_plink_recode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Recodes plink bfiles into a new text fileset applying different modifiers (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eigenstratdatabasetools/eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset.", "rclone/checksum": "Check files in a destination path against a checksum SUM file", "plink/recode": "Recodes plink bfiles into a new text fileset applying different modifiers", "plink/genome": "Calculates identity-by-descent over autosomal SNPs", "plink/exclude": "Exclude variant identifiers from plink bfiles"}}, "target": "plink/recode", "target_idx": 2}
{"id": "field_constraint_fastq_2_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "core_tool_kallisto_bustools_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Ultra-fast pseudoalignment and barcode/UMI processing for single-cell RNA-seq generating bustools count matrices.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"alevin": null, "salmon": null, "starsolo": null, "cellranger": null, "kallisto_bustools": null}}, "target": "kallisto_bustools", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_1_27", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_octopusv_correct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Standardize a caller VCF into OctopuSV SVCF format. (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yahs": "Performs assembly scaffolding using YaHS", "pbsv_discover": "pbsv - PacBio structural variant (SV) signature discovery tool", "octopusv_correct": "Standardize a caller VCF into OctopuSV SVCF format.", "ragtag_scaffold": "Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. G", "svtools_vcftobedpe": "Convert a VCF file to a BEDPE file."}}, "target": "octopusv_correct", "target_idx": 2}
{"id": "mod_custom_multiqccustombiotype_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate MultiQC-compatible biotype count summaries from featureCounts output (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wgsim": "simulating sequence reads from a reference genome", "jasminesv": "Jointly Accurate Sv Merging with Intersample Network Edges", "nonpareil_nonpareilcurvesr": "Generate summary reports with raw data for Nonpareil NPO curves, including MultiQC compatible JSON/TSV files", "anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "custom_multiqccustombiotype", "target_idx": 4}
{"id": "pipe_core10_rnaseq_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Bulk paired-end RNA sequencing pipeline using STAR, Salmon, and DESeq2 differential expression analysis.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"atacseq": null, "eager": null, "ampliseq": null, "viralrecon": null, "chipseq": null, "rnaseq": null, "mag": null, "sarek": null, "taxprofiler": null, "scrnaseq": null}}, "target": "rnaseq", "target_idx": 5}
{"id": "samplesheet_arch_spatial_visium_2_4", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,image": null, "sample,image": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "mod_gt_gff3_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbtk/bam2fastq": "converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq", "gt/gff3": "GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "diamond/cluster": "calculate clusters of highly similar sequences", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file"}}, "target": "gt/gff3", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_2_0", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "FASTQC", "library_inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bbmap_clumpify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strelka/somatic": "Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small coh", "bbmap/clumpify": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "refsolver/identify": "Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver"}}, "target": "bbmap/clumpify", "target_idx": 1}
{"id": "field_constraint_bai_1_13", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "mod_hhsuite_hhsearch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs) (tools: hhsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hhsuite_hhsearch": null, "angsd_soapsnpcalibration": null, "deeptools_computematrix": null, "hmmer_hmmlogo": null, "hmmer_hmmemit": null}}, "target": "hhsuite_hhsearch", "target_idx": 0}
{"id": "pipe_all101_mhcquant_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Identify and quantify MHC eluted peptides from mass spectrometry raw data. Topics: dda, immunopeptidomics, mass-spectrometry, mhc, openms, peptides. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": null, "mhcquant": null, "metaboigniter": null, "metatdenovo": null, "proteinfamilies": null, "circdna": null, "isoseq": null, "genomeqc": null, "scnanoseq": null, "riboseq": null}}, "target": "mhcquant", "target_idx": 1}
{"id": "resource_amplify_predict_4", "category": "resource_profiling", "state": {"process": "AMPLIFY_PREDICT", "tool": "amplify/predict", "description": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPLIFY_PREDICT (AMPlify is an attentive deep learning model for antimicrobial peptide prediction) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bismark_align_4", "category": "resource_profiling", "state": {"process": "BISMARK_ALIGN", "tool": "bismark/align", "description": "Performs alignment of BS-Seq reads using bismark"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_ALIGN (Performs alignment of BS-Seq reads using bismark) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_fastp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform adapter/quality trimming on sequencing reads (tools: fastp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"telescope_assign": null, "chopper": null, "bbmap_bbduk": null, "fastp": null, "diamond_makedb": null}}, "target": "fastp", "target_idx": 3}
{"id": "samplesheet_arch_methylseq_bisulfite_3_1", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "template": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,cpg,methylation": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_gcta_reml_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run univariate REML heritability estimation with a dense GRM (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "wisecondorx/gender": "Returns the gender of a .npz resulting from convert, based on a Gaussian mixture model trained during the newr", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "gcta/calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups", "gcta/reml": "Run univariate REML heritability estimation with a dense GRM"}}, "target": "gcta/reml", "target_idx": 4}
{"id": "samplesheet_arch_prealigned_bam_indexed_0_0", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_0_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_35", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_33", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_bam_cnv_wisecondorx_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A subworkflow for calling CNVs using WisecondorX (tools: bam_cnv_wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "trimmomatic": "Performs quality and adapter trimming on paired end and single end reads", "fgumi/group": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "bam_cnv_wisecondorx": "A subworkflow for calling CNVs using WisecondorX"}}, "target": "bam_cnv_wisecondorx", "target_idx": 4}
{"id": "samplesheet_arch_germline_lane_split_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Multi-lane Illumina sequencing run of clinical samples", "data_format": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-lane Illumina sequencing run of clinical samples with entry step FASTQC.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_4_1", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen?", "criteria": {"sample,bam": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "noul_named_process_output_emits_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_ampir_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ampir uses a supervised statistical machine learning approach to predict AMPs. (tools: ampir)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "carveme_carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "ampir": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ", "agat_spstatistics": "Provides different type of statistics in text format from a GFF/GTF annotation file"}}, "target": "ampir", "target_idx": 3}
{"id": "schema_std_metapep_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/metapep. Description: From metagenomes to epitopes and beyond.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/metapep.", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,group,path,ref,method": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null}}, "target": "condition,type,microbiome_path,alleles,weights_path", "target_idx": 0}
{"id": "mod_gatk_unifiedgenotyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SNP and Indel variant caller on a per-locus basis (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/ftxpy": "Somatic VCF Feature Extraction tool from hap.y.", "gatk/unifiedgenotyper": "SNP and Indel variant caller on a per-locus basis", "scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "ascat": "copy number profiles of tumour cells.", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "gatk/unifiedgenotyper", "target_idx": 1}
{"id": "schema_std_diseasemodulediscovery_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diseasemodulediscovery", "description": "A pipeline for network-based disease module identification.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/diseasemodulediscovery?", "criteria": {"id,test_vcf,test_regions,caller,subsample": null, "sample,tools,file,index": null, "gene_name,alignment,tree,suite,tool": null, "seeds,network,perturbed_networks": null}}, "target": "seeds,network,perturbed_networks", "target_idx": 3}
{"id": "pipe_all101_mag_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Assembly and binning of metagenomes. Topics: annotation, assembly, binning, long-read-sequencing, metagenomes, metagenomics. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "metapep": "From metagenomes to epitopes and beyond", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab"}}, "target": "mag", "target_idx": 6}
{"id": "mod_gatk4_cnnscorevariants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a Convolutional Neural Net to filter annotated variants (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/pluginfixploidy": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignmen", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "gatk4/cnnscorevariants": "Apply a Convolutional Neural Net to filter annotated variants", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "gatk4/cnnscorevariants", "target_idx": 3}
{"id": "mod_hifitrimmer_processblast_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrimary output is a BED describing regions to exclude, a json of summary information, and an optional hits file. (tools: hifi-trimmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hificnv": "Copy number variant calling from PacBio HiFi reads", "bam2fastx_bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "hifitrimmer_processblast": "Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrima", "checkv_endtoend": "Assess the quality of metagenome-assembled viral genomes.", "upd": "Simple software to call UPD regions from germline exome/wgs trios."}}, "target": "hifitrimmer_processblast", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_align_dedup_bwamem_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BWAMEM", "modules": ["parabricks/fq2bam", "samtools/index", "picard/addorreplacereadgroups", "picard/markduplicates", "bam_sort_stats_samtools", "fastq_align_bwa"], "description": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BWAMEM (parabricks/fq2bam, samtools/index, picard/addorreplacereadgroups, picard/markduplicates, bam_sort_stats_samtools, fastq_align_bwa) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_DEDUP_BWAMEM": null, "Use nf-core subworkflow fastq_align_dedup_bwamem": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwamem", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_2_5", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,group": null, "sample,bam": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_gridss_assemble_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble breakend contigs for GRIDSS structural variant calling (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamclipper": "This module is used to clip primer sequences from your alignments.", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "gatk4/indexfeaturefile": "Creates an index for a feature file, e.g. VCF or BED file.", "gridss/assemble": "Assemble breakend contigs for GRIDSS structural variant calling", "purecn/normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as"}}, "target": "gridss/assemble", "target_idx": 3}
{"id": "mod_parabricks_deepvariant_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating deepvariant. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"graphtyper_vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "parabricks_deepvariant": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating deepvariant.", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "openms_psmfeatureextractor": "Computes extra features for each input PSM for use with Percolator rescoring.", "seqtk_rename": "Rename sequence names in FASTQ or FASTA files."}}, "target": "parabricks_deepvariant", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_0_1", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,bam": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_fasta_explore_search_plot_tidk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats\nalong a sliding window for each sequence in the input fasta file. Results are presented in\nTSV and SVG formats. The user can specify an a priori sequence for identification.\nPossible a posteriori sequences are also explored and the most frequent sequence is\nused for identification similar to the a priori sequence. seqkit/seq and seqkit/sort modules are\nalso included to filter out small sequences and sort sequences by length. (tools: fasta_explore_search_plot_tidk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "fasta_explore_search_plot_tidk": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats\nalong a sliding win", "freyja_update": "downloads new versions of the curated SARS-CoV-2 lineage file and barcodes", "deepcell_mesmer": "Deepcell/mesmer segmentation for whole-cell"}}, "target": "fasta_explore_search_plot_tidk", "target_idx": 2}
{"id": "intent_ask_question_5", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "debug_error": null, "ask_question": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 2}
{"id": "intent_build_pipeline_13", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "debug_error": null, "ask_question": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_catpack_prepare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a CAT_pack database based on input FASTAs (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/prepare": "Creates a CAT_pack database based on input FASTAs", "cat/cat": "A module for concatenation of gzipped or uncompressed files", "elprep/filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "coverm/contig": "Map reads to contigs and estimate coverage", "find/concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size"}}, "target": "catpack/prepare", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_3_2", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Fungal ITS1/ITS2 marker gene amplicon surveillance with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,unite_fasta": null, "sample,primer_its1,primer_its2": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_tiddit_cov_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the coverage of different regions from the bam file. (tools: tiddit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "krakentools/kreport2krona": "Takes a Kraken report file and prints out a krona-compatible TEXT file", "ataqv/mkarv": "mkarv function of a corresponding ataqv tool", "tiddit/cov": "Computes the coverage of different regions from the bam file."}}, "target": "tiddit/cov", "target_idx": 4}
{"id": "schema_std_metapep_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metapep", "assay": "metapep pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/metapep (From metagenomes to epitopes and beyond)?", "criteria": {"id,path": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,bam,bai,cram,crai": null, "condition,type,microbiome_path,alleles,weights_path": null}}, "target": "condition,type,microbiome_path,alleles,weights_path", "target_idx": 3}
{"id": "mod_hiphase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across multiple BAM files and samples (tools: hiphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiasm": "Whole-genome assembly using PacBio HiFi reads", "hificnv": "Copy number variant calling from PacBio HiFi reads", "fgumi_dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "quantmsutils_diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils", "hiphase": "Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across "}}, "target": "hiphase", "target_idx": 4}
{"id": "samplesheet_arch_riboseq_profiling_3_1", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "template": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Ribosome profiling (Ribo-seq) footprint sequencing with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_5_5", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "template": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/metatdenovo, determine the input samplesheet column structure for: Environmental community metatranscriptomics de novo assembly.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 2}
{"id": "resource_bigslice_downloaddb_2", "category": "resource_profiling", "state": {"process": "BIGSLICE_DOWNLOADDB", "tool": "bigslice/downloaddb", "description": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_DOWNLOADDB (Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nu) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_process_conditional_execution_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_22", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_variantprioritization_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/variantprioritization. Description: Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR)..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/variantprioritization.", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,condition,reference": null, "patient,sample,vcf,status,cna": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "patient,sample,vcf,status,cna", "target_idx": 2}
{"id": "schema_std_riboseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "assay": "riboseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/riboseq (Pipeline for the analysis of ribosome profiling, or Ribo-seq)?", "criteria": {"id,fasta": null, "sample_id,img_directory,parameter_file": null, "sample,group,path,ref,method": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,fastq_1,fastq_2,strandedness,type", "target_idx": 3}
{"id": "mod_samtools_stats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces comprehensive statistics from SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_sqstatbasic": null, "stacks_refmap": null, "regenie_runl1": null, "samtools_stats": null, "assemblyscan": null}}, "target": "samtools_stats", "target_idx": 3}
{"id": "mod_tcoffee_irmsd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the irmsd score for a given alignment and the structures. (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunc_downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "bcftools_annotate": "Add or remove annotations.", "tcoffee_irmsd": "Computes the irmsd score for a given alignment and the structures.", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "tcoffee_irmsd", "target_idx": 3}
{"id": "mod_cooler_digest_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate fragment-delimited genomic bins (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"peddy": "Manipulation, validation and exploration of pedigrees", "cooler_digest": "Generate fragment-delimited genomic bins", "cooler_balance": "Run matrix balancing on a cool file", "cooler_makebins": "Generate fixed-width genomic bins", "plasmidfinder": "Identify plasmids in bacterial sequences and assemblies"}}, "target": "cooler_digest", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_extract_kraken_krakentools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS", "modules": ["kraken2/kraken2", "krakentools/extractkrakenreads"], "description": "Extract classified Kraken2 reads by taxonomic id"}, "question": {"type": "choice", "instructions": "How should FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS (kraken2/kraken2, krakentools/extractkrakenreads) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_extract_kraken_krakentools": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS": null}}, "target": "Use nf-core subworkflow fastq_extract_kraken_krakentools", "target_idx": 0}
{"id": "intent_prepare_data_20", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "prepare_data", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_6_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns are standard for Longitudinal cancer monitoring across multiple timepoints input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/methylseq --input samplesheet.csv (Assay: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq))", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/methylseq, determine the input samplesheet column structure for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq).", "criteria": {"sample,vcf": null, "sample,cpg,methylation": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_artic_minion_0", "category": "resource_profiling", "state": {"process": "ARTIC_MINION", "tool": "artic/minion", "description": "Run the alignment/variant-call/consensus logic of the artic pipeline"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_MINION (Run the alignment/variant-call/consensus logic of the artic pipeline) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_pindel_pindel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and other structural variants at single-based resolution from next-gen sequence data (tools: pindel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse_sample": "Generates haplotype calls by sampling haplotype estimates", "jasminesv": "Jointly Accurate Sv Merging with Intersample Network Edges", "krakentools_combinekreports": "Takes multiple kraken-style reports and combines them into a single report file", "strvctvre_strvctvre": "a structural variant classifier for exonic deletions and duplications", "pindel_pindel": "Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and"}}, "target": "pindel_pindel", "target_idx": 4}
{"id": "noul_deprecated_dsl1_set_keyword_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_seqkit_seq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...) (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "seqkit_seq": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "rtgtools_rocplot": "Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI is", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}}, "target": "seqkit_seq", "target_idx": 1}
{"id": "field_constraint_bai_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "mod_hmmer_eslalimask_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mask multiple sequence alignments (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_stats_samtools": null, "picard_bedtointervallist": null, "hmmer_eslalimask": null, "hmmer_hmmbuild": null, "hmmer_eslsfetch": null}}, "target": "hmmer_eslalimask", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_4_1", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates?", "criteria": {"sample,fastq_1,image": null, "sample,bam": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "mod_seqtk_seq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Common transformation operations on FASTA or FASTQ files. (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_filterbyname": "Filter out sequences by sequence header name(s)", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "mmseqs_makepaddedseqdb": "Create an MMseqs padded database from an existing MMseqs database", "cellranger_mkvdjref": "Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref co", "seqtk_seq": "Common transformation operations on FASTA or FASTQ files."}}, "target": "seqtk_seq", "target_idx": 4}
{"id": "schema_std_genomicrelatedness_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomicrelatedness", "assay": "genomicrelatedness pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/genomicrelatedness (Bioinformatics pipeline for estimating genetic relatedness f)?", "criteria": {"sample,fastq_1,fastq_2,replicate,antibody": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "sample,fastq_1,fastq_2,bam,cram", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_2_5", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null, "sample,bam": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "mod_agat_convertspgxf2gxf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"varlociraptor/preprocess": null, "abacas": null, "geoquery/getgeo": null, "abyss/abysspe": null, "agat/convertspgxf2gxf": null}}, "target": "agat/convertspgxf2gxf", "target_idx": 4}
{"id": "resource_busco_generateplot_1", "category": "resource_profiling", "state": {"process": "BUSCO_GENERATEPLOT", "tool": "busco/generateplot", "description": "BUSCO plot generation tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_GENERATEPLOT (BUSCO plot generation tool) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_stringtie_stringtie_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transcript assembly and quantification for RNA-Se (tools: stringtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "ensemblvep/vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`.", "bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "evigene/tr2aacds": "Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly", "stringtie/stringtie": "Transcript assembly and quantification for RNA-Se"}}, "target": "stringtie/stringtie", "target_idx": 4}
{"id": "mod_treerecs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Treerecs is an open-source (species- and gene-) tree reconciliation software distributed under the GNU AGPL licence. It can correct, rearrange and (re-)root gene trees with regard to a given species tree. It was designed to be both efficient and easy to install and to use. (tools: treerecs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/tx2gene": null, "treerecs": null, "snpsift/annmemcreate": null, "plink/bcf": null, "sentieon/staralign": null}}, "target": "treerecs", "target_idx": 1}
{"id": "mod_gatk4_printsvevidence_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file containing the location of and orientation of read pairs marked as discordant, and a file containing the clipping location of all soft clipped reads and the orientation of the clipping. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/printsvevidence": "WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end an", "bam_variant_calling_sort_freebayes_bcftools": "Call variants using freebayes, then sort and index", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "deeptools/bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig "}}, "target": "gatk4/printsvevidence", "target_idx": 0}
{"id": "mod_multiqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregate results from bioinformatics analyses across many samples into a single report (tools: multiqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods.", "multiqc": "Aggregate results from bioinformatics analyses across many samples into a single report", "bftools_showinf": "Extract OME xml data from OME-tif", "differential_functional_enrichment": "Run functional analysis on differential abundance analysis output", "krakenuniq_download": "Download KrakenUniq databases and related fles"}}, "target": "multiqc", "target_idx": 1}
{"id": "noul_channel_mix_operator_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnafusion --input samplesheet.csv (Assay: RNA gene fusion detection (Arriba, STAR-Fusion))", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_freyja_demix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: specify the relative abundance of each known haplotype (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja/boot": null, "bedgovcf": null, "concoct/extractfastabins": null, "freyja/demix": null, "custom/tx2gene": null}}, "target": "freyja/demix", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_0_3", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "mod_gt_suffixerator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes enhanced suffix array using GenomeTools gt-suffixerator utility (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "gt/suffixerator": "Computes enhanced suffix array using GenomeTools gt-suffixerator utility", "fusionreport/download": "Build DB for fusionreport", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "yara/mapper": "Align reads to a reference genome using YARA"}}, "target": "gt/suffixerator", "target_idx": 1}
{"id": "intent_build_pipeline_21", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "prepare_data": null, "ask_question": null, "build_pipeline": null}}, "target": "build_pipeline", "target_idx": 3}
{"id": "resource_bakta_baktadbdownload_5", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTADBDOWNLOAD", "tool": "bakta/baktadbdownload", "description": "Downloads BAKTA database from Zenodo"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTADBDOWNLOAD (Downloads BAKTA database from Zenodo) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_damageprofiler_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage (tools: damageprofiler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"damageprofiler": null, "pydamage/analyze": null, "stardist": null, "authentict/deam2cont": null, "bakta/baktadbdownload": null}}, "target": "damageprofiler", "target_idx": 0}
{"id": "intent_ask_question_14", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_lofreq_somatic_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are available (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"getorganelle/config": "Downloads databases needed for running getorganelle", "lofreq/somatic": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl", "integronfinder": "Detect integrons in DNA sequences", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "atlas/call": "generate VCF file from a BAM file using various calling methods"}}, "target": "lofreq/somatic", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Longitudinal cancer monitoring across multiple timepoints. Input files: Serial plasma cfDNA and biopsy FASTQs across treatment intervals.", "question": {"type": "choice", "instructions": "Which columns are standard for Longitudinal cancer monitoring across multiple timepoints input samplesheet?", "criteria": {"patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_0_4", "category": "samplesheet_schema", "state": {"technology": "Spatial In Situ", "workflow_entry": "INPUT_CHECK", "library_inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "field_constraint_sample_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "format: file-path": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "mod_motus_profile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic meta-omics profiling using universal marker genes (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge/centrifuge": "Classifies metagenomic sequence data", "motus/profile": "Taxonomic meta-omics profiling using universal marker genes", "kmcp/search": "Search sequences against database", "haplogrep2/classify": "classification into haplogroups", "legsta": "Typing of clinical and environmental isolates of Legionella pneumophila"}}, "target": "motus/profile", "target_idx": 1}
{"id": "mod_sentieon_bwamem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using Sentieon's BWA MEM (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "minibwa/map": "Align fastq reads to a fasta reference using minibwa", "bwamem3/mem": "Align fastq reads to a fasta reference using bwa-mem3", "spaceranger/mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command"}}, "target": "sentieon/bwamem", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/smrnaseq --input samplesheet.csv (Assay: Small RNA / miRNA sequencing)", "question": {"type": "choice", "instructions": "Which columns are standard for Small RNA / miRNA sequencing input samplesheet?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "field_constraint_status_1_2", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_shigeifinder_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine Shigella serotype from assemblies or Illumina paired-end reads (tools: shigeifinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/getref": "Download and prepare database for Ariba analysis", "regenie/step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions", "hifitrimmer/filterbam": "Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLA", "shigeifinder": "Determine Shigella serotype from assemblies or Illumina paired-end reads", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with"}}, "target": "shigeifinder", "target_idx": 3}
{"id": "mod_ashlar_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Alignment by Simultaneous Harmonization of Layer/Adjacency Registration (tools: ashlar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins", "hmmcopy/gccounter": "gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta", "meningotype": "Serotyping of Neisseria meningitidis assemblies", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "ashlar", "target_idx": 4}
{"id": "mod_gatk4_annotateintervals_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates intervals with GC content, mappability, and segmental-duplication content (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "macrel_contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid", "atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "macs2_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "gatk4_annotateintervals", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_11", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_agat_convertspgff2tsv_2", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2TSV", "tool": "agat/convertspgff2tsv", "description": "Converts a GFF/GTF file into a TSV file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2TSV (Converts a GFF/GTF file into a TSV file) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_2_0", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "PBMM2_ALIGN", "library_inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "mod_wisecondorx_newref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a new reference using healthy reference samples (tools: wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/collectinsertsizemetrics": null, "hisat3n/align": null, "arriba/download": null, "biscuit/index": null, "wisecondorx/newref": null}}, "target": "wisecondorx/newref", "target_idx": 4}
{"id": "core_tool_star_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Splice-aware alignment of paired-end RNA-seq reads against human genome GRCh38 generating coordinate-sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bwa_mem": null, "bowtie2": null, "salmon": null, "star": null, "minimap2": null}}, "target": "star", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_47", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "intent_build_pipeline_12", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "build_pipeline", "target_idx": 0}
{"id": "mod_snpsift_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits/Joins VCF(s) file into chromosomes (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_pluginsplit": "Split VCF by sample, creating single- or multi-sample VCFs.", "bedtools_split": "Split BED files into several smaller BED files", "fgumi_simplexmetrics": "Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data", "bcftools_index": "Index VCF tools", "snpsift_split": "Splits/Joins VCF(s) file into chromosomes"}}, "target": "snpsift_split", "target_idx": 4}
{"id": "schema_std_airrflow_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/airrflow. Description: B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/airrflow.", "criteria": {"sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,tools,file,index": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "sample_id,subject_id,species,pcr_target_locus,tissue", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Trio exome/genome sequencing (Proband, Mother, Father)", "data_format": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs with pedigree relationships and affected status?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_phenoimager2mc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Formatting PhenoImager TIFF output files into stacked and normalized OME-TIFF files per cycle, compatible as ASHLAR and MCMICRO input. (tools: phenoimager2mc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"basicpy": null, "circexplorer2_parse": null, "tidk_search": null, "phenoimager2mc": null, "baysor_run": null}}, "target": "phenoimager2mc", "target_idx": 3}
{"id": "noul_process_conditional_execution_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fgumi_correct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "vizgenpostprocessing_compiletilesegmentation": "The module compiles segmentation tiles using Vizgen's post-processing tool.", "fgumi_codec": "Call CODEC consensus reads from a UMI-grouped BAM with fgumi", "fgumi_dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "fgumi_correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi"}}, "target": "fgumi_correct", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_1_20", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_5_5", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "template": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/pacvar, determine the input samplesheet column structure for: PacBio HiFi unaligned BAM variant calling.", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_8", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "schema_std_marsseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/marsseq", "description": "MARS-seq v2 pre-processing pipeline with velocity", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/marsseq?", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,antibody,control": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "fastq_1,fastq_2,batch,amp_batches,seq_batches", "target_idx": 2}
{"id": "mod_kleborate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species complex (KpSC). (tools: kleborate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "mash_screen": "Screens query sequences against large sequence databases", "rtgtools_bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "kleborate": "Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species"}}, "target": "kleborate", "target_idx": 4}
{"id": "mod_bwa_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA index for reference genome (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plotsr": "Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes.", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "ilastik/multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "biscuit/index": "Indexes a reference genome for use with Biscuit", "bwa/index": "Create BWA index for reference genome"}}, "target": "bwa/index", "target_idx": 4}
{"id": "mod_seqtk_rename_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rename sequence names in FASTQ or FASTA files. (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqtk_rename": "Rename sequence names in FASTQ or FASTA files.", "fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "sentieon_wgsmetrics": "Collects whole genome quality metrics from a bam file", "seqtk_mergepe": "Interleave pair-end reads from FastQ files", "seqtk_subseq": "Select only sequences that match the filtering condition"}}, "target": "seqtk_rename", "target_idx": 0}
{"id": "samplesheet_arch_riboseq_profiling_4_3", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "template": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end ribosome protected RNA fragments (RPFs) with strandedness?", "criteria": {"sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_1_5", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "template": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,host_fasta": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_49", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_5_5", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Tumor-only somatic variant calling without matched normal.", "criteria": {"patient,normal,tumor": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_file_pairing_in_channel_tuples_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "schema_std_viralrecon_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/viralrecon. Description: Assembly and intrahost/low-frequency variant calling for viral samples.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/viralrecon.", "criteria": {"id,path": null, "sample,fastq_1,fastq_2,strandedness,type": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1,fastq_2,barcode": null}}, "target": "sample,fastq_1,fastq_2,barcode", "target_idx": 3}
{"id": "mod_snpsift_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate a VCF file with another VCF file (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools_filter": "Filters VCF files", "bcftools_concat": "Concatenate VCF files", "panacus_visualize": "Create visualizations from a tsv coverage histogram created with panacus.", "snpsift_annotate": "Annotate a VCF file with another VCF file"}}, "target": "snpsift_annotate", "target_idx": 4}
{"id": "noul_executor_support_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_plink2_vcf2bgen_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert from VCF file to BGEN file version 1.2 format preserving dosages. (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/vcf2bgen": "Convert from VCF file to BGEN file version 1.2 format preserving dosages.", "vuegen": "The VueGen nf-core module is designed to automate report generation from outputs produced by other modules, su", "plink2/filter": "Filters plink bfiles or pfiles with filters such as maf or var", "conifer": "Calculate confidence scores from Kraken2 output", "plink2/het": "Calculate Inbreeding data with plink2"}}, "target": "plink2/vcf2bgen", "target_idx": 0}
{"id": "mod_blat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a sequence subject (tools: blat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/dict": null, "sratools/fasterqdump": null, "nucmer": null, "agat/convertgff2bed": null, "blat": null}}, "target": "blat", "target_idx": 4}
{"id": "mod_khmer_uniquekmers_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more (tools: khmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "fastk_fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "khmer_normalizebymedian": "Module that calls normalize-by-median.py from khmer. The module can take a mix of paired end (interleaved) and", "khmer_uniquekmers": "In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more"}}, "target": "khmer_uniquekmers", "target_idx": 4}
{"id": "mod_fastq_preprocess_seqkit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that preprocesses FASTQ files (tools: fastq_preprocess_seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/run": "Query input FASTQs against Ariba formatted databases", "dastool/fastatocontig2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "fastq_preprocess_seqkit": "Subworkflow that preprocesses FASTQ files", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "utils_nextflow_pipeline": "Subworkflow with functionality that may be useful for any Nextflow pipeline"}}, "target": "fastq_preprocess_seqkit", "target_idx": 2}
{"id": "mod_hostile_fetch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads required reference genomes for Hostile (tools: hostile)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hostile/clean": "Removes host reads from short- and long-read FASTQ sequencing files", "deacon/indexdiff": "Subtract minimizers in deacon index (or fasta file) from another index (A - B)", "propr/propr": "Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coeff", "hostile/fetch": "Downloads required reference genomes for Hostile", "rclone/copy": "Copy files or directories between local and/or remote storage using Rclone"}}, "target": "hostile/fetch", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_41", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_ariba_run_2", "category": "resource_profiling", "state": {"process": "ARIBA_RUN", "tool": "ariba/run", "description": "Query input FASTQs against Ariba formatted databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_RUN (Query input FASTQs against Ariba formatted databases) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bedtools_coverage_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COVERAGE", "tool": "bedtools/coverage", "description": "computes both the depth and breadth of coverage of features in file B on the features in file A"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COVERAGE (computes both the depth and breadth of coverage of features in file B on the fea) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_confusing_combine_with_mix_semantics_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_argnorm_4", "category": "resource_profiling", "state": {"process": "ARGNORM", "tool": "argnorm", "description": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARGNORM (Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed b) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_parabricks_dbsnp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"admixture": null, "parabricks_dbsnp": null, "annotsv_annotsv": null, "genometester4_glistmaker": null, "atlasgeneannotationmanipulation_gtf2featureannotation": null}}, "target": "parabricks_dbsnp", "target_idx": 1}
{"id": "mod_seqkit_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: simple statistics of FASTA/Q files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/stats": "simple statistics of FASTA/Q files", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "seqkit/grep": "Select sequences from a large file based on name/ID", "seqkit/pair": "match up paired-end reads from two fastq files", "slimfastq": "Fast, efficient, lossless compression of FASTQ files."}}, "target": "seqkit/stats", "target_idx": 0}
{"id": "pipe_all101_references_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: nf-core/references is a bioinformatics pipeline that build references, for multiple use cases. Topics: genome, references, reproducibility. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]"}}, "target": "references", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_2_5", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "schema_std_radseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/radseq", "assay": "radseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/radseq (Variant-calling pipeline for Restriction site-associated DNA)?", "criteria": {"sample_id,mapped,index,file_type": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,fastq_1,fastq_2,barcode": null, "sample,fastq_1,fastq_2,umi_barcodes": null}}, "target": "sample,fastq_1,fastq_2,umi_barcodes", "target_idx": 3}
{"id": "mod_odgi_draw_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Draw previously-determined 2D layouts of the graph with diverse annotations. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi/draw": null, "odgi/unchop": null, "odgi/build": null, "tiff_segmentation_vpt": null, "lofreq/viterbi": null}}, "target": "odgi/draw", "target_idx": 0}
{"id": "mod_helitronscanner_scan_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes (tools: helitronscanner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"taxonkit/name2taxid": "Convert taxon names to TaxIds", "ea-utils/gtf2bed": "Convert a GTF/GFF annotation file to BED12 format", "helitronscanner/scan": "HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "helitronscanner/scan", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_37", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_kaiju_mergeoutputs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge two tab-separated output files of Kaiju and Kraken in the column format (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_extractfrompdb": null, "kaiju_mergeoutputs": null, "centrifuge_centrifuge": null, "haplogrep2_classify": null, "dia_proteomics_analysis": null}}, "target": "kaiju_mergeoutputs", "target_idx": 1}
{"id": "mod_aardvark_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to evaluate and merge multiple variant calls into a consensus VCF. (tools: aardvark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "ivar/consensus": "Generate a consensus sequence from a BAM file using iVar", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "atlas/call": "generate VCF file from a BAM file using various calling methods", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris"}}, "target": "aardvark/merge", "target_idx": 2}
{"id": "noul_invalid_process_communication_via_globals_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_art_illumina_5", "category": "resource_profiling", "state": {"process": "ART_ILLUMINA", "tool": "art/illumina", "description": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ART_ILLUMINA (Simulation tool to generate synthetic Illumina next-generation sequencing reads) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_4_4", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs with pedigree relationships and affected status?", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_6_5", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic cancer variant calling with tumor-normal pairs input samplesheet?", "criteria": {"patient,sample,status,bam,bai": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_annotsv_annotsv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotation and Ranking of Structural Variation (tools: annotsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dastool_dastool": null, "annotsv_installannotations": null, "agat_spflagshortintrons": null, "annotsv_annotsv": null, "htsnimtools_vcfcheck": null}}, "target": "annotsv_annotsv", "target_idx": 3}
{"id": "mod_mirtrace_qc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool for quality control and tracing taxonomic origins of microRNA sequencing data (tools: mirtrace)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA", "mirtrace_qc": "A tool for quality control and tracing taxonomic origins of microRNA sequencing data", "seqcluster_collapse": "Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file.", "trimmomatic": "Performs quality and adapter trimming on paired end and single end reads"}}, "target": "mirtrace_qc", "target_idx": 2}
{"id": "pipe_core10_rnaseq_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Total RNA-seq with ribosomal RNA depletion for bacterial gene expression profiling and transcriptome quantification.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)"}}, "target": "rnaseq", "target_idx": 0}
{"id": "resource_bamclipper_3", "category": "resource_profiling", "state": {"process": "BAMCLIPPER", "tool": "bamclipper", "description": "This module is used to clip primer sequences from your alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCLIPPER (This module is used to clip primer sequences from your alignments.) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_nanoq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Nanoq implements ultra-fast read filters and summary reports for high-throughput nanopore reads. (tools: nanoq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nanoq": "Nanoq implements ultra-fast read filters and summary reports for high-throughput nanopore reads.", "xeniumranger/importsegmentation": "The xeniumranger importsegmentation module runs `xeniumranger import-segmentation`\nto recompute Xenium Onboard", "rtgtools/bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "biscuit/biscuitblaster": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit", "mafft/align": "Multiple sequence alignment using MAFFT"}}, "target": "nanoq", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_32", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_openms_idmerger_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges several idXML files into one idXML file. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja/variants": "call variant and sequencing depth information of the variant", "bbmap/sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "openms/idmerger": "Merges several idXML files into one idXML file.", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "biobambam/bammerge": "Merge a list of sorted bam files"}}, "target": "openms/idmerger", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_24", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_maxbin2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MaxBin is a software that is capable of clustering metagenomic contigs (tools: maxbin2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"maxbin2": null, "biscuit_vcf2bed": null, "bracken_combinebrackenoutputs": null, "custom_getchromsizes": null, "bracken_bracken": null}}, "target": "maxbin2", "target_idx": 0}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_5_4", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking.", "criteria": {"sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_dupblaster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline in the alignment pipe (aligner | dupblaster | sort) rather than as a standalone step (tools: dupblaster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools/stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "dupblaster": "Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline ", "modkit/bedmethyltobigwig": "Convert a bedMethyl file to bigWig format using modkit", "parabricks/minimap2": "NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference da", "fgumi/dedup": "Mark or remove PCR duplicates using UMI information with fgumi"}}, "target": "dupblaster", "target_idx": 1}
{"id": "mod_snpsift_dbnsfp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The dbNSFP is an integrated database of functional predictions from multiple algorithms (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"panacus_histgrowth": null, "aardvark_compare": null, "snpsift_dbnsfp": null, "vg_deconstruct": null, "atlas_call": null}}, "target": "snpsift_dbnsfp", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_17", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_oarfish_readmode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Map raw reads to the transcriptome internally with the built-in rammap mapper, then quantify. (tools: oarfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": null, "gem3/gem3mapper": null, "bamtofastq10x": null, "binette": null, "oarfish/readmode": null}}, "target": "oarfish/readmode", "target_idx": 4}
{"id": "mod_metacache_query_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metacache query command for taxonomic classification (tools: metacache)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "metacache/query": "Metacache query command for taxonomic classification", "wget": "The non-interactive network downloader", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "meryl/histogram": "A genomic k-mer counter (and sequence utility) with nice features."}}, "target": "metacache/query", "target_idx": 1}
{"id": "noul_retry_errorstrategy_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_fastq_align_chromap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with samtools (tools: fastq_align_chromap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "fastq_align_bowtie2": "Align reads to a reference genome using bowtie2 then sort with samtools", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "coverm_contig": "Map reads to contigs and estimate coverage", "fastq_align_chromap": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with s"}}, "target": "fastq_align_chromap", "target_idx": 4}
{"id": "local_subworkflow_daisribosome_2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for DAISRIBOSOME (dais).", "criteria": {"Leave them out": null, "Use nf-core subworkflow daisribosome": null, "Keep the modules in the main workflow": null, "Local subworkflow DAISRIBOSOME": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 3}
{"id": "mod_gemmi_cif2json_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert macromolecular structure files from mmCIF format to JSON format using gemmi. (tools: gemmi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gemmi/cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "foldcomp/compress": "Efficient compression tool for protein structures", "tmb/pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "foldmason/msa2lddtreport": "Renders a visualization report using foldmason"}}, "target": "gemmi/cif2json", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_3", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_busco_busco_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Benchmarking Universal Single Copy Orthologs (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnaqc": "Quality control of copy number data from bulk WGS assays", "busco_busco": "Benchmarking Universal Single Copy Orthologs", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "hicexplorer_hicpca": "Computes PCA eigenvectors for a Hi-C matrix.", "whamg": "The wham suite consists of two programs, wham and whamg. wham, the original tool, is a very sensitive method w"}}, "target": "busco_busco", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_7", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_bbmap_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align short or PacBio reads to a reference genome using BBMap (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "picard/createsequencedictionary": "Creates a sequence dictionary for a reference sequence.", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "seqcluster/collapse": "Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file."}}, "target": "bbmap/align", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_wgs_7_2", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "HIFIADAPTERFILT", "library_inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for Fungal ITS1/ITS2 marker gene amplicon surveillance. Input files: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: Fungal ITS1/ITS2 marker gene amplicon surveillance.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,unite_fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bwa_aln_1", "category": "resource_profiling", "state": {"process": "BWA_ALN", "tool": "bwa/aln", "description": "Find SA coordinates of the input reads for bwa short-read mapping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_ALN (Find SA coordinates of the input reads for bwa short-read mapping) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_high", "target_idx": 2}
{"id": "mod_fasta_build_add_kraken2_bracken_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KRAKEN2 and BRACKEN build custom database subworkflow (tools: fasta_build_add_kraken2_bracken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/collecthsmetrics": "Collects hybrid-selection (HS) metrics for a SAM or BAM file.", "fasta_build_add_kraken2_bracken": "KRAKEN2 and BRACKEN build custom database subworkflow", "bam_variant_calling_sort_freebayes_bcftools": "Call variants using freebayes, then sort and index", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "fasta_build_add_kraken2_bracken", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Single-end Oxford Nanopore direct RNA. Input files: Single fastq per sample.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_2_27", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_trinity_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembles a de novo transcriptome from RNAseq reads (tools: trinity)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "antismash/antismashlite": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "trinity": "Assembles a de novo transcriptome from RNAseq reads", "bedtools/shuffle": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a gen"}}, "target": "trinity", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_38", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_3_0", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-lane Illumina sequencing run of clinical samples with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_named_output_channel_access_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/raredisease) for Downstream functional annotation of pre-called VCF files. Input files: BGZF-compressed VCF files with companion Tabix index files.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bed": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "noul_deprecated_file_output_syntax_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_0_0", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities", "pipeline": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "mod_plink_ld_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LD analysis in PLINK examines genetic variant associations within populations (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_ld": "LD analysis in PLINK examines genetic variant associations within populations", "artic_minion": "Run the alignment/variant-call/consensus logic of the artic pipeline", "ncbitools_vecscreen": "NCBI tool for detecting vector contamination in nucleic acid sequences. This tool is older than NCBI's FCS-ada", "gcta_bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "gcta_adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`"}}, "target": "plink_ld", "target_idx": 0}
{"id": "mod_rsem_calculateexpression_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate expression with RSEM (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rsem/calculateexpression": null, "tximeta/tximport": null, "sentieon/rsempreparereference": null, "hasheddrops": null, "ariba/getref": null}}, "target": "rsem/calculateexpression", "target_idx": 0}
{"id": "intent_debug_error_14", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "mod_muse_sump_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes tier-based cutoffs from a sample-specific error model which is generated by muse/call and reports the finalized variants (tools: MuSE)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/consensus": "Compresses VCF files", "last/lastdb": "Prepare sequences for subsequent alignment with lastal.", "atlas/call": "generate VCF file from a BAM file using various calling methods", "hisat2/extractsplicesites": "Extracts splicing sites from a gtf files", "muse/sump": "Computes tier-based cutoffs from a sample-specific error model which is generated by muse/call and reports the"}}, "target": "muse/sump", "target_idx": 4}
{"id": "mod_icountmini_peaks_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs iCount peaks on a BED file of crosslinks (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju_mkfmi": "Make Kaiju FMI-index file from a protein FASTA file", "rgi_cardannotation": "Preprocess the CARD database for RGI to predict antibiotic resistance from protein or nucleotide data", "icountmini_summary": "Report proportion of cross-link events/sites on each region type.", "icountmini_peaks": "Runs iCount peaks on a BED file of crosslinks", "peka": "Runs PEKA CLIP peak k-mer analysis"}}, "target": "icountmini_peaks", "target_idx": 3}
{"id": "intent_build_pipeline_19", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "prepare_data": null, "build_pipeline": null, "ask_question": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "samplesheet_arch_vcf_annotation_pipeline_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Downstream functional annotation of pre-called VCF files)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Downstream functional annotation of pre-called VCF files.", "criteria": {"sample,vcf": null, "sample,vcf,tbi": null, "sample,bam,bai": null, "sample,bed": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "field_constraint_expected_cells_1_5", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "mod_kmergenie_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KmerGenie estimates the best k-mer length for genome de novo assembly (tools: kmergenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio/sortbam": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate, queryname, random, and rando", "ngsbits/samplegender": "Determines the gender of a sample from the BAM/CRAM file.", "kmergenie": "KmerGenie estimates the best k-mer length for genome de novo assembly", "ganon/classify": "Classify FASTQ files against ganon database", "fastk/fastk": "A fast K-mer counter for high-fidelity shotgun datasets"}}, "target": "kmergenie", "target_idx": 2}
{"id": "resource_binette_4", "category": "resource_profiling", "state": {"process": "BINETTE", "tool": "binette", "description": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BINETTE (A fast and accurate binning refinement tool to construct high quality MAGs from ) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_saltshaker_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mtDNA deletion and duplication plotting downstream of mitosalt (tools: saltshaker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep2/classify": "classification into haplogroups", "saltshaker/plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "genmod/models": "annotate models of inheritance", "eklipse": "tool for detection and quantification of large mtDNA rearrangements.", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl"}}, "target": "saltshaker/plot", "target_idx": 1}
{"id": "pipe_all101_metapep_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze From metagenomes to epitopes and beyond. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": "Read-based functional profiling of microbiome sequencing data", "metapep": "From metagenomes to epitopes and beyond", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]"}}, "target": "metapep", "target_idx": 1}
{"id": "samplesheet_arch_scrna_multiome_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for 10x Multiome single-cell joint RNA and ATAC chromatin. Input files: Paired FASTQs for both GEX and ATAC modalities per nucleus.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,matrix": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "pipe_all101_crisprseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`).. Topics: crispr, crispr-analysis, crispr-cas, ngs. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"eager": null, "mag": null, "viralmetagenome": null, "pangenome": null, "fetchngs": null, "crisprseq": null, "dualrnaseq": null, "fastquorum": null}}, "target": "crisprseq", "target_idx": 5}
{"id": "mod_agat_convertbed2gff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes a bed12 file and converts to a GFF3 file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "agat_convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "unzip": "Unzip ZIP archive files"}}, "target": "agat_convertbed2gff", "target_idx": 1}
{"id": "mod_centrifuger_centrifuger_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classification of sequencing reads using the Centrifuger tool. (tools: centrifuger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuger/centrifuger": "Classification of sequencing reads using the Centrifuger tool.", "juicertools/pre": "Create a multi-resolution .hic contact matrix for analysis with Juicer", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "hmmcopy/generatemap": "Perl script (generateMap.pl) generates the mappability of a genome given a certain size of reads, for input to", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD"}}, "target": "centrifuger/centrifuger", "target_idx": 0}
{"id": "field_constraint_fastq_2_1_12", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry). Input files: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry).", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "resource_artic_guppyplex_4", "category": "resource_profiling", "state": {"process": "ARTIC_GUPPYPLEX", "tool": "artic/guppyplex", "description": "Aggregates fastq files with demultiplexed reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_GUPPYPLEX (Aggregates fastq files with demultiplexed reads) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_1_4", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "local_subworkflow_prepontreads_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should PREPONTREADS (porechop, nanoplot) be built?", "criteria": {"Local subworkflow PREPONTREADS": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow prepontreads": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_2_0", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "INPUT_CHECK", "library_inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_seqsero2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Salmonella serotype prediction from reads and assemblies (tools: seqsero2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqsero2": null, "presto/filterseq": null, "purecn/coverage": null, "amrfinderplus/update": null, "abritamr/run": null}}, "target": "seqsero2", "target_idx": 0}
{"id": "mod_bam_tumor_only_somatic_variant_calling_gatk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform variant calling on a single tumor sample using mutect2 tumor only mode.\nRun the input bam file through getpileupsummarries and then calculatecontaminationto get the contamination and segmentation tables.\nFilter the mutect2 output vcf using filtermutectcalls and the contamination & segmentation tables for additional filtering. (tools: bam_tumor_only_somatic_variant_calling_gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "bam_tumor_only_somatic_variant_calling_gatk": "Perform variant calling on a single tumor sample using mutect2 tumor only mode.\nRun the input bam file through", "gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "holodeck_mutate": "Generate a VCF of random mutations from a reference genome with holodeck", "fastcov": "Generate a coverage plot from one or more bam files"}}, "target": "bam_tumor_only_somatic_variant_calling_gatk", "target_idx": 1}
{"id": "noul_publishdir_directive_usage_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_2_5", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "pipe_all101_cutandrun_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for cutandrun. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]"}}, "target": "cutandrun", "target_idx": 2}
{"id": "mod_sushie_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to perform multi-ancestry SNP fine-mapping on molecular data (tools: sushie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_runl0": "Run one REGENIE step 1 level-0 job from a split master file", "trycycler_cluster": "Cluster contigs from multiple assemblies by similarity", "sushie": "Software to perform multi-ancestry SNP fine-mapping on molecular data", "anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "admixture": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datas"}}, "target": "sushie", "target_idx": 2}
{"id": "mod_crispresso2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A software pipeline for the analysis of genome editing outcomes from deep sequencing data (tools: crispresso2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr_normalize": null, "fgbio_collectduplexseqmetrics": null, "crispresso2": null, "mtmalign_align": null, "mageck_mle": null}}, "target": "crispresso2", "target_idx": 2}
{"id": "resource_bam2fastx_bam2fastq_4", "category": "resource_profiling", "state": {"process": "BAM2FASTX_BAM2FASTQ", "tool": "bam2fastx/bam2fastq", "description": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAM2FASTX_BAM2FASTQ (Conversion of PacBio BAM files into gzipped fastq files, including splitting of ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_viralrecon_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Assembly and intrahost/low-frequency variant calling for viral samples. Topics: amplicon, artic, assembly, covid-19, covid19, illumina. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]"}}, "target": "viralrecon", "target_idx": 3}
{"id": "mod_scanpy_pca_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "huggingface/download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "meningotype": "Serotyping of Neisseria meningitidis assemblies", "plink2/pca": "Perform PCA analysis using PLINK", "hicexplorer/hicpca": "Computes PCA eigenvectors for a Hi-C matrix."}}, "target": "scanpy/pca", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_6_0", "category": "samplesheet_schema", "state": {"technology": "Mass Spectrometry", "workflow_entry": "INPUT_CHECK", "library_inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns are standard for Data-Independent Acquisition (DIA) quantitative mass spectrometry input samplesheet?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null, "sample,mzml": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "mod_aardvark_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to evaluate and merge multiple variant calls into a consensus VCF. (tools: aardvark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_consensus": "Compresses VCF files", "hamronization_rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification.", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools_filter": "Filters VCF files", "rpbp_estimateorfbayesfactors": "Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian "}}, "target": "aardvark_merge", "target_idx": 2}
{"id": "mod_tinc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TINC is a package to determine the contamination of tumour DNA in a matched normal sample. The approach uses evolutionary theory applied to read counts data from whole-genome sequencing assays. (tools: tinc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spmergeannotations": null, "tinc": null, "agat_spfilterbyorfsize": null, "gget_gget": null, "telescope_assign": null}}, "target": "tinc", "target_idx": 1}
{"id": "resource_amulety_embed_4", "category": "resource_profiling", "state": {"process": "AMULETY_EMBED", "tool": "amulety/embed", "description": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_EMBED (A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_19", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_gcta_makegrm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute a whole dense GRM with GCTA (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/preprocessintervals": null, "gcta/makegrm": null, "gcta/bivariatereml": null, "abricate/summary": null, "gcta/fastgwa": null}}, "target": "gcta/makegrm", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_2_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_msisensorpro_scan_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing data. It accepts the whole genome sequencing, whole exome sequencing and target region (panel) sequencing data as input (tools: msisensorpro)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro/baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "ncbitools/vecscreen": "NCBI tool for detecting vector contamination in nucleic acid sequences. This tool is older than NCBI's FCS-ada", "msisensorpro/pro": "MSIsensor-pro/pro is a tool used to evaluate MSI using single (tumor) sample sequencing data", "sentieon/varcal": "Module for Sentieons VarCal. The VarCal algorithm calculates the Variant Quality Score Recalibration (VQSR).\nV", "msisensorpro/scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d"}}, "target": "msisensorpro/scan", "target_idx": 4}
{"id": "resource_bwa_samse_2", "category": "resource_profiling", "state": {"process": "BWA_SAMSE", "tool": "bwa/samse", "description": "Convert bwa SA coordinate file to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMSE (Convert bwa SA coordinate file to SAM format) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "pipe_all101_atacseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for atac-seq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "atacseq", "target_idx": 5}
{"id": "mod_amrfinderplus_update_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify antimicrobial resistance in gene or protein sequences (tools: amrfinderplus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "odgi/squeeze": "Squeezes multiple graphs in ODGI format into the same file in ODGI format.", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "trimmomatic": "Performs quality and adapter trimming on paired end and single end reads"}}, "target": "amrfinderplus/update", "target_idx": 0}
{"id": "pipe_all101_createpanelrefs_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for createpanelrefs. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]"}}, "target": "createpanelrefs", "target_idx": 4}
{"id": "resource_abyss_abysspe_4", "category": "resource_profiling", "state": {"process": "ABYSS_ABYSSPE", "tool": "abyss/abysspe", "description": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABYSS_ABYSSPE (ABySS is a de novo sequence assembler intended for short paired-end reads and ge) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_arcane_filter_0", "category": "resource_profiling", "state": {"process": "ARCANE_FILTER", "tool": "arcane/filter", "description": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCANE_FILTER (Filter GTF annotations and genome sequence for alignment-free single-cell RNA-se) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_0", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bedtools_genomecov_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GENOMECOV", "tool": "bedtools/genomecov", "description": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., aligned sequences) for a given genome."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GENOMECOV (Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summarie) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_28", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_4_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads with library strandedness?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "pipe_core10_atacseq_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Chromatin accessibility profiling with hyperactive Tn5 transposase to map genome-wide open chromatin regions and nucleosome positioning.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "atacseq", "target_idx": 5}
{"id": "samplesheet_arch_cancer_somatic_bam_6_5", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic tumor-normal calling from pre-aligned BAM files input samplesheet?", "criteria": {"sample,vcf": null, "patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "schema_std_cutandrun_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/cutandrun. Description: Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/cutandrun.", "criteria": {"fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample,run,group,short_reads_1,short_reads_2": null}}, "target": "fastq_1,fastq_2,group,replicate,control", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_6_4", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery", "pipeline": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "Which columns are standard for RNA gene fusion detection (Arriba, STAR-Fusion) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fusion_bed": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_pbsv_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pbsv/call - PacBio structural variant (SV) calling and analysis tools (tools: pbsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xeniumranger_rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "pbsv_call": "pbsv/call - PacBio structural variant (SV) calling and analysis tools", "smoothxg": "Linearize and simplify variation graph in GFA format using blocked partial order alignment", "clair3": "Clair3 is a germline small variant caller for long-reads"}}, "target": "pbsv_call", "target_idx": 2}
{"id": "mod_methurator_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots results produced by methurator gtestimator. (tools: methurator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bismark_methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "crabs_import": "In-house generated or curated data can be imported into CRABS.", "methurator_plot": "Plots results produced by methurator gtestimator.", "vsearch_cluster": "Cluster sequences using a single-pass, greedy centroid-based clustering algorithm."}}, "target": "methurator_plot", "target_idx": 3}
{"id": "pipe_all101_cageseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags.. Topics: cage, cage-seq, cageseq-data, gene-expression, rna. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"riboseq": null, "rnaseq": null, "demo": null, "cageseq": null, "slamseq": null, "nanoseq": null, "bacass": null, "pangenome": null}}, "target": "cageseq", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Longitudinal cancer monitoring across multiple timepoints. Input files: Serial plasma cfDNA and biopsy FASTQs across treatment intervals.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "sample,timepoint,fastq": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_kat_hist_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a histogram of the number of distinct k-mers having a given frequency. (tools: kat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbmm2/align": "Alignment with PacBio's minimap2 frontend", "autocycler/combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "kat/hist": "Creates a histogram of the number of distinct k-mers having a given frequency.", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "ganon/classify": "Classify FASTQ files against ganon database"}}, "target": "kat/hist", "target_idx": 2}
{"id": "mod_diamond_makedb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a DIAMOND database (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/makedb": "Builds a DIAMOND database", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "plink/bcf": "Analyses binary variant call format (BCF) files using plink"}}, "target": "diamond/makedb", "target_idx": 0}
{"id": "pipe_all101_references_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: nf-core/references is a bioinformatics pipeline that build references, for multiple use cases. Topics: genome, references, reproducibility. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hlatyping": null, "genomeqc": null, "ribomsqc": null, "callingcards": null, "stableexpression": null, "rnaseq": null, "rangeland": null, "references": null, "variantbenchmarking": null, "oncoanalyser": null}}, "target": "references", "target_idx": 7}
{"id": "qc_adapt_ont_nanoplot_0_14", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "subworkflow_pkg_bam_stringtie_merge_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STRINGTIE_MERGE", "modules": ["stringtie/stringtie", "stringtie/merge"], "description": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a unified annotation."}, "question": {"type": "choice", "instructions": "How should BAM_STRINGTIE_MERGE (stringtie/stringtie, stringtie/merge) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_STRINGTIE_MERGE": null, "Use nf-core subworkflow bam_stringtie_merge": null}}, "target": "Use nf-core subworkflow bam_stringtie_merge", "target_idx": 3}
{"id": "resource_bedtools_nuc_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_NUC", "tool": "bedtools/nuc", "description": "Profiles the nucleotide content of intervals in a fasta file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_NUC (Profiles the nucleotide content of intervals in a fasta file.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_ngscheckmate_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_NGSCHECKMATE", "modules": ["ngscheckmate/fastq", "ngscheckmate/vafncm"], "description": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs."}, "question": {"type": "choice", "instructions": "How should FASTQ_NGSCHECKMATE (ngscheckmate/fastq, ngscheckmate/vafncm) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_ngscheckmate": null, "Local subworkflow FASTQ_NGSCHECKMATE": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_ngscheckmate", "target_idx": 1}
{"id": "mod_sambamba_flagstat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Outputs some statistics drawn from read flags. (tools: sambamba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sambamba/flagstat": "Outputs some statistics drawn from read flags.", "bamtools/stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "gt/stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "fastq_taxonomic_profile_metaphlan": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn", "mgikit/demultiplex": "Demultiplex MGI fastq files"}}, "target": "sambamba/flagstat", "target_idx": 0}
{"id": "intent_build_pipeline_10", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "build_pipeline", "target_idx": 3}
{"id": "field_constraint_sex_1_8", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "mod_samtools_cat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenate BAM or CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spmergeannotations": null, "biobambam/bammerge": null, "samtools/cat": null, "plasmidid": null, "mmseqs/taxonomy": null}}, "target": "samtools/cat", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_6_5", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns are standard for Small RNA / miRNA sequencing input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,mirna_id": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_5_3", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/diaproteomics, determine the input samplesheet column structure for: Data-Independent Acquisition (DIA) quantitative mass spectrometry.", "criteria": {"sample,mzml": null, "sample,raw_file,condition": null, "sample,fasta": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "mod_prokka_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Whole genome annotation of small genomes (bacterial, archeal, viral) (tools: prokka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "pbmm2/align": "Alignment with PacBio's minimap2 frontend", "prokka": "Whole genome annotation of small genomes (bacterial, archeal, viral)", "mmseqs/createtaxdb": "Adds taxonomy information to an existing MMseqs2 database", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "prokka", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_16", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_41", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "local_subworkflow_irma_1_5", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should this step (irma) be packaged: Iterative assembly step for influenza and coronavirus?", "criteria": {"Use nf-core subworkflow irma": null, "Leave them out": null, "Local subworkflow IRMA": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow IRMA", "target_idx": 2}
{"id": "mod_bcftools_plotvcfstats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots the output of bcftools stats (tools: plot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jvarkit/vcf2table": null, "custom/clustervisualization": null, "deeptmhmm": null, "bcftools/plotvcfstats": null, "custom/orfnormalise": null}}, "target": "bcftools/plotvcfstats", "target_idx": 3}
{"id": "core_tool_star_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Splice-aware alignment of paired-end RNA-seq reads against human genome GRCh38 generating coordinate-sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bowtie2": "Fast aligner for short reads", "minimap2": "Versatile pairwise aligner", "star": "Spliced read aligner for RNA-seq", "bwa_mem": "Burrows-Wheeler aligner for DNA", "salmon": "Transcript quantification from RNA-seq"}}, "target": "star", "target_idx": 2}
{"id": "resource_angsd_soapsnpcalibration_4", "category": "resource_profiling", "state": {"process": "ANGSD_SOAPSNPCALIBRATION", "tool": "angsd/soapsnpcalibration", "description": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_SOAPSNPCALIBRATION (Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality mat) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gatk4_haplotypecaller_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call germline SNPs and indels via local re-assembly of haplotypes (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/haplotypecaller": null, "gatk4/annotateintervals": null, "abacas": null, "cnvkit/access": null, "gatk4/asereadcounter": null}}, "target": "gatk4/haplotypecaller", "target_idx": 0}
{"id": "mod_jellyfish_dump_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dumps the results from a jellyfish binary file into a human readable format (tools: jellyfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "ganon/classify": "Classify FASTQ files against ganon database", "gnu/split": "Split a file into consecutive or interleaved sections", "jellyfish/dump": "Dumps the results from a jellyfish binary file into a human readable format", "fastk/histex": "A fast K-mer counter for high-fidelity shotgun datasets"}}, "target": "jellyfish/dump", "target_idx": 3}
{"id": "noul_undeclared_process_file_inputs_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cageseq) for CAGE-seq 5-prime capped transcript end sequencing. Input files: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,vcf": null, "sample,tss_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_4", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_40", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_aria2_0", "category": "resource_profiling", "state": {"process": "ARIA2", "tool": "aria2", "description": "CLI Download utility"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIA2 (CLI Download utility) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_bedtools_flank_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates two new flanking intervals for each interval in a BED/GFF/VCF file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_docounts_contamination_angsd": null, "pydamage_filter": null, "bedops_convert2bed": null, "bamtools_convert": null, "bedtools_flank": null}}, "target": "bedtools_flank", "target_idx": 4}
{"id": "mod_manta_somatic_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. (tools: manta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"manta/somatic": null, "find/concatenate": null, "bam_stats_mirna_mirtop": null, "controlfreec/freec2bed": null, "controlfreec/makegraph": null}}, "target": "manta/somatic", "target_idx": 0}
{"id": "mod_mafft_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multiple sequence alignment using MAFFT (tools: mafft)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xz/compress": "Compresses files with xz.", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "pypolca/run": "Short read polisher for long read assemblies", "mafft/align": "Multiple sequence alignment using MAFFT", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "mafft/align", "target_idx": 3}
{"id": "schema_std_ampliseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/ampliseq. Description: Amplicon sequencing analysis workflow using DADA2 and QIIME2.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/ampliseq.", "criteria": {"sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,type,level,msfile": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,fastq_1,fastq_2,sampleID,forwardReads", "target_idx": 0}
{"id": "core_tool_deepvariant_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Deep neural network-based variant caller transforming aligned reads into pileup tensor images for high-accuracy SNP/indel detection.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"freebayes": null, "deepvariant": null, "clair3": null, "varscan2": null, "gatk_haplotypecaller": null}}, "target": "deepvariant", "target_idx": 1}
{"id": "subworkflow_pkg_bam_stringtie_merge_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STRINGTIE_MERGE", "modules": ["stringtie/stringtie", "stringtie/merge"], "description": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a unified annotation."}, "question": {"type": "choice", "instructions": "How should BAM_STRINGTIE_MERGE (stringtie/stringtie, stringtie/merge) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_stringtie_merge": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_STRINGTIE_MERGE": null}}, "target": "Use nf-core subworkflow bam_stringtie_merge", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_43", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_samtools_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge BAM or CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_clustermetrics": null, "vcf_filter_bcftools_ensemblvep": null, "agat_spmergeannotations": null, "samtools_merge": null, "bedtools_merge": null}}, "target": "samtools_merge", "target_idx": 3}
{"id": "mod_purgedups_calcuts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate coverage cutoffs to determine when to purge duplicated sequence. (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"allelecounter": "Generates a count of coverage of alleles", "vcflib_vcfbreakmulti": "If multiple alleles are specified in a single record, break the record into several lines preserving allele-sp", "tcoffee_tcs": "Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just", "purgedups_calcuts": "Calculate coverage cutoffs to determine when to purge duplicated sequence.", "bbmap_bbnorm": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result i"}}, "target": "purgedups_calcuts", "target_idx": 3}
{"id": "mod_bedtools_intersect_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Allows one to screen for overlaps between two sets of genomic features. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast/blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "whamg": "The wham suite consists of two programs, wham and whamg. wham, the original tool, is a very sensitive method w", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "bedtools/intersect": "Allows one to screen for overlaps between two sets of genomic features.", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file"}}, "target": "bedtools/intersect", "target_idx": 3}
{"id": "schema_std_genomeassembler_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/genomeassembler. Description: Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/genomeassembler.", "criteria": {"id,fasta,sequence": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,group,ref_fasta,ref_gff,use_ref", "target_idx": 1}
{"id": "noul_workflow_completion_lifecycle_hook_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_hifiasm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Whole-genome assembly using PacBio HiFi reads (tools: hifiasm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie_align": "Align reads to a reference genome using bowtie", "gfastats": "A single fast and exhaustive tool for summary statistics and simultaneous *fa*\n(fasta, fastq, gfa [.gz]) genom", "purgedups_pbcstat": "Create read depth histogram and base-level read depth for an assembly based on pacbio data", "foldcomp_decompress": "Decompression tool for foldcomp compressed structures", "hifiasm": "Whole-genome assembly using PacBio HiFi reads"}}, "target": "hifiasm", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_2_25", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_4_1", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end oncology RNA-seq reads for chimeric transcript discovery?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fusion_bed": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "mod_gappa_examinegraft_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Grafts query sequences from phylogenetic placement on the reference tree (tools: gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gappa_examinegraft": "Grafts query sequences from phylogenetic placement on the reference tree", "clame": "binning of metagenomic sequences", "bedtools_sort": "Sorts a feature file by chromosome and other criteria.", "roary": "Calculate pan-genome from annotated bacterial assemblies in GFF3 format", "midas_run": "A tool to estimate bacterial species abundance"}}, "target": "gappa_examinegraft", "target_idx": 0}
{"id": "mod_sentieon_wgsmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects whole genome quality metrics from a bam file (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/wgsmetrics": "Collects whole genome quality metrics from a bam file", "fgumi/duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data", "gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "syri": "Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearran", "gatk4/calibratedragstrmodel": "estimates the parameters for the DRAGstr model"}}, "target": "sentieon/wgsmetrics", "target_idx": 0}
{"id": "noul_channel_collect_operator_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_default_empty_channel_behavior_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_bcl_demultiplex_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BCL_DEMULTIPLEX", "modules": ["bcl2fastq", "bclconvert", "multiqcsav"], "description": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq"}, "question": {"type": "choice", "instructions": "How should BCL_DEMULTIPLEX (bcl2fastq, bclconvert, multiqcsav) be structured in DSL2?", "criteria": {"Local subworkflow BCL_DEMULTIPLEX": null, "Use nf-core subworkflow bcl_demultiplex": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bcl_demultiplex", "target_idx": 1}
{"id": "mod_bacphlip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A bacteriophage lifestyle prediction tool (tools: bacphlip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pharokka/installdatabases": "Install databases necessary for Pharokka's functional analysis", "iphop/predict": "Predict phage host using iPHoP", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O", "bacphlip": "A bacteriophage lifestyle prediction tool", "hifiasm": "Whole-genome assembly using PacBio HiFi reads"}}, "target": "bacphlip", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_0_34", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_cellbender_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use CellBender to remove ambient RNA from single-cell RNA-seq data (tools: cellbender)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender_merge": null, "repeatmasker_repeatmasker": null, "cellranger_mkvdjref": null, "octopusv_plot": null, "anndata_getsize": null}}, "target": "cellbender_merge", "target_idx": 0}
{"id": "schema_std_readsimulator_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/readsimulator", "assay": "readsimulator pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/readsimulator (A pipeline to simulate sequencing reads, such as Amplicon, T)?", "criteria": {"sample,seed": null, "gene_name,alignment,tree,suite,tool": null, "sample,group,path,ref,method": null, "sample,fastq_1,fastq_2,bam,bai": null}}, "target": "sample,seed", "target_idx": 0}
{"id": "noul_module_metadata_propagation_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_bio2zarr_vcf2zarrexplode_4", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARREXPLODE", "tool": "bio2zarr/vcf2zarrexplode", "description": "Convert VCF(s) to intermediate columnar format (ICF)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARREXPLODE (Convert VCF(s) to intermediate columnar format (ICF)) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_quantify_pseudo_alignment_0", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_PSEUDO_ALIGNMENT", "modules": ["kallisto/quant", "quant_tximport_summarizedexperiment", "salmon/quant"], "description": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_PSEUDO_ALIGNMENT (kallisto/quant, quant_tximport_summarizedexperiment, salmon/quant) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow quantify_pseudo_alignment": null, "Leave them out": null, "Local subworkflow QUANTIFY_PSEUDO_ALIGNMENT": null}}, "target": "Use nf-core subworkflow quantify_pseudo_alignment", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_1_4", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Tumor-only somatic variant calling without matched normal?", "criteria": {"patient,normal,tumor": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_nanoseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Nanopore demultiplexing, QC and alignment pipeline. Topics: alignment, demultiplexing, nanopore, qc. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v"}}, "target": "nanoseq", "target_idx": 0}
{"id": "mod_odgi_unchop_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge unitigs into a single node preserving the node order. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi_unchop": "Merge unitigs into a single node preserving the node order.", "krakenuniq_build": "Download and build (custom) KrakenUniq databases", "odgi_layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "odgi_build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1.", "bowtie_build": "Create bowtie index for reference genome"}}, "target": "odgi_unchop", "target_idx": 0}
{"id": "mod_sentieon_haplotyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs Sentieon's haplotyper for germline variant calling. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/datametrics": "Collects multiple quality metrics from a bam file", "seqtk/sample": "Subsample reads from FASTQ files", "rhocall/annotate": "Markup VCF file using rho-calls.", "sentieon/bwaindex": "Create BWA index for reference genome", "sentieon/haplotyper": "Runs Sentieon's haplotyper for germline variant calling."}}, "target": "sentieon/haplotyper", "target_idx": 4}
{"id": "mod_odgi_layout_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and id-compacted. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi_unchop": "Merge unitigs into a single node preserving the node order.", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "odgi_build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1.", "odgi_layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "custom_filterdifferentialtable": "Filters a differential expression table based on logFC and adjusted p-value thresholds"}}, "target": "odgi_layout", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_10", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_5", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_hamronization_abricate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize ABRicate outputs using the hAMRonization specification (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization_abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "checkm_qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "fastqscan": "FASTQ summary statistics in JSON format", "hamronization_rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification.", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "hamronization_abricate", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_44", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_4", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_49", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "pipe_all101_createpanelrefs_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Generate Panel of Normals, models or other similar references from lots of samples. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v"}}, "target": "createpanelrefs", "target_idx": 3}
{"id": "mod_hhsuite_hhsearch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs) (tools: hhsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment", "varscan/fpfilter": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "hhsuite/hhsearch": "Sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "mobster": "Subclonal deconvolution of cancer genome sequencing data."}}, "target": "hhsuite/hhsearch", "target_idx": 3}
{"id": "mod_survivor_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare or merge VCF files to generate a consensus or multi sample VCF files. (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/seqreformat": "Reformats files with t-coffee", "survivor/merge": "Compare or merge VCF files to generate a consensus or multi sample VCF files.", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "bedtools/merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "seqtk/cutn": "Generates a BED file containing genomic locations of lengths of N."}}, "target": "survivor/merge", "target_idx": 1}
{"id": "mod_varlociraptor_filterfdr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter Varlociraptor variant calls using FDR control. (tools: varlociraptor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last/train": "Find suitable score parameters for sequence alignment", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "goat/taxonsearch": "Query metadata for any taxon across the tree of life.", "varlociraptor/filterfdr": "Filter Varlociraptor variant calls using FDR control.", "bcftools/annotate": "Add or remove annotations."}}, "target": "varlociraptor/filterfdr", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_2_4", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness", "pipeline": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_0_3", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_hypo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembly polisher using short (and long) reads (tools: hypo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hypo": "Assembly polisher using short (and long) reads", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "nextclade_datasetget": "Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ impleme", "centrifuge_kreport": "Creates Kraken-style reports from centrifuge out files", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}}, "target": "hypo", "target_idx": 0}
{"id": "mod_md5sum_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create MD5 (128-bit) checksums (tools: md5sum)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/splitintervals": "Split intervals into sub-interval files.", "shasum": "Print SHA256 (256-bit) checksums.", "samtools/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "rclone/checksum": "Check files in a destination path against a checksum SUM file", "md5sum": "Create MD5 (128-bit) checksums"}}, "target": "md5sum", "target_idx": 4}
{"id": "noul_multiple_script_sections_invalid_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_rtgtools_pedfilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a PED file to VCF headers (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": "Annotation and Ranking of Structural Variation", "expansionhunter": "Estimate repeat sizes using NGS data", "refsolver/identify": "Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver", "rtgtools/pedfilter": "Converts a PED file to VCF headers", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "rtgtools/pedfilter", "target_idx": 3}
{"id": "resource_art_illumina_0", "category": "resource_profiling", "state": {"process": "ART_ILLUMINA", "tool": "art/illumina", "description": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ART_ILLUMINA (Simulation tool to generate synthetic Illumina next-generation sequencing reads) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_biobambam_bammerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge a list of sorted bam files (tools: biobambam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam/bammerge": "Merge a list of sorted bam files", "bedtools/merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "hostile/fetch": "Downloads required reference genomes for Hostile", "suppa/psiperisoform": "Calculate PSI values for transcript isoforms using SUPPA", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "biobambam/bammerge", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_14", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_antismash_antismashlite_3", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITE", "tool": "antismash/antismashlite", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITE (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_6", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "subworkflow_pkg_faa_seqfu_seqkit_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FAA_SEQFU_SEQKIT", "modules": ["seqfu/stats", "seqkit/seq", "seqkit/rmdup", "seqkit/replace"], "description": "Subworkflow that optionally preprocesses amino acid FASTA sequences"}, "question": {"type": "choice", "instructions": "How should FAA_SEQFU_SEQKIT (seqfu/stats, seqkit/seq, seqkit/rmdup, seqkit/replace) be structured in DSL2?", "criteria": {"Local subworkflow FAA_SEQFU_SEQKIT": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow faa_seqfu_seqkit": null}}, "target": "Use nf-core subworkflow faa_seqfu_seqkit", "target_idx": 3}
{"id": "samplesheet_arch_vcf_annotation_pipeline_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/raredisease) for Downstream functional annotation of pre-called VCF files. Input files: BGZF-compressed VCF files with companion Tabix index files.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Downstream functional annotation of pre-called VCF files.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,bed": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "mod_metator_pipeline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing and binning of metagenomic metaHiC datasets. (tools: metator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mgnifam/generatefamilies": "Iteratively builds protein family HMM profiles from MMseqs2 sequence clusters and expands them against a prote", "juicertools/pre": "Create a multi-resolution .hic contact matrix for analysis with Juicer", "custom/catadditionalfasta": "Custom module to Add a new fasta file to an old one and update an associated GTF", "metator/pipeline": "Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing an", "cooler/merge": "Merge multiple coolers with identical axes"}}, "target": "metator/pipeline", "target_idx": 3}
{"id": "mod_bismark_coverage2cytosine_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Relates methylation calls back to genomic cytosine contexts. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_indeppairwise": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of varia", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "motus_merge": "Taxonomic meta-omics profiling using universal marker genes", "bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "bismark_align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "bismark_coverage2cytosine", "target_idx": 3}
{"id": "noul_workflow_completion_lifecycle_hook_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_cooler_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple coolers with identical axes (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bammerge": null, "seqkit_seq": null, "cooler_merge": null, "fmhfunprofiler": null, "agat_spmergeannotations": null}}, "target": "cooler_merge", "target_idx": 2}
{"id": "mod_agat_convertspgff2gtf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a GFF/GTF file into a proper GTF file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "agat_convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "plink_epistasis": "Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others."}}, "target": "agat_convertspgff2gtf", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_find_mirna_mirdeep2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FIND_MIRNA_MIRDEEP2", "modules": ["seqkit/fq2fa", "seqkit/replace", "bowtie/build", "mirdeep2/mapper", "mirdeep2/mirdeep2"], "description": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, processes and replaces any whitespace in sequence IDs, builds a Bowtie index of the genome, and then maps reads using miRDeep2 mapper before identifying known and novel miRNAs."}, "question": {"type": "choice", "instructions": "How should FASTQ_FIND_MIRNA_MIRDEEP2 (seqkit/fq2fa, seqkit/replace, bowtie/build, mirdeep2/mapper, mirdeep2/mirdeep2) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_FIND_MIRNA_MIRDEEP2": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_find_mirna_mirdeep2": null}}, "target": "Use nf-core subworkflow fastq_find_mirna_mirdeep2", "target_idx": 3}
{"id": "noul_named_output_channel_access_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_rustqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, and SAMtools stats (tools: rustqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_blastp": null, "whatshap_haplotag": null, "custom_multiqccustombiotype": null, "rustqc": null, "anota2seq_anota2seqrun": null}}, "target": "rustqc", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_8", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_strelka_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA", "modules": ["gatk4/mergevcfs", "strelka/somatic"], "description": "Perform variant calling on a paired tumor normal set of samples using strelka somatic mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA (gatk4/mergevcfs, strelka/somatic) be structured in DSL2?", "criteria": {"Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA": null, "Leave them out": null, "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka", "target_idx": 2}
{"id": "mod_gtfsort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort GTF files in chr/pos/feature order (tools: gtfsort)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gtfsort": null, "duphold": null, "fgbio/collectduplexseqmetrics": null, "pydamage/analyze": null, "crisprcleanr/normalize": null}}, "target": "gtfsort", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_1_46", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_telogator2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Allele-specific telomere length estimation and TVR characterization from long reads (tools: telogator2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "bamclipper": "This module is used to clip primer sequences from your alignments.", "hisat2/align": "Align RNA-Seq reads to a reference with HISAT2", "telogator2": "Allele-specific telomere length estimation and TVR characterization from long reads", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "telogator2", "target_idx": 3}
{"id": "resource_amulety_embed_0", "category": "resource_profiling", "state": {"process": "AMULETY_EMBED", "tool": "amulety/embed", "description": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_EMBED (A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) ) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_0_2", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_31", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_wipertools_fastqwiper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files (tools: fastqwiper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/catadditionalfasta": null, "catpack/summarise": null, "adapterremovalfixprefix": null, "wipertools/fastqwiper": null, "adapterremoval": null}}, "target": "wipertools/fastqwiper", "target_idx": 3}
{"id": "schema_std_proteinfamilies_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinfamilies", "assay": "proteinfamilies pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/proteinfamilies (Generation and updating of protein families)?", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "id,path": null, "sample,sample_id,fastq_1,fastq_2,method": null}}, "target": "sample,fasta,existing_hmms_to_update,existing_msas_to_update", "target_idx": 1}
{"id": "field_constraint_sex_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "mod_scanpy_hashsolo_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Probabilistic demultiplexing of cell hashing data (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy/hashsolo": null, "bedtools/flank": null, "metaspace/converter": null, "arcane/filter": null, "bam_variant_demix_boot_freyja": null}}, "target": "scanpy/hashsolo", "target_idx": 0}
{"id": "subworkflow_pkg_bcl_demultiplex_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BCL_DEMULTIPLEX", "modules": ["bcl2fastq", "bclconvert", "multiqcsav"], "description": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq"}, "question": {"type": "choice", "instructions": "How should BCL_DEMULTIPLEX (bcl2fastq, bclconvert, multiqcsav) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow bcl_demultiplex": null, "Local subworkflow BCL_DEMULTIPLEX": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bcl_demultiplex", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Standard Paired-end Whole Genome Sequencing (WGS). Input files: Raw paired-end Illumina WGS FASTQs.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Standard Paired-end Whole Genome Sequencing (WGS).", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_dragmap_hashtable_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create DRAGEN hashtable for reference genome (tools: dragmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": null, "kmcp_index": null, "biscuit_index": null, "dragmap_hashtable": null, "svync": null}}, "target": "dragmap_hashtable", "target_idx": 3}
{"id": "mod_mmseqs_fasta_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file. (tools: mmseqs_fasta_cluster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_fasta_cluster": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file.", "bam_markduplicates_samtools": "Samtools markduplicate SAM/BAM/CRAM file", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "gatk4_sitedepthtobaf": "EXPERIMENTAL TOOL! Convert SiteDepth to BafEvidence"}}, "target": "mmseqs_fasta_cluster", "target_idx": 0}
{"id": "field_constraint_fastq_2_1_11", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "resource_baysor_segfree_2", "category": "resource_profiling", "state": {"process": "BAYSOR_SEGFREE", "tool": "baysor/segfree", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_SEGFREE (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_autocycler_resolve_4", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_RESOLVE", "tool": "autocycler/resolve", "description": "Resolve trimmed assembly graphs into final contigs within Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_RESOLVE (Resolve trimmed assembly graphs into final contigs within Autocycler.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_3_0", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic tumor-normal calling from pre-aligned BAM files with entry step MUTECT2.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,vcf": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "mod_oarfish_readprojectionmode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Spliced-align raw reads to the genome, project each read's genomic alignments onto the annotated transcripts via bramble, then quantify. (tools: oarfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "metacache/query": "Metacache query command for taxonomic classification", "raw2ometiff": "write your description here", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "oarfish/readprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Splic"}}, "target": "oarfish/readprojectionmode", "target_idx": 4}
{"id": "core_tool_samtools_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Coordinate-sorting, indexing, and statistics generation for genome-aligned BAM binary alignment files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bedtools": "Genomic arithmetic tools", "sambamba": "Fast BAM manipulation", "picard": "Java-based BAM utilities", "bamtools": "C++ API and toolkit for BAM", "samtools": "Reading/writing/sorting/indexing/viewing SAM/BAM/CRAM format alignments"}}, "target": "samtools", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_binning_concoct_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BINNING_CONCOCT", "modules": ["concoct/cutupfasta", "concoct/concoctcoveragetable", "concoct/concoct", "concoct/mergecutupclustering", "concoct/extractfastabins"], "description": "Runs the CONCOCT workflow of contig binning"}, "question": {"type": "choice", "instructions": "How should FASTA_BINNING_CONCOCT (concoct/cutupfasta, concoct/concoctcoveragetable, concoct/concoct, concoct/mergecutupclustering, concoct/extractfastabins) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_binning_concoct": null, "Leave them out": null, "Local subworkflow FASTA_BINNING_CONCOCT": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_binning_concoct", "target_idx": 0}
{"id": "mod_plink_hwe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate Hardy-Weinberg statistics for provided input (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiddit/sv": "Identify chromosomal rearrangements.", "picard/mergesamfiles": "Merges multiple BAM files into a single file", "assemblyscan": "Assembly summary statistics in JSON format", "plink/hwe": "Generate Hardy-Weinberg statistics for provided input", "trycycler/subsample": "Subsample a long-read sequencing fastq file for multiple assemblies"}}, "target": "plink/hwe", "target_idx": 3}
{"id": "mod_plink_bcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analyses binary variant call format (BCF) files using plink (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quantmsutils_diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils", "plink_exclude": "Exclude variant identifiers from plink bfiles", "plink_bcf": "Analyses binary variant call format (BCF) files using plink", "nextgenmap": "Performs fastq alignment to a fasta reference using NextGenMap", "plink_genome": "Calculates identity-by-descent over autosomal SNPs"}}, "target": "plink_bcf", "target_idx": 2}
{"id": "mod_emboss_revseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: the revseq program from emboss reverse complements a nucleotide sequence (tools: emboss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pydamage/filter": "Damage parameter estimation for ancient DNA", "epang/place": "phylogenetic placement of query sequences in a reference tree", "emboss/revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "tagbam": "A tool for tagging BAM files."}}, "target": "emboss/revseq", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_qc_trim_filter_setstrandedness_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS", "modules": ["bbmap/bbsplit", "cat/fastq", "fastqc", "fq/lint", "fastq_remove_rrna", "fastq_subsample_fq_salmon", "fastq_fastqc_umitools_trimgalore", "fastq_fastqc_umitools_fastp"], "description": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files, preparing them for downstream analysis."}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS (bbmap/bbsplit, cat/fastq, fastqc, fq/lint, fastq_remove_rrna, fastq_subsample_fq_salmon, fastq_fastqc_umitools_trimgalore, fastq_fastqc_umitools_fastp) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS": null, "Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness", "target_idx": 2}
{"id": "pipe_all101_isoseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences and produce a bed annotation.. Topics: isoseq, isoseq-3, rna, tama, ultra. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": null, "mhcquant": null, "demo": null, "eager": null, "isoseq": null}}, "target": "isoseq", "target_idx": 4}
{"id": "mod_scoary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use pangenome outputs for GWAS (tools: scoary)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vg/index": "write your description here", "regenie/runl1": "Finish REGENIE step 1 from split level-0 prediction files", "plastid/metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "scoary": "Use pangenome outputs for GWAS", "plink/gwas": "Generate GWAS association studies"}}, "target": "scoary", "target_idx": 3}
{"id": "noul_exit_code_137_cause_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_1_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_agat_convertspgxf2gxf_4", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGXF2GXF", "tool": "agat/convertspgxf2gxf", "description": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGXF2GXF (Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_ngsbits_rohhunter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: RohHunter is a tool for run of homozygosity (ROH) detection based on a variant list in VCF format. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ferrohgvs_normalize": null, "cowpy": null, "rhocall_viz": null, "bcftools_roh": null, "ngsbits_rohhunter": null}}, "target": "ngsbits_rohhunter", "target_idx": 4}
{"id": "mod_gcta_adjustgrm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adjust a dense GRM for incomplete tagging using `gcta --grm-adj` (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/fastgwa": null, "gcta/bivariateremlldms": null, "gcta/adjustgrm": null, "blobtk/snail": null, "hmmcopy/mapcounter": null}}, "target": "gcta/adjustgrm", "target_idx": 2}
{"id": "intent_ask_question_12", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "ask_question", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_4_4", "category": "samplesheet_schema", "state": {"technology": "Microbial Assembly", "workflow_entry": "FASTQC", "library_inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate?", "criteria": {"sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 0}
{"id": "field_constraint_fastq_1_0_2", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "subworkflow_pkg_bedgraph_bedclip_bedgraphtobigwig_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG", "modules": ["ucsc/bedclip", "ucsc/bedgraphtobigwig"], "description": "Convert bedgraph to bigwig with clip"}, "question": {"type": "choice", "instructions": "How should BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG (ucsc/bedclip, ucsc/bedgraphtobigwig) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG": null, "Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig": null}}, "target": "Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig", "target_idx": 3}
{"id": "mod_fasta_index_methylseq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate index files from reference fasta for bismark, bwameth and bwamem aligners (tools: fasta_index_methylseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": null, "centrifuger_build": null, "bismark_deduplicate": null, "fasta_index_methylseq": null, "truvari_segment": null}}, "target": "fasta_index_methylseq", "target_idx": 3}
{"id": "schema_std_methylong_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/methylong. Description: Extract methylation calls from long reads (ONT/ PacBio) .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/methylong.", "criteria": {"sample,group,path,ref,method": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fastq_1,fastq_2,strandedness,condition": null}}, "target": "sample,group,path,ref,method", "target_idx": 0}
{"id": "mod_panacus_visualize_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create visualizations from a tsv coverage histogram created with panacus. (tools: panacus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spstatistics": "Provides different type of statistics in text format from a GFF/GTF annotation file", "scimap/spatiallda": "SpatialLDA uses an LDA based approach for the identification of cellular neighborhoods, using cell type identi", "bam_telomere_estimation": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter", "panacus/visualize": "Create visualizations from a tsv coverage histogram created with panacus.", "bamstats/generalstats": "write your description here"}}, "target": "panacus/visualize", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_classify_catpack_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CLASSIFY_CATPACK", "modules": ["catpack/addnames", "catpack/bins", "catpack/contigs", "catpack/download", "catpack/prepare", "catpack/summarise", "untar"], "description": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack)."}, "question": {"type": "choice", "instructions": "How should FASTA_CLASSIFY_CATPACK (catpack/addnames, catpack/bins, catpack/contigs, catpack/download, catpack/prepare, catpack/summarise, untar) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_classify_catpack": null, "Local subworkflow FASTA_CLASSIFY_CATPACK": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_classify_catpack", "target_idx": 0}
{"id": "resource_biobambam_bammerge_5", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMERGE", "tool": "biobambam/bammerge", "description": "Merge a list of sorted bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMERGE (Merge a list of sorted bam files) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bftools_showinf_3", "category": "resource_profiling", "state": {"process": "BFTOOLS_SHOWINF", "tool": "bftools/showinf", "description": "Extract OME xml data from OME-tif"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFTOOLS_SHOWINF (Extract OME xml data from OME-tif) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_atacseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/atacseq. Description: ATAC-seq peak-calling and QC analysis pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/atacseq.", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,group,path,ref,method": null, "sample,fastq_1,fastq_2,condition,reference": null}}, "target": "sample,fastq_1,fastq_2,replicate,control", "target_idx": 0}
{"id": "mod_ataqv_ataqv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ataqv function of a corresponding ataqv tool (tools: ataqv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genrich": null, "fq/generate": null, "macs3/callpeak": null, "ataqv/ataqv": null, "fastq_fetch_clean_hostile": null}}, "target": "ataqv/ataqv", "target_idx": 3}
{"id": "mod_lofreq_indelqual_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Inserts indel qualities in a BAM file (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gappa/examineheattree": "colours a phylogeny with placement densities", "lofreq/indelqual": "Inserts indel qualities in a BAM file", "khmer/normalizebymedian": "Module that calls normalize-by-median.py from khmer. The module can take a mix of paired end (interleaved) and", "bcftools/concat": "Concatenate VCF files", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "lofreq/indelqual", "target_idx": 1}
{"id": "mod_fastq_qc_stats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate statistics for short read sequencing data using multiple tools (tools: fastq_qc_stats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_qc_stats": null, "traitar_run": null, "mobsuite_typer": null, "art_illumina": null, "ariba_run": null}}, "target": "fastq_qc_stats", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_8", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_glimpse2_concordance_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Program to compute the genotyping error rate at the sample or marker level. (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse_ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information.", "bam_docounts_contamination_angsd": "Calculate contamination of the X-chromosome with ANGSD", "glimpse2_concordance": "Program to compute the genotyping error rate at the sample or marker level.", "glimpse2_ligate": "Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks tha", "tabix_bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde"}}, "target": "glimpse2_concordance", "target_idx": 2}
{"id": "resource_amrfinderplus_update_0", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_UPDATE", "tool": "amrfinderplus/update", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_UPDATE (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_42", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "intent_build_pipeline_17", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "build_pipeline": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "mod_leafcutter_clusterregtools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alternative splicing analysis (tools: leafcutter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"methurator_gtestimator": null, "leafcutter_clusterregtools": null, "regtools_junctionsextract": null, "ragtag_scaffold": null, "rmats_prep": null}}, "target": "leafcutter_clusterregtools", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_2_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "sample,cdna_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "noul_channel_join_operator_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_mag_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for annotation analysis? Specific context: Assembly and binning of metagenomes. Topics: annotation, assembly, binning, long-read-sequencing, metagenomes, metagenomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "metapep": "From metagenomes to epitopes and beyond", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina"}}, "target": "mag", "target_idx": 2}
{"id": "mod_gem2_gemmappability_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Define the mappability of a reference (tools: gem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_filterintervals": "Filters intervals based on annotations and/or count statistics.", "gem2_gemmappability": "Define the mappability of a reference", "gem3_gem3indexer": "Create a GEM index from a FASTA file", "gem2_gem2bedmappability": "Convert a mappability file to bedgraph format", "ltrretriever_lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric "}}, "target": "gem2_gemmappability", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_6_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for FAIRE-seq / DNAse-seq open chromatin profiling input samplesheet?", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_2_25", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "pipe_all101_marsseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for facs-sorting. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we"}}, "target": "marsseq", "target_idx": 8}
{"id": "samplesheet_arch_ont_demux_barcodes_3_2", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multiplexed Oxford Nanopore run with barcode demultiplexing with entry step NANOPLOT.", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "mod_seqkit_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts sequences by id/name/sequence/length (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "seqkit/sort": "Sorts sequences by id/name/sequence/length", "fasta_newick_epang_gappa": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in ", "samplesheetparser/diff": "Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff cove"}}, "target": "seqkit/sort", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/diaproteomics --input samplesheet.csv (Assay: Data-Independent Acquisition (DIA) quantitative mass spectrometry)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Data-Independent Acquisition (DIA) quantitative mass spectrometry with entry step INPUT_CHECK.", "criteria": {"sample,peptides_tsv": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_41", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_4_1", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: BGZF-compressed VCF files with companion Tabix index files?", "criteria": {"sample,bam,bai": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_9", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wes_pe_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Paired-end Whole Exome Sequencing (WES) target capture)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_pairgenomealign_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pairgenomealign", "description": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pairgenomealign?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,barcode": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "sample,fasta", "target_idx": 0}
{"id": "subworkflow_pkg_bam_methyldackel_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_METHYLDACKEL", "modules": ["methyldackel/extract", "methyldackel/mbias"], "description": "Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignments using Methyldackel."}, "question": {"type": "choice", "instructions": "How should BAM_METHYLDACKEL (methyldackel/extract, methyldackel/mbias) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_METHYLDACKEL": null, "Use nf-core subworkflow bam_methyldackel": null}}, "target": "Use nf-core subworkflow bam_methyldackel", "target_idx": 3}
{"id": "mod_gatk4_calibratedragstrmodel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: estimates the parameters for the DRAGstr model (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_baserecalibrator": null, "ribodetector": null, "s4pred_runmodel": null, "gatk4_annotateintervals": null, "gatk4_calibratedragstrmodel": null}}, "target": "gatk4_calibratedragstrmodel", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_0_9", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_ribodetector_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accurate and rapid RiboRNA sequences Detector based on deep learning (tools: ribodetector)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_haplotyper": null, "cnvkit_coverage": null, "abra2": null, "ribodetector": null, "fusioncatcher_build": null}}, "target": "ribodetector", "target_idx": 3}
{"id": "mod_utils_nfschema_plugin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run nf-schema to validate parameters and create a summary of changed parameters (tools: utils_nfschema_plugin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_align": "Aligns sequences using T_COFFEE", "fastavalidator": "\"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror lo", "utils_nfschema_plugin": "Run nf-schema to validate parameters and create a summary of changed parameters", "happy_happy": "Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row", "foldcomp_compress": "Efficient compression tool for protein structures"}}, "target": "utils_nfschema_plugin", "target_idx": 2}
{"id": "pipe_all101_magmap_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for magmap. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u"}}, "target": "magmap", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "noul_named_process_output_emits_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_3", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_32", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_bam_variant_calling_mpileup_bcftools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to compute genotype likelihoods from BAM files using\nbcftools/mpileup and bcftools/call variants by chromosomes.\nThe resulting VCF files are then merged by chromosomes and\nannotated with bcftools/annotate to give an ID for each variants.\nDuring samples merging and region concatenation, all metadata will\nbe preserved and stored in the key `metas` at each step. (tools: bam_variant_calling_mpileup_bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi", "medaka": "A tool to create consensus sequences and variant calls from nanopore sequencing data", "bamclipper": "This module is used to clip primer sequences from your alignments.", "bam_variant_calling_mpileup_bcftools": "Subworkflow to compute genotype likelihoods from BAM files using\nbcftools/mpileup and bcftools/call variants b", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "bam_variant_calling_mpileup_bcftools", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_6_4", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Parse Biosciences Split-seq combinatorial barcoding input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_parabricks_starfusion_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. This requires input of a genome resource library, in accordance with the original STAR-Fusion tool, and outputs candidate fusion transcripts. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "blobtk/create": "Creates a minimal blobdir.", "sgdemux": "Demultiplex bgzip'd fastq files", "parabricks/starfusion": "This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. Thi", "starfusion/detect": "Fast and Accurate Fusion Transcript Detection from RNA-Seq"}}, "target": "parabricks/starfusion", "target_idx": 3}
{"id": "pipe_all101_viralintegration_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach.. Topics: chimeric-alignment, ctat, viral-integration, virus, virusintegrationfinder. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"oncoanalyser": null, "nanostring": null, "genomeqc": null, "ribomsqc": null, "imcyto": null, "bacass": null, "viralintegration": null, "epitopeprediction": null}}, "target": "viralintegration", "target_idx": 6}
{"id": "mod_duckdb_table2parquet_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a delimited text table (CSV or TSV, gzipped or not) to Parquet (tools: duckdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"duckdb_table2parquet": "Convert a delimited text table (CSV or TSV, gzipped or not) to Parquet", "csvtk_mutate2": "Create a new column from selected fields by awk-like arithmetic/string expressions", "checkqc": "A simple program to parse Illumina NGS data and check it for quality criteria", "csvtk_sort": "Sort  CSV (or TSV) tables", "rastair_call": "Assess positive C->T conversion as a readout for methylation on a genome-wide basis"}}, "target": "duckdb_table2parquet", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Visium spatial transcriptomics with histology image. Input files: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,image": null, "sample,bam": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_49", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_deeptools_plotheatmap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: plots values produced by deeptools_computematrix as a heatmap (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan/easysubstrate": "Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzyme", "krona/ktimporttaxonomy": "KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot.", "deeptools/plotheatmap": "plots values produced by deeptools_computematrix as a heatmap", "rpbp/extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "blobtk/plot": "Creates differing styles of blobplots depending on provided arguments."}}, "target": "deeptools/plotheatmap", "target_idx": 2}
{"id": "noul_process_conditional_execution_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_svdb_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The merge module merges structural variants within one or more vcf files. (tools: svdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": "Annotation and Ranking of Structural Variation", "pygenprop/build": "Generate a Micromeda file containing pathway annotations for one or more genomes.\nSupporting InterProScan and ", "rseqc/junctionsaturation": "compare detected splice junctions to reference gene model", "svdb/merge": "The merge module merges structural variants within one or more vcf files.", "caddsv/run": "Score structural variants with CADD-SV."}}, "target": "svdb/merge", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral amplicon sequencing with primers)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral amplicon sequencing with primers?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bracken_build_1", "category": "resource_profiling", "state": {"process": "BRACKEN_BUILD", "tool": "bracken/build", "description": "Extends a Kraken2 database to be compatible with Bracken"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BUILD (Extends a Kraken2 database to be compatible with Bracken) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_cnvkit_fix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional coverage and GC content, according to the given reference. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/reference": null, "cnvkit/batch": null, "gatk4spark/applybqsr": null, "cnvkit/fix": null, "scanpy/pca": null}}, "target": "cnvkit/fix", "target_idx": 3}
{"id": "mod_pbtk_bam2fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq (tools: pbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "pbtk_bam2fastq": "converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq", "cnvpytor_histogram": "calculates read depth histograms", "bcftools_stats": "Generates stats from VCF files", "bio2zarr_vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}}, "target": "pbtk_bam2fastq", "target_idx": 1}
{"id": "mod_td2_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Seq transcript assembly (tools: td2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whatshap/stats": "Compute statistics from phased variant file using Whatshap", "td2/predict": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "fasta_build_add_kraken2": "KRAKEN2 build custom database subworkflow", "td2/longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "ribotish/predict": "Quality control of riboseq bam data"}}, "target": "td2/predict", "target_idx": 1}
{"id": "resource_bcftools_rohviz_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROHVIZ", "tool": "bcftools/rohviz", "description": "Visualise the output of bcftools roh"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROHVIZ (Visualise the output of bcftools roh) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_bcftools_csq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: bcftools Haplotype-aware consequence caller (tools: reheader)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "custom/addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "bcftools/csq": "bcftools Haplotype-aware consequence caller"}}, "target": "bcftools/csq", "target_idx": 4}
{"id": "samplesheet_arch_pediatric_trio_somatic_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents))", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_tif_registration_stainwarpy_3", "category": "subworkflow_packaging", "state": {"subworkflow": "TIF_REGISTRATION_STAINWARPY", "modules": ["stainwarpy/extractchannel", "stainwarpy/register", "stainwarpy/transformsegmask"], "description": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy"}, "question": {"type": "choice", "instructions": "How should TIF_REGISTRATION_STAINWARPY (stainwarpy/extractchannel, stainwarpy/register, stainwarpy/transformsegmask) be structured in DSL2?", "criteria": {"Local subworkflow TIF_REGISTRATION_STAINWARPY": null, "Leave them out": null, "Use nf-core subworkflow tif_registration_stainwarpy": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow tif_registration_stainwarpy", "target_idx": 2}
{"id": "schema_std_genomicrelatedness_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomicrelatedness", "description": "Bioinformatics pipeline for estimating genetic relatedness from low-coverage whole-genome sequencing (sWGS) data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/genomicrelatedness?", "criteria": {"sample,fastq_1,fastq_2,bam,seq_type": null, "sample,fastq_1,fastq_2,bam,cram": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "sample,fastq_1,fastq_2,bam,cram", "target_idx": 1}
{"id": "mod_bcftools_csq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: bcftools Haplotype-aware consequence caller (tools: reheader)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c", "annotsv_installannotations": "Install the AnnotSV annotations", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bcftools_csq": "bcftools Haplotype-aware consequence caller", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga"}}, "target": "bcftools_csq", "target_idx": 3}
{"id": "mod_sentieon_tnhaplotyper2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_splitheader": "Extract header lines from a SAM/BAM/CRAM file into separate files depending on type", "fastme": "Distance-based phylogeny with FastME", "sentieon_bwaindex": "Create BWA index for reference genome", "sentieon_tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.", "sentieon_collectvcmetrics": "Accelerated implementation of the Picard CollectVariantCallingMetrics tool."}}, "target": "sentieon_tnhaplotyper2", "target_idx": 3}
{"id": "resource_agat_spfilterbyorfsize_4", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERBYORFSIZE", "tool": "agat/spfilterbyorfsize", "description": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF passing the test, the other contains the rest. By default the test is \"> 100\" that means all gene models that have ORF longer than 100 Amino acids, will pass the test."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERBYORFSIZE (The script reads a gff annotation file, and create two output files, one contain) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_fastq_decontaminate_deacon_hostile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile (tools: fastq_decontaminate_deacon_hostile)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hostile_clean": "Removes host reads from short- and long-read FASTQ sequencing files", "fastq_decontaminate_deacon_hostile": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile", "ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro", "hostile_fetch": "Downloads required reference genomes for Hostile", "vardictjava": "The Java port of the VarDict variant caller"}}, "target": "fastq_decontaminate_deacon_hostile", "target_idx": 1}
{"id": "noul_exit_code_137_cause_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_grimer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates an interactive HTML dashboard integrating taxonomy,\nannotation, and metadata to detect contamination in metagenomic\nand amplicon sequencing datasets. GRIMER is independent of\nquantification methods and directly analyses contingency tables. (tools: grimer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kat_hist": "Creates a histogram of the number of distinct k-mers having a given frequency.", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "seqwish_induce": "Induce a variation graph in GFA format from alignments in PAF format", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "grimer": "Generates an interactive HTML dashboard integrating taxonomy,\nannotation, and metadata to detect contamination"}}, "target": "grimer", "target_idx": 4}
{"id": "mod_magus_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multiple Sequence Alignment using Graph Clustering (tools: magus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"magus_align": "Multiple Sequence Alignment using Graph Clustering", "metabuli_build": "Builds a database for classification with metabuli from FASTA files and a taxonomy", "deeparg_downloaddata": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "clustalo_guidetree": "Renders a guidetree in clustalo", "famsa_guidetree": "Renders a guidetree in famsa"}}, "target": "magus_align", "target_idx": 0}
{"id": "mod_raven_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: De novo genome assembler for long uncorrected reads. (tools: raven)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngsbits/bedannotategc": "Annotates GC content fraction to regions in a BED file.", "dastool/scaffolds2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "tabix/tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,", "raven": "De novo genome assembler for long uncorrected reads.", "flye": "De novo assembler for single molecule sequencing reads"}}, "target": "raven", "target_idx": 3}
{"id": "mod_seqwish_induce_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Induce a variation graph in GFA format from alignments in PAF format (tools: seqwish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_subsample_fq_salmon": "Subsample fastq", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats", "seqwish_induce": "Induce a variation graph in GFA format from alignments in PAF format", "macrel_contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid", "mm2plus_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences"}}, "target": "seqwish_induce", "target_idx": 2}
{"id": "pipe_core10_sarek_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Tumor/normal pair exome sequencing for somatic SNV calling with Strelka2, Mutect2, and FreeBayes with VEP annotation.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "sarek", "target_idx": 4}
{"id": "mod_snapaligner_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using SNAP (tools: snapaligner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rastair/call": null, "foldcomp/decompress": null, "amps": null, "snapaligner/align": null, "bwa/mem": null}}, "target": "snapaligner/align", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_star_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_STAR", "modules": ["star/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bowtie2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_STAR (star/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_star": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_STAR": null}}, "target": "Use nf-core subworkflow fastq_align_star", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_40", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_5", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_arcane_filter_3", "category": "resource_profiling", "state": {"process": "ARCANE_FILTER", "tool": "arcane/filter", "description": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCANE_FILTER (Filter GTF annotations and genome sequence for alignment-free single-cell RNA-se) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_pyrodigal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pyrodigal is a Python module that provides bindings to Prodigal, a fast, reliable protein-coding gene prediction for prokaryotic genomes. (tools: pyrodigal)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qcat": null, "pyrodigal": null, "duphold": null, "clame": null, "grabix/check": null}}, "target": "pyrodigal", "target_idx": 1}
{"id": "mod_bam_variant_calling_sort_freebayes_bcftools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call variants using freebayes, then sort and index (tools: bam_variant_calling_sort_freebayes_bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_variant_calling_sort_freebayes_bcftools": null, "artic_aligntrim": null, "graphtyper_genotype": null, "semibin_singleeasybin": null, "ferrohgvs_parse": null}}, "target": "bam_variant_calling_sort_freebayes_bcftools", "target_idx": 0}
{"id": "mod_biobambam_bamsormadup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parallel sorting and duplicate marking (tools: biobambam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch/sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).", "dupblaster": "Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline ", "mitohifi/findmitoreference": "Download a mitochondrial genome to be used as reference for MitoHiFi.\n\nNOTE: An optional NCBI API key can be s", "sambamba/markdup": "find and mark duplicate reads in BAM file", "biobambam/bamsormadup": "Parallel sorting and duplicate marking"}}, "target": "biobambam/bamsormadup", "target_idx": 4}
{"id": "mod_tcoffee_extractfrompdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reformats the header of PDB files with t-coffee (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g", "tcoffee/extractfrompdb": "Reformats the header of PDB files with t-coffee", "plink/indeppairwise": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of varia", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "tesorter": "An accurate and fast method to classify LTR-retrotransposons in plant genomes"}}, "target": "tcoffee/extractfrompdb", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_1_5", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wes_pe_2_0", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_msisensorpro_msisomatic_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing data. It accepts the whole genome sequencing, whole exome sequencing and target region (panel) sequencing data as input (tools: msisensorpro)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amplify/predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "msisensor/msi": "Evaluate microsattelite instability (MSI) using paired tumor-normal sequencing data", "suppa/clusterevents": "Cluster events based on PSI values and significantly differentially spliced events using SUPPA2.", "msisensorpro/scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "msisensorpro/msisomatic": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d"}}, "target": "msisensorpro/msisomatic", "target_idx": 4}
{"id": "mod_metamaps_mapdirectly_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Maps long reads to a metamaps database (tools: metamaps)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "catpack/summarise": "Summarises results from CAT/BAT/RAT classification steps", "metamaps/mapdirectly": "Maps long reads to a metamaps database", "fusioninspector": "Validation of Fusion Transcript Predictions", "cnaqc": "Quality control of copy number data from bulk WGS assays"}}, "target": "metamaps/mapdirectly", "target_idx": 2}
{"id": "mod_genmap_map_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: create mappability files for a genome (tools: genmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hostile_clean": "Removes host reads from short- and long-read FASTQ sequencing files", "umitools_dedup": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "gem2_gemmappability": "Define the mappability of a reference", "genmap_map": "create mappability files for a genome", "gem3_gem3mapper": "Performs fastq alignment to a fasta reference using using gem3-mapper"}}, "target": "genmap_map", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_5_2", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: Fungal ITS1/ITS2 marker gene amplicon surveillance.", "criteria": {"sample,primer_its1,primer_its2": null, "sample,unite_fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_gatk4_intervallisttools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits the interval list file into unique, equally-sized interval files and place it under a directory (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "octopusv/stat": "Summarize structural variant statistics from octopusv SVCF files", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "gatk4/intervallisttools": "Splits the interval list file into unique, equally-sized interval files and place it under a directory"}}, "target": "gatk4/intervallisttools", "target_idx": 4}
{"id": "samplesheet_arch_rare_disease_trio_3_0", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Trio exome/genome sequencing (Proband, Mother, Father) with entry step FASTQC.", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_6_5", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Oxford Nanopore direct RNA input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fast5": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_gfatools_stat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summary statistics for GFA files (tools: gfatools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec_makegraph": "Plot Freec output", "gfatools_stat": "Summary statistics for GFA files", "bismark_summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "taxpasta_merge": "Standardise and merge two or more taxonomic profiles into a single table", "custom_summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a"}}, "target": "gfatools_stat", "target_idx": 1}
{"id": "mod_fq_lint_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fq lint is a FASTQ file pair validator. (tools: fq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/run": "Query input FASTQs against Ariba formatted databases", "vsearch/fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format.", "ucsc/bedtobigbed": "Convert file from bed to bigBed format", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "fq/lint": "fq lint is a FASTQ file pair validator."}}, "target": "fq/lint", "target_idx": 4}
{"id": "mod_snippy_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rapid haploid variant calling (tools: snippy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snippy/run": null, "graphtyper/genotype": null, "ferrohgvs/normalize": null, "seqtk/rename": null, "gcta/adjustgrm": null}}, "target": "snippy/run", "target_idx": 0}
{"id": "field_constraint_sex_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_30", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_13", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_sentieon_dnamodelapply_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: modifies the input VCF file by adding the MLrejected FILTER to the variants (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": null, "haplocheck": null, "fairy_coverage": null, "annotsv_annotsv": null, "sentieon_dnamodelapply": null}}, "target": "sentieon_dnamodelapply", "target_idx": 4}
{"id": "mod_rgi_cardannotation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Preprocess the CARD database for RGI to predict antibiotic resistance from protein or nucleotide data (tools: rgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "malt/build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "rsem/preparereference": "Prepare a reference genome for RSEM", "rgi/cardannotation": "Preprocess the CARD database for RGI to predict antibiotic resistance from protein or nucleotide data"}}, "target": "rgi/cardannotation", "target_idx": 4}
{"id": "samplesheet_arch_amplicon_16s_paired_1_3", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,primer_fwd,primer_rev": null, "sample,otu_table": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_proteinfold_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Protein 3D structure prediction pipeline. Topics: alphafold2, colabfold, esmfold, protein-fold-prediction, protein-folding, protein-sequences. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ampliseq": null, "rangeland": null, "bamtofastq": null, "proteinfold": null, "fastqrepair": null, "longraredisease": null, "rnasplice": null, "mag": null}}, "target": "proteinfold", "target_idx": 3}
{"id": "mod_disambiguate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ files. Useful in explant RNA/DNA-Seq workflows\nwhere reads from two species are present. For reads aligned to both organisms,\nthe algorithm compares alignment quality scores to determine the most likely\nspecies of origin. Produces four BAM files (uniquely assigned to species A or B,\nambiguous for species A or B) and a summary file. (tools: ngs-disambiguate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"disambiguate": "Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ fi", "sylph_query": "Sylph query command for querying genome databases against reads/metagenomes", "pbsv_discover": "pbsv - PacBio structural variant (SV) signature discovery tool", "arriba_visualisation": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in"}}, "target": "disambiguate", "target_idx": 0}
{"id": "mod_homer_maketagdirectory_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a tag directory with the HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"modkit/bedmethyltobigwig": "Convert a bedMethyl file to bigWig format using modkit", "homer/maketagdirectory": "Create a tag directory with the HOMER suite", "homer/findpeaks": "Find peaks with HOMER suite", "homer/annotatepeaks": "Annotate peaks with HOMER suite", "tximeta/tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages"}}, "target": "homer/maketagdirectory", "target_idx": 1}
{"id": "field_constraint_bai_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "intent_prepare_data_10", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "prepare_data", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Multi-lane Illumina sequencing run of clinical samples)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-lane Illumina sequencing run of clinical samples with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_abricate_summary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Screen assemblies for antimicrobial resistance against multiple databases (tools: abricate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nanocomp": "Compare multiple runs of long read sequencing data and alignments", "getorganelle_config": "Downloads databases needed for running getorganelle", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "abricate_summary", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wes_pe_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Paired-end Whole Exome Sequencing (WES) target capture)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Whole Exome Sequencing (WES) target capture with entry step FASTQC.", "criteria": {"sample,bam,bai": null, "sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_foldmason_easymsa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns protein structures using foldmason (tools: foldmason)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats", "foldmason_easymsa": "Aligns protein structures using foldmason", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "seqkit_translate": "Translate DNA/RNA to protein sequence"}}, "target": "foldmason_easymsa", "target_idx": 2}
{"id": "intent_ask_question_9", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "ask_question": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_samplesheetparser_validate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validate an Illumina SampleSheet.csv (V1 or V2) for index, adapter, and\nstructural issues. Format is auto-detected. Exits 0 if valid, 1 if errors\nare found — causing the pipeline to fail early with a clear message rather\nthan discovering demultiplexing problems downstream. (tools: samplesheet-parser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"art/illumina": null, "cellrangerarc/mkfastq": null, "amps": null, "ivar/trim": null, "samplesheetparser/validate": null}}, "target": "samplesheetparser/validate", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_0_45", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_strobealign_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align short reads using dynamic seed size with strobemers (tools: strobealign)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_createdb": null, "vcflib_vcffixup": null, "fastq_align_dna": null, "abra2": null, "strobealign": null}}, "target": "strobealign", "target_idx": 4}
{"id": "intent_debug_error_1", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "prepare_data": null, "build_pipeline": null}}, "target": "debug_error", "target_idx": 0}
{"id": "mod_glnexus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: merge gVCF files and perform joint variant calling (tools: glnexus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/extract": "Subset plink bfiles with a text file of variant identifiers", "glnexus": "merge gVCF files and perform joint variant calling", "biobambam/bammerge": "Merge a list of sorted bam files", "crispresso2": "A software pipeline for the analysis of genome editing outcomes from deep sequencing data", "bcftools/merge": "Merge VCF files"}}, "target": "glnexus", "target_idx": 1}
{"id": "mod_hmmer_eslsfetchindex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel miniapp bundled with the HMMER\npackage (esl-sfetch --index). The resulting index lets esl-sfetch\nretrieve sequences from the file in constant time. This module is the\nindexing half of a pair: hmmer/eslsfetchindex builds the SSI index,\nhmmer/eslsfetch consumes it (or an equivalent one) to fetch sequences\nor subsequences. (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmbuild": null, "huggingface_download": null, "hmmer_eslsfetchindex": null, "gappa_examinegraft": null, "hmmer_eslreformat": null}}, "target": "hmmer_eslsfetchindex", "target_idx": 2}
{"id": "noul_channel_operator_map_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bbmap_pileup_2", "category": "resource_profiling", "state": {"process": "BBMAP_PILEUP", "tool": "bbmap/pileup", "description": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_PILEUP (Calculates per-scaffold or per-base coverage information from an unsorted sam or) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bbmap_filterbyname_2", "category": "resource_profiling", "state": {"process": "BBMAP_FILTERBYNAME", "tool": "bbmap/filterbyname", "description": "Filter out sequences by sequence header name(s)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_FILTERBYNAME (Filter out sequences by sequence header name(s)) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_3_2", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq with entry step FASTQC.", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,well,fastq": null, "plate,sample,bam": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_gsea_gsea_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: run the Broad Gene Set Enrichment tool in GSEA mode (tools: gsea)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hlala/preparegraph": "Pre-compute the graph index structure.", "homer/findpeaks": "Find peaks with HOMER suite", "abacas": "Contiguate draft genome assembly", "custom/tabulartogseacls": "Make a GSEA class file (.cls) from tabular inputs", "gsea/gsea": "run the Broad Gene Set Enrichment tool in GSEA mode"}}, "target": "gsea/gsea", "target_idx": 4}
{"id": "mod_diann_insilicolibrarygeneration_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN software for data-independent acquisition (DIA) proteomics data processing.\nOutput materials should include attribution: \"Generated using DIA-NN\". (tools: diann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "diann/insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "vg/deconstruct": "Deconstruct snarls present in a variation graph in GFA format to variants in VCF format", "kmcp/search": "Search sequences against database"}}, "target": "diann/insilicolibrarygeneration", "target_idx": 2}
{"id": "samplesheet_arch_vcf_annotation_pipeline_0_4", "category": "samplesheet_schema", "state": {"technology": "Variant Annotation", "workflow_entry": "ENSEMBLVEP", "library_inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,bam,bai": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "mod_artic_aligntrim_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files. (tools: align_trim)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "artic/minion": "Run the alignment/variant-call/consensus logic of the artic pipeline", "starfusion/detect": "Fast and Accurate Fusion Transcript Detection from RNA-Seq", "gem2/gem2bedmappability": "Convert a mappability file to bedgraph format", "crabs/import": "In-house generated or curated data can be imported into CRABS."}}, "target": "artic/aligntrim", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_4_0", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs for patient tumor and germline normal tissue?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay_type": "PacBio HiFi unaligned BAM variant calling", "data_format": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for PacBio HiFi unaligned BAM variant calling with entry step PBMM2_ALIGN.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "subworkflow_pkg_bam_impute_stitch_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_STITCH", "modules": ["stitch", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using STITCH software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_STITCH (stitch, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_IMPUTE_STITCH": null, "Use nf-core subworkflow bam_impute_stitch": null}}, "target": "Use nf-core subworkflow bam_impute_stitch", "target_idx": 3}
{"id": "schema_std_chipseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/chipseq. Description: ChIP-seq peak-calling, QC and differential analysis pipeline..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/chipseq.", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq_1,fastq_2,replicate,antibody": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "sample,fastq_1,fastq_2,replicate,antibody", "target_idx": 1}
{"id": "resource_bracken_combinebrackenoutputs_1", "category": "resource_profiling", "state": {"process": "BRACKEN_COMBINEBRACKENOUTPUTS", "tool": "bracken/combinebrackenoutputs", "description": "Combine output of metagenomic samples analyzed by bracken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_COMBINEBRACKENOUTPUTS (Combine output of metagenomic samples analyzed by bracken.) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should this step (custom/positionsofint) be packaged: Position of interest depth extraction?", "criteria": {"Leave them out": null, "Use nf-core subworkflow positionsofint": null, "Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 2}
{"id": "samplesheet_arch_ont_metagenome_single_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Long-read Oxford Nanopore environmental metagenomic sequencing. Input files: High molecular weight environmental metagenomic long reads per sampling site.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "mod_lima_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: lima - The PacBio Barcode Demultiplexer and Primer Remover (tools: lima)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gstama_collapse": null, "lima": null, "drep_dereplicate": null, "samtools_calmd": null, "isoseq_refine": null}}, "target": "lima", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_26", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_43", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_subworkflow_structural_blocks_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_5_2", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq.", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "sample,well,fastq": null, "plate,sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "intent_prepare_data_3", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "prepare_data": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 2}
{"id": "mod_raven_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: De novo genome assembler for long uncorrected reads. (tools: raven)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"raven": "De novo genome assembler for long uncorrected reads.", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O", "dastool_scaffolds2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "dastool_dastool": "DAS Tool binning step.", "plink_genome": "Calculates identity-by-descent over autosomal SNPs"}}, "target": "raven", "target_idx": 0}
{"id": "mod_elprep_fastatoelfasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a file in FASTA format to the ELFASTA format (tools: elprep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"graphmap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "last_mafconvert": "Converts MAF alignments in another format.", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "elprep_fastatoelfasta": "Convert a file in FASTA format to the ELFASTA format", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "elprep_fastatoelfasta", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_37", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "field_constraint_sex_0_11", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_31", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Standard Paired-end Whole Genome Sequencing (WGS))", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Standard Paired-end Whole Genome Sequencing (WGS) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_mmseqs_tsv2exprofiledb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Conversion of expandable profile to databases to the MMseqs2 databases format (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiddit/cov": "Computes the coverage of different regions from the bam file.", "mmseqs/tsv2exprofiledb": "Conversion of expandable profile to databases to the MMseqs2 databases format", "mmseqs/createtsv": "Create a tsv file from a query and a target database as well as the result database", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "mmseqs/cluster": "Cluster sequences using MMSeqs2 cluster."}}, "target": "mmseqs/tsv2exprofiledb", "target_idx": 1}
{"id": "pipe_all101_multiplesequencealign_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"slamseq": null, "chipseq": null, "fetchngs": null, "multiplesequencealign": null, "fastquorum": null, "metaboigniter": null, "rnasplice": null, "scrnaseq": null}}, "target": "multiplesequencealign", "target_idx": 3}
{"id": "resource_artic_minion_2", "category": "resource_profiling", "state": {"process": "ARTIC_MINION", "tool": "artic/minion", "description": "Run the alignment/variant-call/consensus logic of the artic pipeline"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_MINION (Run the alignment/variant-call/consensus logic of the artic pipeline) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_43", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bedtools_makewindows_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAKEWINDOWS", "tool": "bedtools/makewindows", "description": "Makes adjacent or sliding windows across a genome or BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAKEWINDOWS (Makes adjacent or sliding windows across a genome or BED file.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_evexplorer_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/evexplorer. Description: nf-core/evexplorer is a pipeline for analyzing RNA data from extracellular vesicles, compatible with technologies such as nextflex, comboSeq, and ONT with further support forthcoming. evexplorer handles QC, expressed region detection, library size normalization and Differential RNA Expression (DRE).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/evexplorer.", "criteria": {"sample,input,output_path,checksum_md5,checksum_sha": null, "sample,fastq_1,fastq_2,batch,condition": null, "id,fasta,reference,optional_data,template": null, "sample_id,name,description,path,path_2": null}}, "target": "sample,fastq_1,fastq_2,batch,condition", "target_idx": 1}
{"id": "field_constraint_status_3_9", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"pattern: ^[A-Z]+$": null, "format: file-path": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "mod_gecco_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This command helps transforming the output files created by\nGECCO into helpful format, should you want to use the results in\ncombination with other tools. (tools: gecco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba/download": null, "gecco/convert": null, "antismash/antismashdownloaddatabases": null, "antismash/antismashlite": null, "damageprofiler": null}}, "target": "gecco/convert", "target_idx": 1}
{"id": "schema_std_callingcards_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/callingcards. Description: A pipeline for processing calling cards data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/callingcards.", "criteria": {"id,path": null, "sample,fastq_1,fastq_2,barcode_details": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null}}, "target": "sample,fastq_1,fastq_2,barcode_details", "target_idx": 1}
{"id": "resource_biscuit_vcf2bed_5", "category": "resource_profiling", "state": {"process": "BISCUIT_VCF2BED", "tool": "biscuit/vcf2bed", "description": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_VCF2BED (Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compl) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "core_tool_macs2_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Model-based analysis of ChIP-Seq data to identify statistically significant transcription factor binding sites and histone mark enrichment peaks.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"homer": "Motif discovery tool", "seacr": "Peak caller", "genrich": "Peak caller", "macs2": "Model-based Analysis of ChIP-Seq (MACS) for identifying transcript factor binding sites", "epic2": "Diffuse domain caller"}}, "target": "macs2", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_37", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_28", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_44", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "noul_container_environment_specification_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_strandedness_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"format: file-path": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_fusionreport_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build DB for fusionreport (tools: fusionreport)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clame": "binning of metagenomic sequences", "csvtk_sort": "Sort  CSV (or TSV) tables", "cellbender_merge": "Module to use CellBender to remove ambient RNA from single-cell RNA-seq data", "smoove_call": "smoove simplifies and speeds calling and genotyping SVs for short reads. It also improves specificity by remov", "fusionreport_download": "Build DB for fusionreport"}}, "target": "fusionreport_download", "target_idx": 4}
{"id": "mod_bedtools_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split BED files into several smaller BED files (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_split": null, "bedtools_flank": null, "plink_bcf": null, "bedtools_coverage": null, "propr_logratio": null}}, "target": "bedtools_split", "target_idx": 0}
{"id": "mod_genometester4_glistmaker_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create and count k-mer lists from nucelotide sequences. (tools: genometester4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genometester4/glistmaker": "Create and count k-mer lists from nucelotide sequences.", "oarfish/alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "metacache/build": "Taxonomic profiling database building with MetaCache", "bedtools/maskfasta": "masks sequences in a FASTA file based on intervals defined in a feature file.", "cobiontid/kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written"}}, "target": "genometester4/glistmaker", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bcftools_call_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CALL", "tool": "bcftools/call", "description": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily lost in the process of transition under htslib, but will be added back on popular demand.\nThe original calling model can be invoked with the -c option."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CALL (This command replaces the former bcftools view caller.\nSome of the original func) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_4_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,tss_bed": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_mira_influenza_sc2_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (custom/mira-nf) for Custom MIRA-NF Influenza / SC2 pipeline. Input files: Paired-end surveillance FASTQs from respiratory pathogen panels.", "question": {"type": "choice", "instructions": "Which columns are standard for Custom MIRA-NF Influenza / SC2 pipeline input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_cnvnator_cnvnator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads. (tools: cnvnator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"icountmini/peaks": "Runs iCount peaks on a BED file of crosslinks", "truvari/bench": "Given baseline and comparison sets of variants, calculate the recall/precision/f-measure", "cnvkit/antitarget": "Derive off-target (“antitarget”) bins from target regions.", "cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "cnvnator/convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format."}}, "target": "cnvnator/cnvnator", "target_idx": 3}
{"id": "mod_segemehl_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate genome indices for segemehl align (tools: segemehl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnaqc": "Quality control of copy number data from bulk WGS assays", "segemehl/index": "Generate genome indices for segemehl align", "bowtie/build": "Create bowtie index for reference genome", "dshbio/splitgff3": "Split features in gzipped GFF3 format", "biscuit/index": "Indexes a reference genome for use with Biscuit"}}, "target": "segemehl/index", "target_idx": 1}
{"id": "pipe_all101_demultiplex_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Demultiplexing pipeline for sequencing data. Topics: bases2fastq, bcl2fastq, demultiplexing, elementbiosciences, illumina. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "seqsubmit": "nf-core pipeline for data submission to ENA", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection"}}, "target": "demultiplex", "target_idx": 5}
{"id": "noul_process_conditional_execution_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_5_3", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/eager, determine the input samplesheet column structure for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_core10_atacseq_2_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? ATAC-seq peak calling with MACS2 and Genrich, QC analysis, and nucleosome-free region identification.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "atacseq", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_31", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_ampcombi2_parsetables_1", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_PARSETABLES", "tool": "ampcombi2/parsetables", "description": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_PARSETABLES (A submodule that parses and standardizes the results from various antimicrobial ) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_fastq_align_dedup_bismark_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align BS-Seq reads to a reference genome using bismark, deduplicate and sort (tools: fastq_align_dedup_bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa/clusterevents": "Cluster events based on PSI values and significantly differentially spliced events using SUPPA2.", "bismark/align": "Performs alignment of BS-Seq reads using bismark", "fastq_align_dedup_bismark": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "centrifuge/centrifuge": "Classifies metagenomic sequence data"}}, "target": "fastq_align_dedup_bismark", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_27", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "subworkflow_pkg_bam_qc_rnaseq_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_RNASEQ", "modules": ["preseq/lcextrap", "qualimap/rnaseq", "dupradar", "subread/featurecounts", "custom/multiqccustombiotype", "samtools/sort", "bam_rseqc"], "description": "Run post-alignment QC tools on RNA-seq BAM files including library complexity"}, "question": {"type": "choice", "instructions": "How should BAM_QC_RNASEQ (preseq/lcextrap, qualimap/rnaseq, dupradar, subread/featurecounts, custom/multiqccustombiotype, samtools/sort, bam_rseqc) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_qc_rnaseq": null, "Local subworkflow BAM_QC_RNASEQ": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_qc_rnaseq", "target_idx": 0}
{"id": "mod_bio2zarr_vcf2zarrconvert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster. (tools: vcf2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "entrezdirect_esummary": "Queries an NCBI database using Unique Identifier(s)", "metaphlan_mergemetaphlantables": "Merges output abundance tables from MetaPhlAn4", "bio2zarr_vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}}, "target": "bio2zarr_vcf2zarrconvert", "target_idx": 4}
{"id": "pipe_all101_crisprseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`).. Topics: crispr, crispr-analysis, crispr-cas, ngs. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnadnavar": null, "pixelator": null, "nanoseq": null, "metaboigniter": null, "proteinannotator": null, "hicar": null, "metatdenovo": null, "crisprseq": null, "differentialabundance": null, "mcmicro": null}}, "target": "crisprseq", "target_idx": 7}
{"id": "samplesheet_arch_metatranscriptome_denovo_6_4", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering", "pipeline": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "Which columns are standard for Environmental community metatranscriptomics de novo assembly input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,rrna_fasta": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "mod_anndata_getsize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file (tools: anndata)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects", "anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file", "rpbp_selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s", "rtgtools_svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs"}}, "target": "anndata_getsize", "target_idx": 2}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_complexity_filter_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_COMPLEXITY_FILTER", "modules": ["prinseqplusplus", "bbmap/bbduk", "fastp"], "description": "Perform low-complexity filtering of FASTQ reads using a selectable tool."}, "question": {"type": "choice", "instructions": "How should FASTQ_COMPLEXITY_FILTER (prinseqplusplus, bbmap/bbduk, fastp) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_complexity_filter": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_COMPLEXITY_FILTER": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_complexity_filter", "target_idx": 0}
{"id": "resource_bedtools_shuffle_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHUFFLE", "tool": "bedtools/shuffle", "description": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a genome file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHUFFLE (bedtools shuffle will randomly permute the genomic locations of a feature file a) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bismark_report_2", "category": "resource_profiling", "state": {"process": "BISMARK_REPORT", "tool": "bismark/report", "description": "Collects bismark alignment reports"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_REPORT (Collects bismark alignment reports) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_8_0", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin", "pipeline": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metatdenovo", "assay_type": "Environmental community metatranscriptomics de novo assembly", "data_format": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Environmental community metatranscriptomics de novo assembly with entry step FASTQC.", "criteria": {"sample,rrna_fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/dualrnaseq --input samplesheet.csv (Assay: Dual RNA-seq simultaneous host and pathogen transcriptomics)", "question": {"type": "choice", "instructions": "Which columns are standard for Dual RNA-seq simultaneous host and pathogen transcriptomics input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,host_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_2_5", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,well,fastq": null, "plate,sample,bam": null, "sample,matrix": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_1_4", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,unite_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq with strandedness. Input files: Paired-end FASTQ reads with library strandedness.", "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "noul_dynamic_resource_allocation_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_variantprioritization_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR).. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantprioritization": null, "pacvar": null, "rnastructurome": null, "seqinspector": null, "nanostring": null}}, "target": "variantprioritization", "target_idx": 0}
{"id": "mod_fasta_index_dna_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate aligner index for a reference genome.\nPlease note, this workflow requires input CHANNELS. Input values will cause errors (tools: fasta_index_dna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_index_dna": "Generate aligner index for a reference genome.\nPlease note, this workflow requires input CHANNELS. Input value", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "salmon/index": "Create index for salmon", "spaceranger/count": "Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data"}}, "target": "fasta_index_dna", "target_idx": 0}
{"id": "core_tool_macs2_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Model-based analysis of ChIP-Seq data to identify statistically significant transcription factor binding sites and histone mark enrichment peaks.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"epic2": "Diffuse domain caller", "homer": "Motif discovery tool", "genrich": "Peak caller", "macs2": "Model-based Analysis of ChIP-Seq (MACS) for identifying transcript factor binding sites", "seacr": "Peak caller"}}, "target": "macs2", "target_idx": 3}
{"id": "mod_llamacpppython_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Python wrapper for running locally-hosted LLM with llama.cpp (tools: llama-cpp-python)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_makeblastdb": null, "popscle_dscpileup": null, "huggingface_download": null, "llamacpppython_run": null, "stranger": null}}, "target": "llamacpppython_run", "target_idx": 3}
{"id": "samplesheet_arch_ont_direct_rna_se_3_0", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Oxford Nanopore direct RNA with entry step NANOPLOT.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fast5": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_5_3", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pre-aligned BAM variant calling pipeline.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_32", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_hifitrimmer_filterbam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLAST against\nadapter sequences. Primary output is filtered FASTA/FASTQ. (tools: hifi_trimmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canu": null, "hmmer_hmmfetch": null, "traitar_run": null, "hifiadapterfilt_hifiadapterfilt": null, "hifitrimmer_filterbam": null}}, "target": "hifitrimmer_filterbam", "target_idx": 4}
{"id": "mod_fgumi_simplex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls simplex consensus sequences from reads with the same unique molecular tag.\nThis is a high-performance replacement for fgbio CallMolecularConsensusReads. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "fgumi/simplex": "Calls simplex consensus sequences from reads with the same unique molecular tag.\nThis is a high-performance re", "flash": "Perform merging of mate paired-end sequencing reads", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "fgbio/callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub"}}, "target": "fgumi/simplex", "target_idx": 1}
{"id": "mod_mirdeep2_mapper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: miRDeep2 Mapper is a tool that prepares deep sequencing reads for downstream miRNA detection by collapsing reads, mapping them to a genome, and outputting the required files for miRNA discovery. (tools: mirdeep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirdeep2_mapper": null, "vcftools": null, "mapad_map": null, "mashmap": null, "scanpy_scrublet": null}}, "target": "mirdeep2_mapper", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_30", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_amrfinderplus_run_5", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_RUN", "tool": "amrfinderplus/run", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_RUN (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_sambamba_flagstat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Outputs some statistics drawn from read flags. (tools: sambamba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "isoseq3_tag": "Extract UMI and cell barcodes", "wipertools_fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files", "bcftools_plotvcfstats": "Plots the output of bcftools stats", "sambamba_flagstat": "Outputs some statistics drawn from read flags."}}, "target": "sambamba_flagstat", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_taxonomic_profile_metaphlan_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TAXONOMIC_PROFILE_METAPHLAN", "modules": ["metaphlan/makedb", "metaphlan/metaphlan", "metaphlan/mergemetaphlantables"], "description": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn"}, "question": {"type": "choice", "instructions": "How should FASTQ_TAXONOMIC_PROFILE_METAPHLAN (metaphlan/makedb, metaphlan/metaphlan, metaphlan/mergemetaphlantables) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_taxonomic_profile_metaphlan": null, "Local subworkflow FASTQ_TAXONOMIC_PROFILE_METAPHLAN": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_taxonomic_profile_metaphlan", "target_idx": 0}
{"id": "resource_bcftools_pluginvcf2table_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINVCF2TABLE", "tool": "bcftools/pluginvcf2table", "description": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output as one row, with INFO and FORMAT fields as columns."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINVCF2TABLE (Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table ) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_racon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Consensus module for raw de novo DNA assembly of long uncorrected reads (tools: racon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": null, "racon": null, "stacks_refmap": null, "fasta_build_add_kraken2_bracken": null, "abricate_run": null}}, "target": "racon", "target_idx": 1}
{"id": "resource_ampcombi_2", "category": "resource_profiling", "state": {"process": "AMPCOMBI", "tool": "ampcombi", "description": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI (A tool to parse and summarise results from antimicrobial peptides tools and pres) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gatk4_printreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Print reads in the SAM/BAM/CRAM file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_splitmerge": "split single end read groups by length and merge paired end reads", "whatshap_haplotag": "Tag reads by haplotype", "utils_references": "Functionality for dealing with references that may be useful for any Nextflow pipeline", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "gatk4_printreads": "Print reads in the SAM/BAM/CRAM file"}}, "target": "gatk4_printreads", "target_idx": 4}
{"id": "mod_leehom_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bayesian reconstruction of ancient DNA fragments (tools: leehom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen", "leehom": "Bayesian reconstruction of ancient DNA fragments", "ripgrep": "ripgrep recursively searches directories for a regex pattern", "vsearch/sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength)."}}, "target": "leehom", "target_idx": 2}
{"id": "mod_emboss_cons_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence weights and a scoring matrix are used to calculate a score for each amino acid residue or nucleotide at each position in the alignment. (tools: emboss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "autocycler_combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "emboss_cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "irescue": "Quantification of transposable elements expression in scRNA-seq"}}, "target": "emboss_cons", "target_idx": 2}
{"id": "schema_std_cutandrun_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay": "cutandrun pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/cutandrun (Analysis pipeline for CUT&RUN and CUT&TAG experiments that i)?", "criteria": {"fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2,bam,bai": null}}, "target": "fastq_1,fastq_2,group,replicate,control", "target_idx": 2}
{"id": "mod_sentieon_coveragemetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accelerated implementation of the GATK DepthOfCoverage tool. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "bbmap_pileup": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file.", "bedtools_coverage": "computes both the depth and breadth of coverage of features in file B on the features in file A", "sentieon_coveragemetrics": "Accelerated implementation of the GATK DepthOfCoverage tool.", "fastx_collapser": "Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts)"}}, "target": "sentieon_coveragemetrics", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_1_4", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fusion_bed": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "pipe_all101_riboseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for riboseq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "metapep": "From metagenomes to epitopes and beyond", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "riboseq", "target_idx": 5}
{"id": "samplesheet_arch_metagenome_mag_grouped_1_3", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "mod_fastavalidator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: \"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror log upon validation failure.\" (tools: fasta_validate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus_update": null, "crabs_insilicopcr": null, "opt_flip_track_stat": null, "any2fasta": null, "fastavalidator": null}}, "target": "fastavalidator", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_bracken_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2_BRACKEN", "modules": ["kraken2/add", "kraken2/build", "bracken/build"], "description": "KRAKEN2 and BRACKEN build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2_BRACKEN (kraken2/add, kraken2/build, bracken/build) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTA_BUILD_ADD_KRAKEN2_BRACKEN": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_build_add_kraken2_bracken": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2_bracken", "target_idx": 3}
{"id": "pipe_all101_multiplesequencealign_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for multiplesequencealign. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]"}}, "target": "multiplesequencealign", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_5_5", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: 10x Multiome single-cell joint RNA and ATAC chromatin.", "criteria": {"sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "mod_backsub_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data. (tools: backsub)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging_macsima2mc": "Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO.", "muse_call": "pre-filtering and calculating position-specific summary statistics using the Markov substitution model", "kma_index": "This module wraps the index module of the KMA alignment tool.", "mcquant": "Mcquant extracts single-cell data given a multi-channel image and a segmentation mask.", "backsub": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data."}}, "target": "backsub", "target_idx": 4}
{"id": "resource_anndata_barcodes_2", "category": "resource_profiling", "state": {"process": "ANNDATA_BARCODES", "tool": "anndata/barcodes", "description": "Module to subset AnnData object to cells with matching barcodes from the csv file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_BARCODES (Module to subset AnnData object to cells with matching barcodes from the csv fil) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_1_3", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"sample,timepoint,fastq": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_links_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by Oxford Nanopore Technologies Ltd.\nIt can be used to scaffold high-quality draft genome assemblies with any long sequences\n(eg. ONT reads, PacBio reads, other draft genomes, etc).\nIt is also used to scaffold contig pairs linked by ARCS/ARKS.\nThis module is for LINKS >=2.0.0 and does not support MPET input. (tools: links)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vclust/cluster": "Vclust cluster performs threshold-based clustering by assigning a genome sequence to a cluster if its similari", "vclust/align": "The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like", "seqfu/derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th", "kaiju/kaiju2krona": "Convert Kaiju's tab-separated output file into a tab-separated text file which can be imported into Krona.", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O"}}, "target": "links", "target_idx": 4}
{"id": "mod_dragen_germline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The DRAGEN DNA Germline Pipeline accelerates the secondary analysis of NGS data by harnessing the tremendous power available on the DRAGEN Platform. The pipeline includes highly optimized algorithms for mapping, aligning, sorting, duplicate marking, and haplotype variant calling. In addition to haplotype variant calling, the pipeline supports calling of copy number and structural variants as well as detection of repeat expansions and targeted calls. (tools: dragen)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_qc_stats": "Generate statistics for short read sequencing data using multiple tools", "fastq_fastqc_umitools_fastp": "Read QC, UMI extraction and trimming", "dragen_germline": "The DRAGEN DNA Germline Pipeline accelerates the secondary analysis of NGS data by harnessing the tremendous p", "tcoffee_align": "Aligns sequences using T_COFFEE", "mudskipper_index": "Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM fi"}}, "target": "dragen_germline", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_5_4", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: ATAC-seq chromatin accessibility with biological replicates.", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "mod_seqtk_mergepe_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Interleave pair-end reads from FastQ files (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_merge": null, "hpsuissero": null, "tetranscripts": null, "seqtk_mergepe": null, "concoct_extractfastabins": null}}, "target": "seqtk_mergepe", "target_idx": 3}
{"id": "resource_bcftools_consensus_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONSENSUS", "tool": "bcftools/consensus", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONSENSUS (Compresses VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_plink2_score_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a scoring system to each sample in a plink 2 fileset (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mykrobe_predict": "AMR predictions for supported species", "plink2_filter": "Filters plink bfiles or pfiles with filters such as maf or var", "plink2_score": "Apply a scoring system to each sample in a plink 2 fileset", "plink2_indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium", "foldmason_easymsa": "Aligns protein structures using foldmason"}}, "target": "plink2_score", "target_idx": 2}
{"id": "field_constraint_sex_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_hmmsearch_rank_fastas_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_HMMSEARCH_RANK_FASTAS", "modules": ["hmmer/hmmsearch", "hmmer/hmmrank", "seqtk/subseq"], "description": "Run hmmsearch and output separate fasta files for top scoring hits to each profile"}, "question": {"type": "choice", "instructions": "How should FASTA_HMMSEARCH_RANK_FASTAS (hmmer/hmmsearch, hmmer/hmmrank, seqtk/subseq) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTA_HMMSEARCH_RANK_FASTAS": null, "Use nf-core subworkflow fasta_hmmsearch_rank_fastas": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_hmmsearch_rank_fastas", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_0", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_holodeck_eval_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment accuracy of holodeck-simulated reads (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ale": "ALE: assembly likelihood estimator.", "fgumi/zipper": "Zip an unmapped UMI BAM together with its aligned BAM using fgumi", "holodeck/eval": "Evaluate alignment accuracy of holodeck-simulated reads", "survivor/simsv": "Simulate an SV VCF file based on a reference genome", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference."}}, "target": "holodeck/eval", "target_idx": 2}
{"id": "mod_gatk4_revertsam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reverts SAM or BAM files to a previous state. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/revertsam": "Reverts SAM or BAM files to a previous state.", "vcontact3/prepareddatabases": "Prepare and format databases for vCONTACT3 viral taxonomic analysis", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4/mergemutectstats": "Merges mutect2 stats generated on different intervals/regions"}}, "target": "gatk4/revertsam", "target_idx": 0}
{"id": "mod_mageck_mle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: maximum-likelihood analysis of gene essentialities computation (tools: mageck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clame": "binning of metagenomic sequences", "bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "caddsv/run": "Score structural variants with CADD-SV.", "mageck/mle": "maximum-likelihood analysis of gene essentialities computation", "bedtools/intersect": "Allows one to screen for overlaps between two sets of genomic features."}}, "target": "mageck/mle", "target_idx": 3}
{"id": "mod_memote_report_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate HTML quality report snapshot for genome-scale metabolic models (tools: memote)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spring_compress": "Fast, efficient, lossless compression of FASTQ files.", "memote_report": "Generate HTML quality report snapshot for genome-scale metabolic models", "qualimap_bamqccram": "Evaluate alignment data", "gapseq_doall": "Complete gapseq workflow from genome to gap-filled model", "gapseq_medium": "Predict growth medium from a draft model and pathway predictions"}}, "target": "memote_report", "target_idx": 1}
{"id": "resource_blast_blastp_5", "category": "resource_profiling", "state": {"process": "BLAST_BLASTP", "tool": "blast/blastp", "description": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTP (BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (prot) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic tumor-normal calling from pre-aligned BAM files)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic tumor-normal calling from pre-aligned BAM files with entry step MUTECT2.", "criteria": {"patient,sample,status,bam,bai": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "schema_std_references_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/references", "assay": "references pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/references (nf-core/references is a bioinformatics pipeline that build r)?", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "vcf,fasta,genome,site,source": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,group,path,ref,method": null}}, "target": "vcf,fasta,genome,site,source", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Multi-lane Illumina sequencing run of clinical samples", "data_format": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/pacvar --input samplesheet.csv (Assay: PacBio HiFi unaligned BAM variant calling)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "schema_std_taxprofiler_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "assay": "taxprofiler pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/taxprofiler (Highly parallelised multi-taxonomic profiling of shotgun sho)?", "criteria": {"sample,fastq_1,fastq_2,replicate,antibody": null, "sample,trait,pascal,twas,additional_sources": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 2}
{"id": "resource_bamtools_split_5", "category": "resource_profiling", "state": {"process": "BAMTOOLS_SPLIT", "tool": "bamtools/split", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_SPLIT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_32", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_cageseq_transcription_1_4", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,tss_bed": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "noul_container_environment_specification_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_3_0", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pre-aligned BAM variant calling pipeline with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "mod_expansionhunterdenovo_profile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute genome-wide STR profile (tools: expansionhunterdenovo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmstat": null, "fusioncatcher/fusioncatcher": null, "expansionhunterdenovo/profile": null, "purgedups/getseqs": null, "hmmer/hmmalign": null}}, "target": "expansionhunterdenovo/profile", "target_idx": 2}
{"id": "resource_assemblyscan_4", "category": "resource_profiling", "state": {"process": "ASSEMBLYSCAN", "tool": "assemblyscan", "description": "Assembly summary statistics in JSON format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASSEMBLYSCAN (Assembly summary statistics in JSON format) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_pbtk_pbmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simple tool which merges several PacBio BAM files together (tools: pbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "macs2/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "pbtk/pbmerge": "Simple tool which merges several PacBio BAM files together"}}, "target": "pbtk/pbmerge", "target_idx": 4}
{"id": "noul_modular_subworkflow_composition_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_strandedness_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null, "pattern: ^[0-9]+$": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "mod_gunzip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses and decompresses files. (tools: gunzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat_cat": "A module for concatenation of gzipped or uncompressed files", "sawfish_discover": "SV candidate discovery from PacBio HiFi data", "gunzip": "Compresses and decompresses files.", "samtools_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "foldcomp_compress": "Efficient compression tool for protein structures"}}, "target": "gunzip", "target_idx": 2}
{"id": "mod_hmmer_hmmfetch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: extract hmm from hmm database file or create index for hmm database (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmfetch": null, "somalier_extract": null, "srst2_srst2": null, "hmmer_hmmemit": null, "hmmer_hmmstat": null}}, "target": "hmmer_hmmfetch", "target_idx": 0}
{"id": "schema_std_variantprioritization_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/variantprioritization", "description": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR).", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/variantprioritization?", "criteria": {"ID,R1,R2,LongFastQ,Fast5": null, "id,raw_file": null, "sample,bam,bai": null, "patient,sample,vcf,status,cna": null}}, "target": "patient,sample,vcf,status,cna", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_5_4", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnafusion, determine the input samplesheet column structure for: RNA gene fusion detection (Arriba, STAR-Fusion).", "criteria": {"sample,fusion_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "resource_busco_busco_0", "category": "resource_profiling", "state": {"process": "BUSCO_BUSCO", "tool": "busco/busco", "description": "Benchmarking Universal Single Copy Orthologs"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_BUSCO (Benchmarking Universal Single Copy Orthologs) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gecco_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This command helps transforming the output files created by\nGECCO into helpful format, should you want to use the results in\ncombination with other tools. (tools: gecco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fq_lint": "fq lint is a FASTQ file pair validator.", "gecco_convert": "This command helps transforming the output files created by\nGECCO into helpful format, should you want to use ", "gem3_gem3indexer": "Create a GEM index from a FASTA file", "antismash_antismashlite": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters"}}, "target": "gecco_convert", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_2", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_isoseq3_tag_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract UMI and cell barcodes (tools: isoseq3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xeniumranger/relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts.", "gstama/merge": "Merge multiple transcriptomes while maintaining source information.", "isoseq3/tag": "Extract UMI and cell barcodes", "gstama/polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information."}}, "target": "isoseq3/tag", "target_idx": 2}
{"id": "mod_odgi_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi/unchop": "Merge unitigs into a single node preserving the node order.", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format", "krona/ktimportkrona": "Collect multiple krona reports into a single html file", "sentieon/tnscope": "TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, us", "odgi/sort": "Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm."}}, "target": "odgi/sort", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_2_31", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq with strandedness. Input files: Paired-end FASTQ reads with library strandedness.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "pipe_all101_pangenome_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609.. Topics: pangenome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel"}}, "target": "pangenome", "target_idx": 4}
{"id": "mod_pneumocat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine Streptococcus pneumoniae serotype from Illumina paired-end reads (tools: pneumocat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "expansionhunterdenovo_merge": "Merge STR profiles into a multi-sample STR profile", "pneumocat": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "fastq_index_filter_deacon": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with"}}, "target": "pneumocat", "target_idx": 2}
{"id": "mod_megan_rma2info_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analyses an RMA file and exports information in text format (tools: megan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"megan/daa2info": "Analyses a DAA file and exports information in text format", "megan/rma2info": "Analyses an RMA file and exports information in text format", "fastavalidator": "\"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror lo", "emu/abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads.", "bbmap/sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}}, "target": "megan/rma2info", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_newick_epang_gappa_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_NEWICK_EPANG_GAPPA", "modules": ["hmmer/hmmbuild", "hmmer/hmmalign", "hmmer/eslalimask", "hmmer/eslreformat", "clustalo/align", "mafft/align", "epang/place", "epang/split", "gappa/examinegraft", "gappa/examineassign", "gappa/examineheattree"], "description": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in nf-core/phyloplace."}, "question": {"type": "choice", "instructions": "How should FASTA_NEWICK_EPANG_GAPPA (hmmer/hmmbuild, hmmer/hmmalign, hmmer/eslalimask, hmmer/eslreformat, clustalo/align, mafft/align, epang/place, epang/split, gappa/examinegraft, gappa/examineassign, gappa/examineheattree) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_NEWICK_EPANG_GAPPA": null, "Use nf-core subworkflow fasta_newick_epang_gappa": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_newick_epang_gappa", "target_idx": 1}
{"id": "intent_prepare_data_5", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "prepare_data": null, "build_pipeline": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_20", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_spaceranger_mkgtf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build a filtered GTF needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkgtf command. (tools: spaceranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie/align": null, "skesa": null, "gatk4/variantstotable": null, "spaceranger/mkgtf": null, "bbmap/align": null}}, "target": "spaceranger/mkgtf", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_2", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_purgedups_histplot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots the read coverage from a purge dups statistics file and cutoffs. (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purgedups_pbcstat": "Create read depth histogram and base-level read depth for an assembly based on pacbio data", "cnvkit_coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "strdrop_build": "Build reference json from sequencing coverage in STR VCFs", "samtools_convert": "convert and then index CRAM -> BAM or BAM -> CRAM file", "purgedups_histplot": "Plots the read coverage from a purge dups statistics file and cutoffs."}}, "target": "purgedups_histplot", "target_idx": 4}
{"id": "samplesheet_arch_cageseq_transcription_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cageseq", "assay_type": "CAGE-seq 5-prime capped transcript end sequencing", "data_format": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,tss_bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_proteomics_dia_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diaproteomics", "assay_type": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "data_format": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Data-Independent Acquisition (DIA) quantitative mass spectrometry with entry step INPUT_CHECK.", "criteria": {"sample,peptides_tsv": null, "sample,mzml": null, "sample,fasta": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "field_constraint_expected_cells_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"enum: [auto, single, paired]": null, "format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_15", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "intent_ask_question_2", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 0}
{"id": "mod_mcquant_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mcquant extracts single-cell data given a multi-channel image and a segmentation mask. (tools: mcquant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcquant": "Mcquant extracts single-cell data given a multi-channel image and a segmentation mask.", "fgbio/fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI", "oarfish/alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "jellyfish/count": "Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm", "oarfish/readprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Splic"}}, "target": "mcquant", "target_idx": 0}
{"id": "mod_cobiontid_kmercounter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written with downstream processing with Tensorflow\nor numpy in mind. (tools: kmer-counter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cobiontid/kmercounter": null, "roary": null, "concoct/concoct": null, "cellranger/mkgtf": null, "metacache/build": null}}, "target": "cobiontid/kmercounter", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral amplicon sequencing with primers", "data_format": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Viral amplicon sequencing with primers input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_1_3", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1": null, "sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "samplesheet_arch_bulk_small_rna_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/smrnaseq", "assay_type": "Small RNA / miRNA sequencing", "data_format": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,mirna_id": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_plink_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subset plink bfiles with a text file of variant identifiers (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "umitools_extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "bam_qc_rnaseq": "Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC ", "plink_missing": "Compute sample-based and variant-based missing genotype rates and write a new PLINK binary fileset", "plink_extract": "Subset plink bfiles with a text file of variant identifiers"}}, "target": "plink_extract", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_bam_5_4", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic tumor-normal calling from pre-aligned BAM files.", "criteria": {"sample,vcf": null, "patient,sample,bam": null, "patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_38", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_sample_0_9", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"type: integer": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "subworkflow_pkg_bam_markduplicates_samtools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_SAMTOOLS", "modules": ["samtools/collate", "samtools/fixmate", "samtools/sort", "samtools/markdup"], "description": "Samtools markduplicate SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_SAMTOOLS (samtools/collate, samtools/fixmate, samtools/sort, samtools/markdup) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_markduplicates_samtools": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_MARKDUPLICATES_SAMTOOLS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_markduplicates_samtools", "target_idx": 0}
{"id": "schema_std_detaxizer_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/detaxizer", "description": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/detaxizer?", "criteria": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null}}, "target": "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/chipseq --input samplesheet.csv (Assay: ChIP-seq with IP and input control design)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_dna_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DNA", "modules": ["bowtie2/align", "bwa/mem", "bwamem2/mem", "dragmap/align", "snapaligner/align", "strobealign"], "description": "Align fastq files to a reference genome"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DNA (bowtie2/align, bwa/mem, bwamem2/mem, dragmap/align, snapaligner/align, strobealign) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_dna": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_DNA": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_dna", "target_idx": 0}
{"id": "pipe_core10_ampliseq_2_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Targeted microbial marker gene profiling across environmental microbiome samples.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr"}}, "target": "ampliseq", "target_idx": 8}
{"id": "mod_modkit_repair_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Repair the MM/ML tags on trimmed or hard-clipped ONT reads using untrimmed ONT reads. (tools: modkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "saltshaker_call": "mtDNA deletion and duplication calling downstream of mitosalt", "fasta_index_dna": "Generate aligner index for a reference genome.\nPlease note, this workflow requires input CHANNELS. Input value", "modkit_repair": "Repair the MM/ML tags on trimmed or hard-clipped ONT reads using untrimmed ONT reads.", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali"}}, "target": "modkit_repair", "target_idx": 3}
{"id": "resource_amulety_embed_5", "category": "resource_profiling", "state": {"process": "AMULETY_EMBED", "tool": "amulety/embed", "description": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_EMBED (A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) ) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_explore_search_plot_tidk_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_EXPLORE_SEARCH_PLOT_TIDK", "modules": ["seqkit/seq", "seqkit/sort", "tidk/explore", "tidk/plot", "tidk/search"], "description": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats"}, "question": {"type": "choice", "instructions": "How should FASTA_EXPLORE_SEARCH_PLOT_TIDK (seqkit/seq, seqkit/sort, tidk/explore, tidk/plot, tidk/search) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_EXPLORE_SEARCH_PLOT_TIDK": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_explore_search_plot_tidk": null}}, "target": "Use nf-core subworkflow fasta_explore_search_plot_tidk", "target_idx": 3}
{"id": "mod_abritamr_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes (tools: abritamr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "elprep/split": "Split bam file into manageable chunks", "fasta_index_bismark_bwameth": "Generate index files from reference fasta for bismark and bwameth"}}, "target": "abritamr/run", "target_idx": 2}
{"id": "field_constraint_fastq_2_0_8", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "resource_bismark_genomepreparation_2", "category": "resource_profiling", "state": {"process": "BISMARK_GENOMEPREPARATION", "tool": "bismark/genomepreparation", "description": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_GENOMEPREPARATION (Converts a specified reference genome into two different bisulfite\nconverted ver) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_ont_metagenome_single_0_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "NANOPLOT", "library_inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_bcftools_pluginsetgt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that. (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bcftools/convert": "Converts certain output formats to VCF", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "wget": "The non-interactive network downloader"}}, "target": "bcftools/pluginsetgt", "target_idx": 0}
{"id": "field_constraint_sample_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null, "enum: [0, 1]": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_4_0", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end tiled viral amplicon FASTQs per clinical swab sample?", "criteria": {"sample,fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Tumor-only somatic variant calling without matched normal. Input files: Paired-end FASTQ reads from tumor biopsy without matched normal.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Tumor-only somatic variant calling without matched normal.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bracken_combinebrackenoutputs_0", "category": "resource_profiling", "state": {"process": "BRACKEN_COMBINEBRACKENOUTPUTS", "tool": "bracken/combinebrackenoutputs", "description": "Combine output of metagenomic samples analyzed by bracken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_COMBINEBRACKENOUTPUTS (Combine output of metagenomic samples analyzed by bracken.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_29", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_3_2", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 16S rRNA / ITS microbiome amplicon profiling with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,primer_fwd,primer_rev": null, "sample,otu_table": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_3_2", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Dual RNA-seq simultaneous host and pathogen transcriptomics with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "noul_executor_support_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_exit_code_137_cause_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_homer_maketagdirectory_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a tag directory with the HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hapibd": "The hap-ibd program detects identity-by-descent (IBD) segments and homozygosity-by-descent (HBD) segments in p", "homer_makeucscfile": "Create a UCSC bed graph with the HOMER suite", "homer_maketagdirectory": "Create a tag directory with the HOMER suite", "homer_findpeaks": "Find peaks with HOMER suite", "chromap_chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap."}}, "target": "homer_maketagdirectory", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_31", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/genomeassembler --input samplesheet.csv (Assay: Long-read Pacific Biosciences HiFi sequencing)", "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Pacific Biosciences HiFi sequencing input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_21", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_octopusv_stat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarize structural variant statistics from octopusv SVCF files (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"octopusv/svcf2bed": null, "svanalyzer/svbenchmark": null, "octopusv/stat": null, "rpbp/selectperiodicoffsets": null, "samshee": null}}, "target": "octopusv/stat", "target_idx": 2}
{"id": "resource_baysor_run_3", "category": "resource_profiling", "state": {"process": "BAYSOR_RUN", "tool": "baysor/run", "description": "Bayesian segmentation of spatial transcriptomics data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_RUN (Bayesian segmentation of spatial transcriptomics data.) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should POSITIONSOFINT (custom/positionsofint) be built?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow POSITIONSOFINT": null, "Use nf-core subworkflow positionsofint": null, "Leave them out": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 1}
{"id": "field_constraint_phenotype_3_2", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"format: file-path": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "mod_openms_peakpickerhires_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool for peak detection in high-resolution profile data (Orbitrap or FTICR) (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_filefilter": "Filters peptide/protein identification results by different criteria.", "gcta_keep": "Apply a keep file to a dense GRM using `gcta --keep`", "gatk4_samtofastq": "Converts BAM/SAM file to FastQ format", "quantmsutils_mzmlstatistics": "Generate statistics from mzML files using quantms-utils", "openms_peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)"}}, "target": "openms_peakpickerhires", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_29", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_8_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic tumor-normal calling from pre-aligned BAM files", "data_format": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"patient,sample,bam": null, "sample,vcf": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "mod_bowtie_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bowtie (tools: bowtie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/collectalignmentsummarymetrics": "Collect metrics about the alignment summary of a paired-end library.", "deepmased/predict": "DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "bowtie/align": "Align reads to a reference genome using bowtie", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap"}}, "target": "bowtie/align", "target_idx": 3}
{"id": "mod_finaletoolkit_delfi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the DELFI scores (Cristiano et al., 2019) from a BAM file. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_stats": "Generates stats from VCF files", "alignoth": "Creating alignment plots from bam files", "gatk4_mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "finaletoolkit_delfi": "Calculate the DELFI scores (Cristiano et al., 2019) from a BAM file."}}, "target": "finaletoolkit_delfi", "target_idx": 4}
{"id": "noul_named_output_channel_access_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bedtools_bamtobed_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_BAMTOBED", "tool": "bedtools/bamtobed", "description": "Converts a bam file to a bed12 file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_BAMTOBED (Converts a bam file to a bed12 file.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_bwafastalign_mem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA-FastAlign. (tools: bwafastalign)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stadeniolib/scramble": null, "drep/dereplicate": null, "bwafastalign/mem": null, "sentieon/bwamem": null, "bwamem3/mem": null}}, "target": "bwafastalign/mem", "target_idx": 2}
{"id": "mod_shigapass_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ShigaPass is an in silico tool used to predict Shigella serotypes and to differentiate between Shigella, EIEC (Enteroinvasive E. coli), and non Shigella/EIEC using assembled whole genomes. (tools: shigapass)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"taxonkit/name2taxid": null, "amrfinderplus/update": null, "antismash/antismash": null, "shigapass": null, "bam_telomere_estimation": null}}, "target": "shigapass", "target_idx": 3}
{"id": "resource_agat_spaddintrons_3", "category": "resource_profiling", "state": {"process": "AGAT_SPADDINTRONS", "tool": "agat/spaddintrons", "description": "Add intron features to gtf/gff file without intron features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPADDINTRONS (Add intron features to gtf/gff file without intron features.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_bai_1_8", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "mod_sentieon_bwamem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using Sentieon's BWA MEM (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt_decompose": "decomposes multiallelic variants into biallelic in a VCF file.", "malt_run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "sentieon_bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA", "bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign."}}, "target": "sentieon_bwamem", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Genome analysis from reference-compressed CRAM files. Input files: Coordinate-sorted CRAM alignments with companion CRAI indexes.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,cram": null, "sample,cram,crai": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "schema_std_multiplesequencealign_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/multiplesequencealign. Description: A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/multiplesequencealign.", "criteria": {"id,fasta,reference,optional_data,template": null, "sample,fasta": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2,bam,bai": null}}, "target": "id,fasta,reference,optional_data,template", "target_idx": 0}
{"id": "mod_varscan_processsomatic_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, and copy number variations in both somatic and germline samples. It is particularly useful for analyzing tumor/normal sample pairs. This subtool divides variants based on status (germline, somatic, loss of heterozygosity) and confidence level (high-confidence or not) and outputs them in separate VCF files. (tools: varscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "deeparg_predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "faa_seqfu_seqkit": "Subworkflow that optionally preprocesses amino acid FASTA sequences\n(seqkit seq/replace/rmdup), computes seque", "varscan_processsomatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "varscan_processsomatic", "target_idx": 3}
{"id": "noul_channel_filter_operator_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_trgt_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge TRGT VCFs from multiple samples (tools: trgt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trgt/genotype": "Tandem repeat genotyping from PacBio HiFi data", "cellranger/mkvdjref": "Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref co", "hmmer/eslsfetch": "Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. T", "trgt/merge": "Merge TRGT VCFs from multiple samples", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database"}}, "target": "trgt/merge", "target_idx": 3}
{"id": "intent_ask_question_23", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "ask_question": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 2}
{"id": "schema_std_genephylomodeler_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genephylomodeler", "assay": "genephylomodeler pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/genephylomodeler (A bioinformatics pipeline that fits evolutionary models and )?", "criteria": {"sample_id,mapped,index,file_type": null, "gene_name,alignment,tree,suite,tool": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,strandedness": null}}, "target": "gene_name,alignment,tree,suite,tool", "target_idx": 1}
{"id": "resource_bedtools_getfasta_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GETFASTA", "tool": "bedtools/getfasta", "description": "extract sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GETFASTA (extract sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_vcf2maf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: vcf2maf (tools: vcf2maf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"s4pred_runmodel": "Prediction of a protein's secondary structure from its amino acid sequence", "vcf2maf": "vcf2maf", "gatk4_determinegermlinecontigploidy": "Determines the baseline contig ploidy for germline samples given counts data", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "vcf2maf", "target_idx": 1}
{"id": "resource_any2fasta_1", "category": "resource_profiling", "state": {"process": "ANY2FASTA", "tool": "any2fasta", "description": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input files may be gzip, bzip2, zip, or zstd compressed."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANY2FASTA (Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_affy_justrma_3", "category": "resource_profiling", "state": {"process": "AFFY_JUSTRMA", "tool": "affy/justrma", "description": "Read CEL files into an ExpressionSet and generate a matrix"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AFFY_JUSTRMA (Read CEL files into an ExpressionSet and generate a matrix) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_falco_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run falco on sequenced reads (tools: fastqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification.", "hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "falco": "Run falco on sequenced reads", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "falco", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_0", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_cellranger_multi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's pipelines to analyze sequencing data produced from various Chromium technologies, including Single Cell Gene Expression, Single Cell Immune Profiling, Feature Barcoding, and Cell Multiplexing. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_cluster": null, "cellranger_multi": null, "bbmap_align": null, "bakta_baktadbdownload": null, "dshbio_filterbed": null}}, "target": "cellranger_multi", "target_idx": 1}
{"id": "resource_amulety_esm2_0", "category": "resource_profiling", "state": {"process": "AMULETY_ESM2", "tool": "amulety/esm2", "description": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ESM2 (A module to create esm2 embeddings of antibody (BCR) amino acid sequences using ) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_index_bismark_bwameth_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_BISMARK_BWAMETH", "modules": ["untar", "gunzip", "bismark/genomepreparation", "bwameth/index", "samtools/faidx"], "description": "Generate index files from reference fasta for bismark and bwameth"}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_BISMARK_BWAMETH (untar, gunzip, bismark/genomepreparation, bwameth/index, samtools/faidx) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_index_bismark_bwameth": null, "Local subworkflow FASTA_INDEX_BISMARK_BWAMETH": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_index_bismark_bwameth", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cageseq) for CAGE-seq 5-prime capped transcript end sequencing. Input files: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,tss_bed": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_19", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_abra2_0", "category": "resource_profiling", "state": {"process": "ABRA2", "tool": "abra2", "description": "Assembly Based ReAligner for next-generation sequencing data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRA2 (Assembly Based ReAligner for next-generation sequencing data) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_rnasplice_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnasplice", "assay": "rnasplice pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnasplice (rnasplice is a bioinformatics pipeline for RNA-seq alternati)?", "criteria": {"sample,bundle,image": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,vcf,tbi": null}}, "target": "sample,fastq_1,fastq_2,strandedness,condition", "target_idx": 2}
{"id": "pipe_all101_rnaseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for rna. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]"}}, "target": "rnaseq", "target_idx": 1}
{"id": "mod_gstama_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple transcriptomes while maintaining source information. (tools: gstama)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gstama_merge": null, "bio2zarr_vcfpartition": null, "autocycler_resolve": null, "ivar_consensus": null, "autocycler_subsample": null}}, "target": "gstama_merge", "target_idx": 0}
{"id": "pipe_core10_scrnaseq_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Drop-seq, Smart-seq2, and 10x Genomics single-cell sequencing processing with Alevin, CellRanger, and STARsolo.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"mag": null, "taxprofiler": null, "scrnaseq": null, "chipseq": null, "sarek": null, "viralrecon": null, "atacseq": null, "ampliseq": null, "rnaseq": null, "eager": null}}, "target": "scrnaseq", "target_idx": 2}
{"id": "field_constraint_phenotype_0_12", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "pipe_all101_hadge_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Comprehensive pipeline for donor demultiplexing in single cell. Topics: cell-hashing, deconvolution, demultiplexing, donor-assignment, donor-deconvolution, genetic-demultiplexing. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nascent": null, "rnadnavar": null, "funcscan": null, "multiplesequencealign": null, "funcprofiler": null, "crisprseq": null, "riboseq": null, "callingcards": null, "coproid": null, "hadge": null}}, "target": "hadge", "target_idx": 9}
{"id": "samplesheet_arch_spatial_xenium_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Xenium in situ subcellular spatial RNA transcriptomics)", "question": {"type": "choice", "instructions": "Which columns are standard for 10x Xenium in situ subcellular spatial RNA transcriptomics input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,vcf": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "noul_single_hyphen_cli_params_error_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bio2zarr_vcf2zarrconvert_0", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARRCONVERT", "tool": "bio2zarr/vcf2zarrconvert", "description": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARRCONVERT (Convert VCF data to the VCF Zarr specification reliably, in parallel or distribu) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_jvarkit_vcffilterjdk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtering VCF with dynamically-compiled java expressions (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "sickle": "A windowed adaptive trimming tool for FASTQ files using quality", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "vcf2zarr/explode": "Convert VCF(s) to intermediate columnar format", "jvarkit/vcffilterjdk": "Filtering VCF with dynamically-compiled java expressions"}}, "target": "jvarkit/vcffilterjdk", "target_idx": 4}
{"id": "schema_std_molkart_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/molkart. Description: A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/molkart.", "criteria": {"fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample,nuclear_image,spot_table,membrane_image", "target_idx": 1}
{"id": "resource_bedtools_shift_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHIFT", "tool": "bedtools/shift", "description": "Shifts each feature by specific number of bases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHIFT (Shifts each feature by specific number of bases) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_plastid_metagenegenerate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of interest, optionally applying a mapping rule (tools: plastid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vizgenpostprocessing_compiletilesegmentation": null, "agat_spfilterbyorfsize": null, "plastid_metagenegenerate": null, "vcf_impute_minimac4": null, "alignoth": null}}, "target": "plastid_metagenegenerate", "target_idx": 2}
{"id": "mod_metabuli_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a database for classification with metabuli from FASTA files and a taxonomy (tools: metabuli)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "metabuli/build": "Builds a database for classification with metabuli from FASTA files and a taxonomy", "sourcepredict": "Classifies and predicts the origin of metagenomic samples", "antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "fastq_align_star": "Align reads to a reference genome using bowtie2 then sort with samtools"}}, "target": "metabuli/build", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_47", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bcftools_concat_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONCAT", "tool": "bcftools/concat", "description": "Concatenate VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONCAT (Concatenate VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_3_0", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Longitudinal cancer monitoring across multiple timepoints with entry step FASTQC.", "criteria": {"sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_hmmcopy_readcounter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: readCounter function from HMMcopy utilities, used to generate read in windows (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmcopy_mapcounter": "mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a big", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O", "hmmcopy_generatemap": "Perl script (generateMap.pl) generates the mappability of a genome given a certain size of reads, for input to", "spring_decompress": "Fast, efficient, lossless decompression of FASTQ files.", "hmmcopy_readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows"}}, "target": "hmmcopy_readcounter", "target_idx": 4}
{"id": "resource_amrfinderplus_update_3", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_UPDATE", "tool": "amrfinderplus/update", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_UPDATE (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_phaseimpute_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for genomics analysis? Specific context: A bioinformatics pipeline to phase and impute genetic data. Topics: genomics, genotype, imputation, low-pass-sequencing, phasing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]"}}, "target": "phaseimpute", "target_idx": 5}
{"id": "samplesheet_arch_rare_disease_trio_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/raredisease) for Trio exome/genome sequencing (Proband, Mother, Father). Input files: Paired-end FASTQs with pedigree relationships and affected status.", "question": {"type": "choice", "instructions": "Which columns are standard for Trio exome/genome sequencing (Proband, Mother, Father) input samplesheet?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_bam_create_som_pon_gatk_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CREATE_SOM_PON_GATK", "modules": ["gatk4/mutect2", "gatk4/genomicsdbimport", "gatk4/createsomaticpanelofnormals", "gatk4/mergevcfs", "gatk4/mergemutectstats"], "description": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a genomicsdbworkspace using genomicsdbimport, then use this to create a panel of normals using createsomaticpanelofnormals."}, "question": {"type": "choice", "instructions": "How should BAM_CREATE_SOM_PON_GATK (gatk4/mutect2, gatk4/genomicsdbimport, gatk4/createsomaticpanelofnormals, gatk4/mergevcfs, gatk4/mergemutectstats) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_create_som_pon_gatk": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_CREATE_SOM_PON_GATK": null}}, "target": "Use nf-core subworkflow bam_create_som_pon_gatk", "target_idx": 0}
{"id": "mod_hisat3n_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build HISAT-3N index for nucleotide conversion sequencing alignment (tools: hisat-3n)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge_build": "Build centrifuge database for taxonomic profiling", "gt_suffixerator": "Computes enhanced suffix array using GenomeTools gt-suffixerator utility", "hisat3n_build": "Build HISAT-3N index for nucleotide conversion sequencing alignment", "hisat2_build": "Builds HISAT2 index for reference genome", "samtools_getrg": "filter/convert SAM/BAM/CRAM file"}}, "target": "hisat3n_build", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry))", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "resource_bismark_coverage2cytosine_2", "category": "resource_profiling", "state": {"process": "BISMARK_COVERAGE2CYTOSINE", "tool": "bismark/coverage2cytosine", "description": "Relates methylation calls back to genomic cytosine contexts."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_COVERAGE2CYTOSINE (Relates methylation calls back to genomic cytosine contexts.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_nextclade_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should this step (nextclade/run) be packaged: Viral clade typing and QC?", "criteria": {"Use nf-core subworkflow nextclade": null, "Keep the modules in the main workflow": null, "Local subworkflow NEXTCLADE": null, "Leave them out": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 2}
{"id": "mod_stardist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cell and nuclear segmentation with star-convex shapes (tools: stardist)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gecco_convert": "This command helps transforming the output files created by\nGECCO into helpful format, should you want to use ", "deepcell_mesmer": "Deepcell/mesmer segmentation for whole-cell", "stardist": "Cell and nuclear segmentation with star-convex shapes", "sourmash_taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "baysor_run": "Bayesian segmentation of spatial transcriptomics data."}}, "target": "stardist", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_0_0", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control", "pipeline": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "mod_smncopynumbercaller_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion of Exon7-8) from a whole-genome sequencing (WGS) BAM file. (tools: smncopynumbercaller)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem3_index": "Create bwa-mem3 index for reference genome", "bedtools_makewindows": "Makes adjacent or sliding windows across a genome or BED file.", "smncopynumbercaller": "tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion ", "cnvkit_access": "Calculate the sequence-accessible coordinates in chromosomes from the given reference genome, output as a BED ", "cnaqc": "Quality control of copy number data from bulk WGS assays"}}, "target": "smncopynumbercaller", "target_idx": 2}
{"id": "noul_deprecated_dsl1_set_keyword_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_sex_1_14", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"pattern: ^\\S+\\.gz$": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "field_constraint_phenotype_1_1", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 1}
{"id": "resource_assemblyscan_2", "category": "resource_profiling", "state": {"process": "ASSEMBLYSCAN", "tool": "assemblyscan", "description": "Assembly summary statistics in JSON format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASSEMBLYSCAN (Assembly summary statistics in JSON format) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_31", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_anndata_getsize_4", "category": "resource_profiling", "state": {"process": "ANNDATA_GETSIZE", "tool": "anndata/getsize", "description": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_GETSIZE (Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "intent_debug_error_10", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "debug_error", "target_idx": 0}
{"id": "mod_bbmap_bbmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merging overlapping paired reads into a single read. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/getref": "Download and prepare database for Ariba analysis", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "sourmash/index": "Create a database of sourmash signatures (a group of FracMinHash sketches) to be used as references.", "qualimap/rnaseq": "Evaluate alignment data", "bbmap/bbmerge": "Merging overlapping paired reads into a single read."}}, "target": "bbmap/bbmerge", "target_idx": 4}
{"id": "mod_fastq_align_dedup_bwamem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate (tools: fastq_align_dedup_bwamem)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_index_dna": "Generate aligner index for a reference genome.\nPlease note, this workflow requires input CHANNELS. Input value", "dshbio_exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "bedtools_jaccard": "Calculate Jaccard statistic b/w two feature files.", "fastq_align_dedup_bwamem": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate", "alignoth": "Creating alignment plots from bam files"}}, "target": "fastq_align_dedup_bwamem", "target_idx": 3}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP", "modules": ["ensemblvep/vep", "tabix/tabix"], "description": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP (ensemblvep/vep, tabix/tabix) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_annotate_ensemblvep": null, "Keep the modules in the main workflow": null, "Local subworkflow VCF_ANNOTATE_ENSEMBLVEP": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep", "target_idx": 0}
{"id": "mod_skesa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble microbial genomes from short-read FASTQ files into contigs in FASTA format using SKESA. (tools: skesa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skesa": "Assemble microbial genomes from short-read FASTQ files into contigs in FASTA format using SKESA.", "helitronscanner_draw": "HelitronScanner draw tool for Helitron transposons in genomes", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ucsc_bedtobigbed": "Convert file from bed to bigBed format", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "skesa", "target_idx": 0}
{"id": "mod_fastq_extract_kraken_krakentools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract classified Kraken2 reads by taxonomic id (tools: fastq_extract_kraken_krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kofamscan": "Produces annotation using kofamscan against a Profile database and a KO list", "haplogrep2/classify": "classification into haplogroups", "fastq_extract_kraken_krakentools": "Extract classified Kraken2 reads by taxonomic id", "conifer": "Calculate confidence scores from Kraken2 output", "fastx/collapser": "Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts)"}}, "target": "fastq_extract_kraken_krakentools", "target_idx": 2}
{"id": "samplesheet_arch_pediatric_trio_somatic_0_1", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_strdrop_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect drops in STR coverage (tools: strdrop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo_merge": "Merge STR profiles into a multi-sample STR profile", "strdrop_call": "Detect drops in STR coverage", "canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "expansionhunterdenovo_profile": "Compute genome-wide STR profile", "lofreq_somatic": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl"}}, "target": "strdrop_call", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diaproteomics", "assay_type": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "data_format": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns are standard for Data-Independent Acquisition (DIA) quantitative mass spectrometry input samplesheet?", "criteria": {"sample,fasta": null, "sample,peptides_tsv": null, "sample,mzml": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "resource_bbmap_bbduk_5", "category": "resource_profiling", "state": {"process": "BBMAP_BBDUK", "tool": "bbmap/bbduk", "description": "Adapter and quality trimming of sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBDUK (Adapter and quality trimming of sequencing reads) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "intent_ask_question_17", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "prepare_data": null, "ask_question": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_jvarkit_dict2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract BED file from hts files containing a dictionary (VCF,BAM, CRAM, DICT, etc...) (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_annotate": "Add or remove annotations.", "instrain_profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "jvarkit_dict2bed": "Extract BED file from hts files containing a dictionary (VCF,BAM, CRAM, DICT, etc...)", "atlas_call": "generate VCF file from a BAM file using various calling methods", "pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g"}}, "target": "jvarkit_dict2bed", "target_idx": 2}
{"id": "mod_osfclient_fetch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A python library and a command-line client for up- and downloading files to and from your Open Science Framework projects (tools: osfclient)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"echtvar_anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "fcsgx_fetchdb": "Fetches the NCBI FCS-GX database using a provided manifest URL", "svanalyzer_svbenchmark": "SVbenchmark compares a set of “test” structural variants in VCF format to a known truth set (also in VCF forma", "osfclient_fetch": "A python library and a command-line client for up- and downloading files to and from your Open Science Framewo", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA."}}, "target": "osfclient_fetch", "target_idx": 3}
{"id": "intent_debug_error_13", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "build_pipeline": null, "prepare_data": null}}, "target": "debug_error", "target_idx": 0}
{"id": "pipe_all101_kmermaid_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze k-mer similarity analysis pipeline. Topics: k-mer, kmer, kmer-counting, kmer-frequency-count. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeqc": null, "metatdenovo": null, "rnavar": null, "mhcquant": null, "magmap": null, "proteinfamilies": null, "kmermaid": null, "pangenome": null}}, "target": "kmermaid", "target_idx": 6}
{"id": "qc_adapt_illumina_novaseq_1_0", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_cancer_longitudinal_4_0", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Serial plasma cfDNA and biopsy FASTQs across treatment intervals?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_single_hyphen_cli_params_error_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "local_subworkflow_checkirma_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for CHECKIRMA (custom/checkirma).", "criteria": {"Use nf-core subworkflow checkirma": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "mod_unzip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unzip ZIP archive files (tools: unzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genomad/endtoend": "Identify mobile genetic elements present in genomic assemblies", "xz/decompress": "Decompresses files with xz.", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "unzipfiles": "Unzip ZIP archive files", "unzip": "Unzip ZIP archive files"}}, "target": "unzip", "target_idx": 4}
{"id": "resource_bedtools_getfasta_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GETFASTA", "tool": "bedtools/getfasta", "description": "extract sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GETFASTA (extract sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_spatial_xenium_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Xenium in situ subcellular spatial RNA transcriptomics", "data_format": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,image": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "mod_fgbio_sortbam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts a SAM or BAM file. Several sort orders are available, including coordinate, queryname, random, and randomquery. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_sortbam": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate, queryname, random, and rando", "clame": "binning of metagenomic sequences", "tmb_pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "samtools_mpileup": "Generate text pileup output for one or multiple BAM files. Each input file produces a separate group of pileup", "csvtk_sort": "Sort  CSV (or TSV) tables"}}, "target": "fgbio_sortbam", "target_idx": 0}
{"id": "schema_std_abotyper_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/abotyper. Description: A pipeline for characterising the Human Blood Group and Red Cell Antigens using Oxford Nanopore third-generation sequencing data..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/abotyper.", "criteria": {"SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,fastq_1,strandedness": null, "sample_id,idat_red,idat_green,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_19", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_ashlar_4", "category": "resource_profiling", "state": {"process": "ASHLAR", "tool": "ashlar", "description": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASHLAR (Alignment by Simultaneous Harmonization of Layer/Adjacency Registration) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_16", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_agrvate_3", "category": "resource_profiling", "state": {"process": "AGRVATE", "tool": "agrvate", "description": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGRVATE (Rapid identification of Staphylococcus aureus agr locus type and agr operon vari) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_samtools_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: convert and then index CRAM -> BAM or BAM -> CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/call": null, "macse/refinealignment": null, "bcftools/view": null, "rtgtools/vcfeval": null, "samtools/convert": null}}, "target": "samtools/convert", "target_idx": 4}
{"id": "resource_bbmap_filterbyname_0", "category": "resource_profiling", "state": {"process": "BBMAP_FILTERBYNAME", "tool": "bbmap/filterbyname", "description": "Filter out sequences by sequence header name(s)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_FILTERBYNAME (Filter out sequences by sequence header name(s)) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedtools_shift_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHIFT", "tool": "bedtools/shift", "description": "Shifts each feature by specific number of bases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHIFT (Shifts each feature by specific number of bases) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_phaseimpute_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/phaseimpute", "assay": "phaseimpute pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/phaseimpute (A bioinformatics pipeline to phase and impute genetic data)?", "criteria": {"sample,fastq_1,fastq_2,bam,bai": null, "sample,bam,pbi,fail,repeat_id": null, "sample,tools,file,index": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "sample,tools,file,index", "target_idx": 2}
{"id": "resource_bamutil_clipoverlap_3", "category": "resource_profiling", "state": {"process": "BAMUTIL_CLIPOVERLAP", "tool": "bamutil/clipoverlap", "description": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_CLIPOVERLAP (clips overlapping read pairs. When two mates overlap, this tool will clip the re) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_basicpy_1", "category": "resource_profiling", "state": {"process": "BASICPY", "tool": "basicpy", "description": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is developed based on the Matlab version of BaSiC tool with major improvements in the algorithm."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASICPY (BaSiCPy is a python package for background and shading correction of optical mic) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_kmcp_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge search results from multiple databases. (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "concoct/extractfastabins": null, "bracken/combinebrackenoutputs": null, "minibwa/map": null, "kmcp/merge": null}}, "target": "kmcp/merge", "target_idx": 4}
{"id": "mod_utils_nfcore_pipeline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow with utility functions specific to the nf-core pipeline template (tools: utils_nfcore_pipeline)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nfcore_pipeline": null, "custom_dumpsoftwareversions": null, "aria2": null, "gmmdemux": null, "prodigal": null}}, "target": "utils_nfcore_pipeline", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_8", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bbmap_index_4", "category": "resource_profiling", "state": {"process": "BBMAP_INDEX", "tool": "bbmap/index", "description": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_INDEX (Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_octopusv_clean_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clean broken VCF/SVCF files using OctopuSV clean (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_merge": null, "sequali": null, "octopusv_clean": null, "bam_rseqc": null, "bcftools_annotate": null}}, "target": "octopusv_clean", "target_idx": 2}
{"id": "noul_modular_subworkflow_composition_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_mafft_guidetree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Guide tree rendering using MAFFT (tools: mafft)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"famsa/align": null, "sequencetools/pileupcaller": null, "agrvate": null, "mafft/guidetree": null, "agat/spextractsequences": null}}, "target": "mafft/guidetree", "target_idx": 3}
{"id": "resource_admixture_1", "category": "resource_profiling", "state": {"process": "ADMIXTURE", "tool": "admixture", "description": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datasets, where the individuals are unrelated (for example, the individuals in a case-control association study)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADMIXTURE (ADMIXTURE is a program for estimating ancestry in a model-based manner from larg) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_module_metadata_propagation_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/diaproteomics --input samplesheet.csv (Assay: Data-Independent Acquisition (DIA) quantitative mass spectrometry)", "question": {"type": "choice", "instructions": "Which columns are standard for Data-Independent Acquisition (DIA) quantitative mass spectrometry input samplesheet?", "criteria": {"sample,raw_file,condition": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "mod_deeparg_downloaddata_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes (tools: deeparg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metaphlan3/mergemetaphlantables": null, "bakta/baktadbdownload": null, "deeparg/downloaddata": null, "annotsv/installannotations": null, "tiddit/sv": null}}, "target": "deeparg/downloaddata", "target_idx": 2}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_repeatmasker_rmouttogff3_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files. (tools: repeatmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fmhfunprofiler": "Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references.", "clame": "binning of metagenomic sequences", "glimpse2_splitreference": "Tool to create a binary reference panel for quick reading time.", "repeatmasker_rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "biobambam_bamsormadup": "Parallel sorting and duplicate marking"}}, "target": "repeatmasker_rmouttogff3", "target_idx": 3}
{"id": "mod_leafcutter_differentialsplicing_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform differential splicing analysis to identify junctions with significant changes in splicing between conditions (tools: leafcutter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cleanifier/filter": null, "suppa/psiperevent": null, "rmats/prep": null, "leafcutter/differentialsplicing": null, "graphmap2/index": null}}, "target": "leafcutter/differentialsplicing", "target_idx": 3}
{"id": "mod_seqtk_cutn_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a BED file containing genomic locations of lengths of N. (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode_metaplots": "Set up RiboCode ORF calling with metaplots", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "seqtk_cutn": "Generates a BED file containing genomic locations of lengths of N.", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "gridss_preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and "}}, "target": "seqtk_cutn", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_46", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bcftools_concat_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONCAT", "tool": "bcftools/concat", "description": "Concatenate VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONCAT (Concatenate VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_pypolca_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Short read polisher for long read assemblies (tools: pypolca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quarto_prerender": null, "pypolca_run": null, "jupyternotebook": null, "parabricks_starfusion": null, "plink2_score": null}}, "target": "pypolca_run", "target_idx": 1}
{"id": "resource_autocycler_subsample_4", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_SUBSAMPLE", "tool": "autocycler/subsample", "description": "Downsample long-read sequencing data to the requested coverage using Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_SUBSAMPLE (Downsample long-read sequencing data to the requested coverage using Autocycler.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_seqkit_sliding_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use seqkit to generate sliding windows of input fasta (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_sample": "Sample sequences from FASTA/FASTQ files by number or proportion", "gcta_keep": "Apply a keep file to a dense GRM using `gcta --keep`", "seqkit_sliding": "Use seqkit to generate sliding windows of input fasta", "seqkit_grep": "Select sequences from a large file based on name/ID", "telseq": "Telseq: a software for calculating telomere length"}}, "target": "seqkit_sliding", "target_idx": 2}
{"id": "core_tool_fastqc_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Quality control metric evaluation including per-base sequence quality scores, GC content distributions, and k-mer overrepresentation for raw FASTQ data.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"falco": "FastQC C++ drop-in", "multiqc": "Aggregate report tool", "nanoplot": "Nanopore plotting", "qualimap": "BAM QC tool", "fastqc": "Quality control tool for high throughput sequence data"}}, "target": "fastqc", "target_idx": 4}
{"id": "resource_bowtie_build_0", "category": "resource_profiling", "state": {"process": "BOWTIE_BUILD", "tool": "bowtie/build", "description": "Create bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_BUILD (Create bowtie index for reference genome) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_core10_mag_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Assembly and binning of metagenomes using SPAdes, MEGAHIT, MetaBAT2, and CheckM quality control.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"chipseq": null, "sarek": null, "eager": null, "mag": null, "taxprofiler": null, "ampliseq": null, "viralrecon": null, "rnaseq": null, "atacseq": null, "scrnaseq": null}}, "target": "mag", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_1_21", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_somalier_relate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/GVCF or from jointly-called VCFs (tools: somalier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/multiinter": null, "somalier/relate": null, "ascat": null, "sam2lca/analyze": null, "somalier/extract": null}}, "target": "somalier/relate", "target_idx": 1}
{"id": "resource_argnorm_1", "category": "resource_profiling", "state": {"process": "ARGNORM", "tool": "argnorm", "description": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARGNORM (Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed b) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "data_format": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates?", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,well,fastq": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_abricate_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Screen assemblies for antimicrobial resistance against multiple databases (tools: abricate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi/draw": null, "abricate/run": null, "tcoffee/tcs": null, "amrfinderplus/update": null, "amrfinderplus/run": null}}, "target": "abricate/run", "target_idx": 1}
{"id": "mod_pbptyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assign PBP type of Streptococcus pneumoniae assemblies (tools: pbptyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbptyper": "Assign PBP type of Streptococcus pneumoniae assemblies", "pbjasmine": "Identify specific base modifications in PacBio HiFi reads by analyzing polymerase kinetic signatures", "plink2/vcf2bgen": "Convert from VCF file to BGEN file version 1.2 format preserving dosages.", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "pbptyper", "target_idx": 0}
{"id": "pipe_all101_slamseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze SLAMSeq processing and analysis pipeline. Topics: differential-expression, quantseq, slamseq, transcriptomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection"}}, "target": "slamseq", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pre-aligned BAM variant calling pipeline)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pre-aligned BAM variant calling pipeline.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Long-read Oxford Nanopore environmental metagenomic sequencing", "data_format": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fasta": null, "sample,bam": null, "sample,fastq_1,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "mod_cnvkit_fix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional coverage and GC content, according to the given reference. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "mdust": "mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences", "sentieon_haplotyper": "Runs Sentieon's haplotyper for germline variant calling.", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples).", "cnvkit_call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number"}}, "target": "cnvkit_fix", "target_idx": 0}
{"id": "schema_std_methylseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "assay": "methylseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/methylseq (Methylation (Bisulfite-Sequencing) analysis pipeline using B)?", "criteria": {"sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,strandedness,type": null, "id,fasta,reference,optional_data,template": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "sample,fastq_1,fastq_2,genome", "target_idx": 3}
{"id": "resource_bcftools_call_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CALL", "tool": "bcftools/call", "description": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily lost in the process of transition under htslib, but will be added back on popular demand.\nThe original calling model can be invoked with the -c option."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CALL (This command replaces the former bcftools view caller.\nSome of the original func) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_evexplorer_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/evexplorer. Description: nf-core/evexplorer is a pipeline for analyzing RNA data from extracellular vesicles, compatible with technologies such as nextflex, comboSeq, and ONT with further support forthcoming. evexplorer handles QC, expressed region detection, library size normalization and Differential RNA Expression (DRE).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/evexplorer.", "criteria": {"patient,sample,vcf,status,cna": null, "sample,fastq_1,fastq_2,vcf": null, "sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null}}, "target": "sample,fastq_1,fastq_2,batch,condition", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_34", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_4_3", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired FASTQs for both GEX and ATAC modalities per nucleus?", "criteria": {"sample,rna_fastq,atac_fastq": null, "sample,matrix": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "mod_coptr_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the coverage map along the reference genome (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr/extract": null, "rgi/bwt": null, "coptr/merge": null, "cellranger/count": null, "coptr/map": null}}, "target": "coptr/extract", "target_idx": 0}
{"id": "mod_clippy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs the Clippy CLIP peak caller (tools: clippy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ripgrep": "ripgrep recursively searches directories for a regex pattern", "gatk4_createreadcountpanelofnormals": "Creates a panel of normals (PoN) for read-count denoising given the read counts for samples in the panel.", "icountmini_metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks.", "clippy": "Runs the Clippy CLIP peak caller", "icountmini_summary": "Report proportion of cross-link events/sites on each region type."}}, "target": "clippy", "target_idx": 3}
{"id": "field_constraint_sample_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"format: file-path": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "samplesheet_arch_vcf_annotation_pipeline_5_4", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Downstream functional annotation of pre-called VCF files.", "criteria": {"sample,bed": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null}}, "target": "sample,vcf,tbi", "target_idx": 3}
{"id": "local_subworkflow_preparereports_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should this step (custom/preparereports, multiqc) be packaged: Custom aggregation and MultiQC reporting?", "criteria": {"Leave them out": null, "Local subworkflow PREPAREREPORTS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow preparereports": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 1}
{"id": "mod_blast_updateblastdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads a BLAST database from NCBI (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_cnv_wisecondorx": null, "blast_updateblastdb": null, "amrfinderplus_run": null, "mmseqs_databases": null, "abritamr_run": null}}, "target": "blast_updateblastdb", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_2", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_3_2", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for FAIRE-seq / DNAse-seq open chromatin profiling with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_stitch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: STITCH is an R program for reference panel free, read aware, low coverage sequencing genotype imputation. STITCH runs on a set of samples with sequencing reads in BAM format, as well as a list of positions to genotype, and outputs imputed genotypes in VCF format. (tools: stitch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eido_convert": "Convert any PEP project or Nextflow samplesheet to any format", "glimpse_concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "cellrangerarc_count": "Module to use Cell Ranger's ARC pipelines analyze sequencing data produced from Chromium Single Cell ARC. Uses", "stitch": "STITCH is an R program for reference panel free, read aware, low coverage sequencing genotype imputation. STIT", "glimpse_chunk": "Defines chunks where to run imputation"}}, "target": "stitch", "target_idx": 3}
{"id": "resource_agat_spkeeplongestisoform_4", "category": "resource_profiling", "state": {"process": "AGAT_SPKEEPLONGESTISOFORM", "tool": "agat/spkeeplongestisoform", "description": "Filters GFF records to keep only the longest isoform per gene"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPKEEPLONGESTISOFORM (Filters GFF records to keep only the longest isoform per gene) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_angsd_realsfs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate site frequency spectrum from site allele frequencies (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker_call": "mtDNA deletion and duplication calling downstream of mitosalt", "angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "angsd_docounts": "Calculates base frequency statistics across reference positions from BAM.", "angsd_gl": "Calculated genotype likelihoods from BAM files.", "nail_search": "nail search is a fast and scalable tool for searching protein sequences against protein databases"}}, "target": "angsd_realsfs", "target_idx": 1}
{"id": "mod_custom_bed12codonpositions_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviour emits one row per codon (the\n5' nucleotide); --step / --width / --frame control the stride, span\nand offset on the spliced mRNA. Useful for codon-level work on\nspliced features (e.g. ribo-seq P-site counts per codon, frame /\nperiodicity QC, novel-ORF tiling). (tools: bed12codonpositions)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "custom/bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes"}}, "target": "custom/bed12codonpositions", "target_idx": 2}
{"id": "mod_ngmaster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotyping Neisseria gonorrhoeae assemblies (tools: ngmaster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_filterconsensusreads": null, "ngmaster": null, "deeptools_bamcompare": null, "amrfinderplus_update": null, "any2fasta": null}}, "target": "ngmaster", "target_idx": 1}
{"id": "mod_varscan_fpfilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, and copy number variations in both somatic and germline samples. It is particularly useful for analyzing tumor/normal sample pairs. Subtool fpfilter is used to filter a set of SNPs/indels based on coverage, reads, p-value, etc. (tools: varscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/consensus": null, "odgi/unchop": null, "varscan/fpfilter": null, "gzrt": null, "atlas/call": null}}, "target": "varscan/fpfilter", "target_idx": 2}
{"id": "noul_dynamic_resource_allocation_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_shapeit5_switch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Program to compute switch error rate and genotyping error rate given simulated or trio data. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"beagle5_beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "flash": "Perform merging of mate paired-end sequencing reads", "shapeit5_switch": "Program to compute switch error rate and genotyping error rate given simulated or trio data.", "metaphlan_metaphlan": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing", "eagle2": "Perform phasing of genotyped data with or without a reference panel"}}, "target": "shapeit5_switch", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_4_0", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Aligned BAM files?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_0_16", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_spaceranger_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data (tools: spaceranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_cluster": null, "fastq_preprocess_seqkit": null, "spaceranger_count": null, "bamaligncleaner": null, "falint": null}}, "target": "spaceranger_count", "target_idx": 2}
{"id": "mod_cnvkit_genemetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number variant detection from high-throughput sequencing data (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "sam2lca/analyze": "Calling lowest common ancestors from multi-mapped reads in SAM/BAM/CRAM files", "cnvkit/export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "cnvkit/genemetrics": "Copy number variant detection from high-throughput sequencing data", "cnvkit/call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number"}}, "target": "cnvkit/genemetrics", "target_idx": 3}
{"id": "field_constraint_fastq_2_0_1", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "noul_dynamic_resource_allocation_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_cutandrun_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis.. Topics: cutandrun, cutandrun-seq, cutandtag, cutandtag-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin"}}, "target": "cutandrun", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_17", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_20", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_sylph_sketchsamples_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sketching/indexing sequencing reads (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"minimac4_impute": "Imputation of genotypes using a reference panel", "skani_sketch": "Storing skani sketches/indices on disk.", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "mash_sketch": "Creates vastly reduced representations of sequences using MinHash", "sylph_sketchsamples": "Sketching/indexing sequencing reads"}}, "target": "sylph_sketchsamples", "target_idx": 4}
{"id": "mod_bismark_deduplicate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes alignments to the same position in the genome\nfrom the Bismark mapping output. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_report": "Collects bismark alignment reports", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "bismark_summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "shasum": "Print SHA256 (256-bit) checksums.", "mdust": "mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences"}}, "target": "bismark_deduplicate", "target_idx": 1}
{"id": "mod_bam2fastx_bam2fastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data (tools: bam2fastx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/makegrm": "Compute a whole dense GRM with GCTA", "hifiadapterfilt/hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "bam2fastx/bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga"}}, "target": "bam2fastx/bam2fastq", "target_idx": 2}
{"id": "mod_deeptools_bigwigcompare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare two bigWig files based on the number of mapped reads (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ucsc_bedgraphtobigwig": "Convert a bedGraph file to bigWig format.", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs", "ucsc_bigwigaverageoverbed": "compute average score of bigwig over bed file", "jellyfish_count": "Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm", "deeptools_bigwigcompare": "Compare two bigWig files based on the number of mapped reads"}}, "target": "deeptools_bigwigcompare", "target_idx": 4}
{"id": "pipe_all101_proteinannotator_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Generation of sequence-level annotations for amino acid sequences. Topics: annotation, proteomics. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]"}}, "target": "proteinannotator", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_18", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "noul_process_conditional_execution_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_arriba_download_3", "category": "resource_profiling", "state": {"process": "ARRIBA_DOWNLOAD", "tool": "arriba/download", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_DOWNLOAD (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_raredisease_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for diagnostics analysis? Specific context: Call and score variants from WGS/WES of rare disease patients.. Topics: diagnostics, rare-disease, snv, structural-variants, variant-annotation, variant-calling. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]"}}, "target": "raredisease", "target_idx": 1}
{"id": "subworkflow_pkg_bam_taps_conversion_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TAPS_CONVERSION", "modules": ["rastair/mbias", "rastair/call", "rastair/methylkit", "rastair/mbiasparser"], "description": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis"}, "question": {"type": "choice", "instructions": "How should BAM_TAPS_CONVERSION (rastair/mbias, rastair/call, rastair/methylkit, rastair/mbiasparser) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_TAPS_CONVERSION": null, "Leave them out": null, "Use nf-core subworkflow bam_taps_conversion": null}}, "target": "Use nf-core subworkflow bam_taps_conversion", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_2_4", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status", "pipeline": "nf-core/eager"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_svaba_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements (tools: svaba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": "Annotation and Ranking of Structural Variation", "modkit/callmods": "Call mods from a modbam, creates a new modbam with probabilities set to 100% if a base modification is called ", "nanocomp": "Compare multiple runs of long read sequencing data and alignments", "svaba": "SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide ", "caddsv/get": "Download CADD-SV annotation resources or SegmentNT model files."}}, "target": "svaba", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_3_1", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "resource_bio2zarr_vcf2zarrexplode_0", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARREXPLODE", "tool": "bio2zarr/vcf2zarrexplode", "description": "Convert VCF(s) to intermediate columnar format (ICF)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARREXPLODE (Convert VCF(s) to intermediate columnar format (ICF)) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_hmmer_eslalipid_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "bbmap_filterbyname": "Filter out sequences by sequence header name(s)", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "seqkit_seq": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)"}}, "target": "hmmer_eslalipid", "target_idx": 0}
{"id": "noul_default_empty_channel_behavior_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "intent_prepare_data_17", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "debug_error": null, "build_pipeline": null, "ask_question": null}}, "target": "prepare_data", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral genome sequencing on Oxford Nanopore MinION / GridION. Input files: Demultiplexed single-end long reads from tiled viral amplicons.", "question": {"type": "choice", "instructions": "Which columns are standard for Viral genome sequencing on Oxford Nanopore MinION / GridION input samplesheet?", "criteria": {"sample,fasta": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_gatk4_collectsvevidence_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file containing the location of and orientation of read pairs marked as discordant, and a file containing the clipping location of all soft clipped reads and the orientation of the clipping. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_asereadcounter": null, "metacache_build": null, "gatk4_applybqsr": null, "ultra_index": null, "gatk4_collectsvevidence": null}}, "target": "gatk4_collectsvevidence", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_align_dna_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DNA", "modules": ["bowtie2/align", "bwa/mem", "bwamem2/mem", "dragmap/align", "snapaligner/align", "strobealign"], "description": "Align fastq files to a reference genome"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DNA (bowtie2/align, bwa/mem, bwamem2/mem, dragmap/align, snapaligner/align, strobealign) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_DNA": null, "Use nf-core subworkflow fastq_align_dna": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_align_dna", "target_idx": 2}
{"id": "mod_proteus_readproteingroups_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: reads a maxQuant proteinGroups file with Proteus (tools: proteus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann": null, "picard/fastqtosam": null, "proteus/readproteingroups": null, "sentieon/tnhaplotyper2": null, "comet": null}}, "target": "proteus/readproteingroups", "target_idx": 2}
{"id": "mod_gatk4_bedtointervallist_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates an interval list from a bed file and a reference dict (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "gatk4/bedtointervallist": "Creates an interval list from a bed file and a reference dict", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "bam_rseqc": "Subworkflow to run multiple commands in the RSeqC package"}}, "target": "gatk4/bedtointervallist", "target_idx": 1}
{"id": "mod_pbtk_bam2fastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq (tools: pbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/happy": null, "bio2zarr/vcf2zarrexplode": null, "pbtk/bam2fastq": null, "bamtools/convert": null, "proovframe/map": null}}, "target": "pbtk/bam2fastq", "target_idx": 2}
{"id": "resource_bwa_sampe_4", "category": "resource_profiling", "state": {"process": "BWA_SAMPE", "tool": "bwa/sampe", "description": "Convert paired-end bwa SA coordinate files to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMPE (Convert paired-end bwa SA coordinate files to SAM format) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_high", "target_idx": 1}
{"id": "mod_entrezdirect_esearch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Searches a term in a public NCBI database (tools: entrezdirect)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "entrezdirect_esearch": "Searches a term in a public NCBI database", "cnvkit_export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "entrezdirect_xtract": "Queries an NCBI database using an UID", "blat": "Queries a sequence subject"}}, "target": "entrezdirect_esearch", "target_idx": 1}
{"id": "resource_biscuit_epiread_1", "category": "resource_profiling", "state": {"process": "BISCUIT_EPIREAD", "tool": "biscuit/epiread", "description": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_EPIREAD (Summarizes read-level methylation (and optionally SNV) information from a\nBiscui) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_melon_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs taxonomic profiling of long metagenomic reads against the melon database (tools: melon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmstat": null, "melon": null, "deeptools/plotprofile": null, "coptr/extract": null, "argnorm": null}}, "target": "melon", "target_idx": 1}
{"id": "mod_custom_gtffilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter a gtf file to keep only regions that are located on a chromosome represented in a given fasta file (tools: gtffilter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/extractfrompdb": null, "agat/convertspgff2gtf": null, "methylsieve": null, "custom/gtffilter": null, "agat/spkeeplongestisoform": null}}, "target": "custom/gtffilter", "target_idx": 3}
{"id": "subworkflow_pkg_bam_docounts_contamination_angsd_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DOCOUNTS_CONTAMINATION_ANGSD", "modules": ["angsd/docounts", "angsd/contamination"], "description": "Calculate contamination of the X-chromosome with ANGSD"}, "question": {"type": "choice", "instructions": "How should BAM_DOCOUNTS_CONTAMINATION_ANGSD (angsd/docounts, angsd/contamination) be structured in DSL2?", "criteria": {"Local subworkflow BAM_DOCOUNTS_CONTAMINATION_ANGSD": null, "Use nf-core subworkflow bam_docounts_contamination_angsd": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_docounts_contamination_angsd", "target_idx": 1}
{"id": "mod_vrhyme_extractunbinned_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracting sequences that were unbinnned by vRhyme into a FASTA file (tools: vrhyme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/multibamsummary": "Computes read coverage for genomic regions (bins) across the entire genome.", "vrhyme/linkbins": "Linking bins output by vRhyme to create one sequences per bin", "leviosam2/lift": "Converting aligned short and long reads records from one reference to another", "bedtools/maskfasta": "masks sequences in a FASTA file based on intervals defined in a feature file.", "vrhyme/extractunbinned": "Extracting sequences that were unbinnned by vRhyme into a FASTA file"}}, "target": "vrhyme/extractunbinned", "target_idx": 4}
{"id": "mod_sam2lca_analyze_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calling lowest common ancestors from multi-mapped reads in SAM/BAM/CRAM files (tools: sam2lca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": null, "sam2lca/analyze": null, "simpleaf/index": null, "bwa/mem": null, "alignoth": null}}, "target": "sam2lca/analyze", "target_idx": 1}
{"id": "mod_gatk4_indexfeaturefile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates an index for a feature file, e.g. VCF or BED file. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_consensus": "Compresses VCF files", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "gatk4_indexfeaturefile": "Creates an index for a feature file, e.g. VCF or BED file.", "dshbio_splitgff3": "Split features in gzipped GFF3 format", "plink_epistasis": "Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others."}}, "target": "gatk4_indexfeaturefile", "target_idx": 2}
{"id": "mod_sentieon_datametrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects multiple quality metrics from a bam file (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svanalyzer_svbenchmark": "SVbenchmark compares a set of “test” structural variants in VCF format to a known truth set (also in VCF forma", "fgumi_simplexmetrics": "Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data", "fgumi_duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data", "samshee": "Module to validate illumina® Sample Sheet v2 files.", "sentieon_datametrics": "Collects multiple quality metrics from a bam file"}}, "target": "sentieon_datametrics", "target_idx": 4}
{"id": "noul_executor_support_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_gatk4_learnreadorientationmodel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses f1r2 counts collected during mutect2 to Learn the prior probability of read orientation artifacts (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/applybqsr": null, "calder2": null, "mobsuite/recon": null, "gatk4/asereadcounter": null, "gatk4/learnreadorientationmodel": null}}, "target": "gatk4/learnreadorientationmodel", "target_idx": 4}
{"id": "local_subworkflow_variantsofint_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should VARIANTSOFINT (custom/variantsofint) be built?", "criteria": {"Local subworkflow VARIANTSOFINT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow variantsofint": null, "Leave them out": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_47", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_angsd_soapsnpcalibration_3", "category": "resource_profiling", "state": {"process": "ANGSD_SOAPSNPCALIBRATION", "tool": "angsd/soapsnpcalibration", "description": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_SOAPSNPCALIBRATION (Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality mat) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_htsnimtools_vcfcheck_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will instead want whole exome) coverage and uses that as an expectation of variants. (tools: htsnimtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro", "htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "samtools_ampliconclip": "Clips read alignments where they match BED file defined regions", "rasusa": "Randomly subsample sequencing reads to a specified coverage", "falint": "A fasta linter/validator"}}, "target": "htsnimtools_vcfcheck", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_44", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_18", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_40", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay_type": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "data_format": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_imcyto_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Image Mass Cytometry analysis pipeline. Topics: cytometry, image-analysis, image-processing, image-segmentation. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]"}}, "target": "imcyto", "target_idx": 5}
{"id": "samplesheet_arch_taxprofiler_shotgun_6_4", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform", "pipeline": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multi-taxonomic profiling of complex metagenomic shotgun reads input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_strandedness_0_1", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"pattern: ^[0-9]+$": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_bam_stats_samtools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces comprehensive statistics from SAM/BAM/CRAM file (tools: bam_stats_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "soupx": "Estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.\n\nThe filtere", "assemblyscan": "Assembly summary statistics in JSON format", "bam_stats_samtools": "Produces comprehensive statistics from SAM/BAM/CRAM file", "bamstats/generalstats": "write your description here"}}, "target": "bam_stats_samtools", "target_idx": 3}
{"id": "intent_ask_question_14", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_pcne_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimates plasmid copy number from assembled genome (tools: pcne)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genomad/endtoend": "Identify mobile genetic elements present in genomic assemblies", "mobsuite/typer": "Bacterial plasmid typing and mobility prediction", "samtools/sort": "Sort SAM/BAM/CRAM file", "pcne": "Estimates plasmid copy number from assembled genome", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate"}}, "target": "pcne", "target_idx": 3}
{"id": "pipe_all101_proteogenomicsdb_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis.. Topics: cosmic, gnomad, protein-databases, proteogenomics, proteomics, pypgatk. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"lsmquant": null, "proteogenomicsdb": null, "rnaseq": null, "chipseq": null, "hgtseq": null, "metaboigniter": null, "bacass": null, "detaxizer": null}}, "target": "proteogenomicsdb", "target_idx": 1}
{"id": "mod_mobsuite_recon_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to reconstruct plasmids in bacterial assemblies (tools: mobsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpdists": "Pairwise SNP distance matrix from a FASTA sequence alignment", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje", "mobsuite/recon": "A tool to reconstruct plasmids in bacterial assemblies", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "mobsuite/recon", "target_idx": 3}
{"id": "mod_finaletoolkit_adjustwps_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adjusts raw Windowed Protection Score (WPS) by applying a median filter\nand Savitsky-Golay filter. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "finaletoolkit/adjustwps": "Adjusts raw Windowed Protection Score (WPS) by applying a median filter\nand Savitsky-Golay filter.", "maxquant/lfq": "Run standard proteomics data analysis with MaxQuant, mostly dedicated to label-free. Paths to fasta and raw fi", "picard/fixmateinformation": "Verify mate-pair information between mates and fix if needed", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "finaletoolkit/adjustwps", "target_idx": 1}
{"id": "schema_std_proteinfamilies_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinfamilies", "assay": "proteinfamilies pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/proteinfamilies (Generation and updating of protein families)?", "criteria": {"sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2,condition,reference": null, "id,taxid,fasta_dna,fasta_aa": null}}, "target": "sample,fasta,existing_hmms_to_update,existing_msas_to_update", "target_idx": 0}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_shinyngs_app_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: build and deploy Shiny apps for interactively mining differential abundance data (tools: shinyngs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shinyngs/app": "build and deploy Shiny apps for interactively mining differential abundance data", "metaspace/converter": "Export METASPACE datasets to AnnData and SpatialData objects", "xeniumranger/rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "propr/propd": "Perform differential proportionality analysis", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}}, "target": "shinyngs/app", "target_idx": 0}
{"id": "resource_angsd_dosaf_5", "category": "resource_profiling", "state": {"process": "ANGSD_DOSAF", "tool": "angsd/dosaf", "description": "Estimate site allele frequencies from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOSAF (Estimate site allele frequencies from BAM files.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_exit_code_137_cause_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_mirtop_export_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package (tools: mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop/gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations", "mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package", "panacus/visualize": "Create visualizations from a tsv coverage histogram created with panacus.", "nacho/normalize": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "plastid/metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere"}}, "target": "mirtop/export", "target_idx": 1}
{"id": "field_constraint_sex_0_7", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"pattern: ^\\S+\\.gz$": null, "format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "intent_debug_error_22", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "debug_error", "target_idx": 1}
{"id": "mod_transdecoder_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. You can use this module after transdecoder_longorf (tools: transdecoder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "transdecoder/predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "entrezdirect/esummary": "Queries an NCBI database using Unique Identifier(s)", "krakentools/extractkrakenreads": "Extract reads classified at any user-specified taxonomy IDs."}}, "target": "transdecoder/predict", "target_idx": 1}
{"id": "resource_bedtools_closest_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_CLOSEST", "tool": "bedtools/closest", "description": "For each feature in A, finds the closest feature (upstream or downstream) in B."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_CLOSEST (For each feature in A, finds the closest feature (upstream or downstream) in B.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_align_dedup_bwameth_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BWAMETH", "modules": ["bwameth/align", "parabricks/fq2bammeth", "samtools/sort", "samtools/index", "samtools/flagstat", "samtools/stats", "picard/markduplicates"], "description": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BWAMETH (bwameth/align, parabricks/fq2bammeth, samtools/sort, samtools/index, samtools/flagstat, samtools/stats, picard/markduplicates) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_dedup_bwameth": null, "Local subworkflow FASTQ_ALIGN_DEDUP_BWAMETH": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwameth", "target_idx": 0}
{"id": "mod_stainwarpy_transformsegmask_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy (tools: stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy/transformsegmask": "Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy", "stainwarpy/extractchannel": "Extract a single channel image from multiplexed tissue images using stainwarpy", "cnvkit/fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "hmmer/hmmemit": "emit sequences from a profile HMM"}}, "target": "stainwarpy/transformsegmask", "target_idx": 0}
{"id": "noul_process_conditional_execution_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_abacas_0", "category": "resource_profiling", "state": {"process": "ABACAS", "tool": "abacas", "description": "Contiguate draft genome assembly"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABACAS (Contiguate draft genome assembly) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_21", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_18", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_fcsgx_rungx_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to screen and remove foreign contamination from genome assemblies (tools: fcsgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fcsgx_rungx": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to screen and remove foreign contamination from ", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "shinyngs_staticexploratory": "Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots", "abacas": "Contiguate draft genome assembly", "gatk4_learnreadorientationmodel": "Uses f1r2 counts collected during mutect2 to Learn the prior probability of read orientation artifacts"}}, "target": "fcsgx_rungx", "target_idx": 0}
{"id": "mod_samshee_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to validate illumina® Sample Sheet v2 files. (tools: samshee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"refsolver_identify": "Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver", "parsesdrf_convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration ", "jasminesv": "Jointly Accurate Sv Merging with Intersample Network Edges", "samplesheetparser_info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "samshee": "Module to validate illumina® Sample Sheet v2 files."}}, "target": "samshee", "target_idx": 4}
{"id": "field_constraint_strandedness_0_2", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "resource_bbmap_clumpify_2", "category": "resource_profiling", "state": {"process": "BBMAP_CLUMPIFY", "tool": "bbmap/clumpify", "description": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_CLUMPIFY (Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_workflow_completion_lifecycle_hook_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_bcftools_consensus_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONSENSUS", "tool": "bcftools/consensus", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONSENSUS (Compresses VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_riboseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/riboseq. Description: Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/riboseq.", "criteria": {"sample,fastq_1,fastq_2,strandedness,type": null, "id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,fastq_1,fastq_2,replicate,control": null}}, "target": "sample,fastq_1,fastq_2,strandedness,type", "target_idx": 0}
{"id": "mod_clipkit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference. (tools: clipkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "oncocnv": "Calls CNVs in bam files from tumor patients"}}, "target": "clipkit", "target_idx": 3}
{"id": "mod_purgedups_calcuts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate coverage cutoffs to determine when to purge duplicated sequence. (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker/classify": "mtDNA deletion and duplication classification downstream of mitosalt", "bedtools/coverage": "computes both the depth and breadth of coverage of features in file B on the features in file A", "purgedups/calcuts": "Calculate coverage cutoffs to determine when to purge duplicated sequence.", "cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "gcta/calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups"}}, "target": "purgedups/calcuts", "target_idx": 2}
{"id": "local_subworkflow_prepilluminareads_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should this step (trimmomatic) be packaged: Single-step adapter trimming for Illumina reads?", "criteria": {"Leave them out": null, "Local subworkflow PREPILLUMINAREADS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 1}
{"id": "samplesheet_arch_scrna_multiome_6_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Multiome single-cell joint RNA and ATAC chromatin input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "resource_bcftools_plotvcfstats_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLOTVCFSTATS", "tool": "bcftools/plotvcfstats", "description": "Plots the output of bcftools stats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLOTVCFSTATS (Plots the output of bcftools stats) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_0_2", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,otu_table": null, "sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_3_1", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_bio2zarr_vcfpartition_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing. (tools: bio2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "soupx": "Estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.\n\nThe filtere", "bio2zarr/vcfpartition": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing.", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "snpeff/snpeff": "Genetic variant annotation and functional effect prediction toolbox"}}, "target": "bio2zarr/vcfpartition", "target_idx": 2}
{"id": "resource_alignoth_0", "category": "resource_profiling", "state": {"process": "ALIGNOTH", "tool": "alignoth", "description": "Creating alignment plots from bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALIGNOTH (Creating alignment plots from bam files) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_0_0", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels", "pipeline": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_sourmash_taxannotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"geoquery_getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)", "sourmash_taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "hifitrimmer_filterbam": "Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLA", "sourmash_gather": "Search a metagenome sourmash signature against one or many reference databases and return the minimum set of g", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity"}}, "target": "sourmash_taxannotate", "target_idx": 1}
{"id": "mod_bedtools_groupby_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Groups features in a BED file by given column(s) and computes summary statistics for each group to another column. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/groupby": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another col", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "mudskipper/index": "Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM fi"}}, "target": "bedtools/groupby", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_44", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_picard_collectinsertsizemetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics about the insert size distribution of a paired-end library. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "cnvkit/access": "Calculate the sequence-accessible coordinates in chromosomes from the given reference genome, output as a BED ", "fgumi/duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data", "rsem/preparereference": "Prepare a reference genome for RSEM", "picard/collectinsertsizemetrics": "Collect metrics about the insert size distribution of a paired-end library."}}, "target": "picard/collectinsertsizemetrics", "target_idx": 4}
{"id": "mod_gunc_downloaddb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes (tools: gunc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aria2": "CLI Download utility", "gunc/downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "cellranger/mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command.", "gt/suffixerator": "Computes enhanced suffix array using GenomeTools gt-suffixerator utility", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo"}}, "target": "gunc/downloaddb", "target_idx": 1}
{"id": "schema_std_seqinspector_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/seqinspector", "description": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput. ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/seqinspector?", "criteria": {"sample,fastq_1,fastq_2,pool,hash_index": null, "sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,rundir,tags": null, "vcf,fasta,genome,site,source": null}}, "target": "sample,fastq_1,fastq_2,rundir,tags", "target_idx": 2}
{"id": "subworkflow_pkg_homer_groseq_3", "category": "subworkflow_packaging", "state": {"subworkflow": "HOMER_GROSEQ", "modules": ["unzip", "homer/maketagdirectory", "homer/makeucscfile", "homer/findpeaks", "homer/pos2bed"], "description": "Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.ucsd.edu/homer/ngs/groseq/groseq.html)."}, "question": {"type": "choice", "instructions": "How should HOMER_GROSEQ (unzip, homer/maketagdirectory, homer/makeucscfile, homer/findpeaks, homer/pos2bed) be structured in DSL2?", "criteria": {"Use nf-core subworkflow homer_groseq": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow HOMER_GROSEQ": null}}, "target": "Use nf-core subworkflow homer_groseq", "target_idx": 0}
{"id": "pipe_all101_mhcquant_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for dda. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "seqsubmit": "nf-core pipeline for data submission to ENA", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]"}}, "target": "mhcquant", "target_idx": 9}
{"id": "noul_publishdir_directive_usage_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_4_0", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery", "pipeline": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end oncology RNA-seq reads for chimeric transcript discovery?", "criteria": {"sample,bam": null, "sample,fusion_bed": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_samtools_cramsize_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: List CRAM Content-ID and Data-Series sizes (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krakenuniq/download": "Download KrakenUniq databases and related fles", "plink/gwas": "Generate GWAS association studies", "samtools/cramsize": "List CRAM Content-ID and Data-Series sizes", "bwameme/mem": "Performs fastq alignment to a fasta reference using BWA-MEME", "biobambam/bammarkduplicates2": "Locate and tag duplicate reads in a BAM file"}}, "target": "samtools/cramsize", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_17", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "subworkflow_pkg_bam_stats_mirna_mirtop_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STATS_MIRNA_MIRTOP", "modules": ["mirtop/gff", "mirtop/counts", "mirtop/export", "mirtop/stats"], "description": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 format."}, "question": {"type": "choice", "instructions": "How should BAM_STATS_MIRNA_MIRTOP (mirtop/gff, mirtop/counts, mirtop/export, mirtop/stats) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_STATS_MIRNA_MIRTOP": null, "Use nf-core subworkflow bam_stats_mirna_mirtop": null}}, "target": "Use nf-core subworkflow bam_stats_mirna_mirtop", "target_idx": 3}
{"id": "samplesheet_arch_ont_direct_rna_se_2_4", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "intent_ask_question_13", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "ask_question": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 2}
{"id": "pipe_all101_mnaseseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: MNase-seq analysis pipeline using BWA and DANPOS2.. Topics: mnase-seq, nucleosome, nucleosome-maps, nucleosome-positioning. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin"}}, "target": "mnaseseq", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_47", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "schema_std_reportho_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/reportho", "description": "nf-core pipeline for comparative analysis of ortholog predictions", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/reportho?", "criteria": {"id,fasta,query": null, "sample,id,data_path,fastq_dir,cytaimage": null, "sample,fastq,cell_count": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null}}, "target": "id,fasta,query", "target_idx": 0}
{"id": "local_subworkflow_preparereports_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should PREPAREREPORTS (custom/preparereports, multiqc) be built?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow PREPAREREPORTS": null, "Leave them out": null, "Use nf-core subworkflow preparereports": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 1}
{"id": "mod_upp_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns protein structures using UPP (tools: upp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie2/align": "Align reads to a reference genome using bowtie2", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "upp/align": "Aligns protein structures using UPP", "svtk/standardize": "Convert SV calls to a standardized format."}}, "target": "upp/align", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_30", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_bedtools_flank_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates two new flanking intervals for each interval in a BED/GFF/VCF file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/plotcorrelation": "Visualises sample correlations using a compressed matrix generated by mutlibamsummary or multibigwigsummary as", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "vizgenpostprocessing/runsegmentationontile": "The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool.", "bedtools/flank": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file.", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}}, "target": "bedtools/flank", "target_idx": 3}
{"id": "pipe_all101_cutandrun_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for cutandrun analysis? Specific context: Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis.. Topics: cutandrun, cutandrun-seq, cutandtag, cutandtag-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "callingcards": "A pipeline for processing calling cards data", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]"}}, "target": "cutandrun", "target_idx": 2}
{"id": "subworkflow_pkg_bam_markduplicates_picard_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_PICARD", "modules": ["picard/markduplicates", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_PICARD (picard/markduplicates, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_MARKDUPLICATES_PICARD": null, "Leave them out": null, "Use nf-core subworkflow bam_markduplicates_picard": null}}, "target": "Use nf-core subworkflow bam_markduplicates_picard", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_download_prefetch_fasterqdump_sratools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS", "modules": ["custom/sratoolsncbisettings", "sratools/prefetch", "sratools/fasterqdump"], "description": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA)."}, "question": {"type": "choice", "instructions": "How should FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS (custom/sratoolsncbisettings, sratools/prefetch, sratools/fasterqdump) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS": null, "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools": null}}, "target": "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_29", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_31", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_0_4", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,bam,bai": null, "sample,cram,crai": null, "sample,fastq_1,fastq_2": null, "sample,cram": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "mod_fastq_align_dna_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align fastq files to a reference genome (tools: fastq_align_dna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba_getref": "Download and prepare database for Ariba analysis", "autocycler_resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "shapeit5_switch": "Program to compute switch error rate and genotyping error rate given simulated or trio data.", "fastq_align_dna": "Align fastq files to a reference genome", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads"}}, "target": "fastq_align_dna", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_binning_concoct_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BINNING_CONCOCT", "modules": ["concoct/cutupfasta", "concoct/concoctcoveragetable", "concoct/concoct", "concoct/mergecutupclustering", "concoct/extractfastabins"], "description": "Runs the CONCOCT workflow of contig binning"}, "question": {"type": "choice", "instructions": "How should FASTA_BINNING_CONCOCT (concoct/cutupfasta, concoct/concoctcoveragetable, concoct/concoct, concoct/mergecutupclustering, concoct/extractfastabins) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_binning_concoct": null, "Local subworkflow FASTA_BINNING_CONCOCT": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_binning_concoct", "target_idx": 0}
{"id": "resource_bbmap_bbnorm_3", "category": "resource_profiling", "state": {"process": "BBMAP_BBNORM", "tool": "bbmap/bbnorm", "description": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result in a flat coverage distribution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBNORM (BBNorm is designed to normalize coverage by down-sampling reads over high-depth ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_ataqv_ataqv_5", "category": "resource_profiling", "state": {"process": "ATAQV_ATAQV", "tool": "ataqv/ataqv", "description": "ataqv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_ATAQV (ataqv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_atlasgeneannotationmanipulation_gtf2featureannotation_4", "category": "resource_profiling", "state": {"process": "ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION", "tool": "atlasgeneannotationmanipulation/gtf2featureannotation", "description": "Generate tables of feature metadata from GTF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION (Generate tables of feature metadata from GTF files) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_immunedeconv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform immune cell deconvolution using RNA-seq data and various computational methods. (tools: immunedeconv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"immunedeconv": null, "gatk4_learnreadorientationmodel": null, "arriba_visualisation": null, "fusioninspector": null, "picard_collectvariantcallingmetrics": null}}, "target": "immunedeconv", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_44", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_custom_filterdifferentialtable_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters a differential expression table based on logFC and adjusted p-value thresholds (tools: pandas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "bbmap_filterbyname": "Filter out sequences by sequence header name(s)", "deacon_filter": "Filter DNA sequences using index of reference genome", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "custom_filterdifferentialtable": "Filters a differential expression table based on logFC and adjusted p-value thresholds"}}, "target": "custom_filterdifferentialtable", "target_idx": 4}
{"id": "mod_bwameth_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of BS-Seq reads using bwameth (tools: bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_blastdbcmd": null, "fasta_index_methylseq": null, "bwameth_align": null, "parabricks_fq2bammeth": null, "openms_textexporter": null}}, "target": "bwameth_align", "target_idx": 2}
{"id": "schema_std_alleleexpression_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/alleleexpression", "description": "Alleleexpression is a nf-core pipeline for allele-specific expression (ASE) analysis using STAR-WASP for alignment, UMI-tools for deduplication, and phaser for haplotype phasing and ASE detection.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/alleleexpression?", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,fastq_1,fastq_2,vcf": null, "sample,nuclear_image,spot_table,membrane_image": null}}, "target": "sample,fastq_1,fastq_2,vcf", "target_idx": 2}
{"id": "mod_xeniumranger_importsegmentation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger importsegmentation module runs `xeniumranger import-segmentation`\nto recompute Xenium Onboard Analysis outputs using external segmentation results.\nIt supports two execution modes mirroring the Xenium Ranger CLI: an image-based\nmode that accepts nuclei and/or cell masks (TIFF/NPY) or GeoJSON polygons together\nwith optional coordinate transforms and unit definitions, and a transcript-based\nmode that ingests Baysor-style transcript assignment CSV files plus visualization\npolygons. Use the image-based inputs when providing label masks or polygons, or\nswitch to the transcript-based inputs when supplying transcript-level assignments\nso the appropriate command-line arguments are passed to Xenium Ranger. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scimap_mcmicro": "SCIMAP is a suite of tools that enables spatial single-cell analyses", "pypgx_createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "proseg_proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity", "xeniumranger_importsegmentation": "The xeniumranger importsegmentation module runs `xeniumranger import-segmentation`\nto recompute Xenium Onboard"}}, "target": "xeniumranger_importsegmentation", "target_idx": 4}
{"id": "resource_aardvark_merge_4", "category": "resource_profiling", "state": {"process": "AARDVARK_MERGE", "tool": "aardvark/merge", "description": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_MERGE (A tool to evaluate and merge multiple variant calls into a consensus VCF.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_pretextsnapshot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to generate images from Pretext contact maps. (tools: pretextsnapshot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellpose": null, "homer/makeucscfile": null, "cooler/merge": null, "bwa/index": null, "pretextsnapshot": null}}, "target": "pretextsnapshot", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_1_6", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_bwa_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWA", "modules": ["bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bwa then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWA (bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_BWA": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_bwa": null}}, "target": "Use nf-core subworkflow fastq_align_bwa", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_2_4", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_all101_marsseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze MARS-seq v2 pre-processing pipeline with velocity. Topics: facs-sorting, mars-seq, single-cell, single-cell-rna-seq, star-solo, transcriptional-dynamics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"marsseq": null, "proteinannotator": null, "scrnaseq": null, "smrnaseq": null, "viralmetagenome": null}}, "target": "marsseq", "target_idx": 0}
{"id": "noul_named_output_channel_access_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fargene_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full-length antiobiotic resistance genes as output. (tools: fargene)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/cutupfasta": null, "busco/busco": null, "fastavalidator": null, "concoct/concoctcoveragetable": null, "fargene": null}}, "target": "fargene", "target_idx": 4}
{"id": "mod_parabricks_minimap2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference database using an accelerated KSW2 to convert FASTQ to BAM/CRAM. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_tblastn": "Queries a BLAST DNA database", "caalm_downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "parabricks_minimap2": "NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference da", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "parabricks_minimap2", "target_idx": 2}
{"id": "subworkflow_pkg_mmseqs_contig_taxonomy_1", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_CONTIG_TAXONOMY", "modules": ["mmseqs/databases", "mmseqs/createdb", "mmseqs/taxonomy", "mmseqs/createtsv"], "description": "Assign taxonomy to contigs using the MMseqs2 workflow."}, "question": {"type": "choice", "instructions": "How should MMSEQS_CONTIG_TAXONOMY (mmseqs/databases, mmseqs/createdb, mmseqs/taxonomy, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow MMSEQS_CONTIG_TAXONOMY": null, "Use nf-core subworkflow mmseqs_contig_taxonomy": null, "Leave them out": null}}, "target": "Use nf-core subworkflow mmseqs_contig_taxonomy", "target_idx": 2}
{"id": "noul_retry_errorstrategy_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_30", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_sourmash_pairwise_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash_pairwise": "Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch.", "drep_compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "sylphtax_taxprof": "Incorporates taxonomy into sylph metagenomic classifier", "kma_kma": "Mapping raw reads directly against redundant databases via KMA alignment", "deeptools_bigwigcompare": "Compare two bigWig files based on the number of mapped reads"}}, "target": "sourmash_pairwise", "target_idx": 0}
{"id": "resource_bedtools_makewindows_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAKEWINDOWS", "tool": "bedtools/makewindows", "description": "Makes adjacent or sliding windows across a genome or BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAKEWINDOWS (Makes adjacent or sliding windows across a genome or BED file.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_bam_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_14", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "schema_std_nanostring_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanostring", "description": "An analysis pipeline for Nanostring nCounter expression data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/nanostring?", "criteria": {"id,fasta,sequence": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1,fastq_2,genome": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null}}, "target": "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_wgs_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay_type": "Long-read Pacific Biosciences HiFi sequencing", "data_format": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "field_constraint_sample_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "format: file-path": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "noul_container_environment_specification_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_umitools_prepareforrsem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make the output from umi_tools dedup or group compatible with RSEM (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_explore_search_plot_tidk": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats\nalong a sliding win", "umitools/dedup": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "umitools/prepareforrsem": "Make the output from umi_tools dedup or group compatible with RSEM", "custom/rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "geoquery/getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)"}}, "target": "umitools/prepareforrsem", "target_idx": 2}
{"id": "mod_refsolver_identify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver (tools: refsolver)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbtk_pbmerge": "Simple tool which merges several PacBio BAM files together", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "biscuit_index": "Indexes a reference genome for use with Biscuit", "shasum": "Print SHA256 (256-bit) checksums.", "refsolver_identify": "Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver"}}, "target": "refsolver_identify", "target_idx": 4}
{"id": "mod_svtk_baftest_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs tests on BAF files (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ea-utils_gtf2bed": "Convert a GTF/GFF annotation file to BED12 format", "svtk_vcf2bed": "Converts VCFs containing structural variants to BED format", "svtk_standardize": "Convert SV calls to a standardized format.", "svtk_baftest": "Performs tests on BAF files", "dragmap_hashtable": "Create DRAGEN hashtable for reference genome"}}, "target": "svtk_baftest", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_5_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq with strandedness.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "schema_std_drop_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/drop", "description": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/drop?", "criteria": {"sample,fastq_1,fastq_2,condition,reference": null, "patient,sample,vcf,status,cna": null, "sample,fastq_1,fastq_2,group": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null}}, "target": "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE", "target_idx": 3}
{"id": "resource_amrfinderplus_run_2", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_RUN", "tool": "amrfinderplus/run", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_RUN (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_agat_spflagshortintrons_3", "category": "resource_profiling", "state": {"process": "AGAT_SPFLAGSHORTINTRONS", "tool": "agat/spflagshortintrons", "description": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting the data to EBI.\n(Typical EBI error message: ********ERROR: Intron usually expected to be at least 10 nt long. Please check the accuracy)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFLAGSHORTINTRONS (The script flags the short introns with the attribute <pseudo>. Is is usefull to) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_openms_idscoreswitcher_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Switches between different scores of peptide or protein hits in identification data (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse2/chunk": null, "shapeit5/switch": null, "genmod/score": null, "openms/idscoreswitcher": null, "carveme/carve": null}}, "target": "openms/idscoreswitcher", "target_idx": 3}
{"id": "field_constraint_expected_cells_0_14", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"enum: [auto, single, paired]": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "mod_odgi_viz_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualize a variation graph in 1D. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/fastq": "Convert a BAM file to interleaved FASTQ format with fgumi", "pbjasmine": "Identify specific base modifications in PacBio HiFi reads by analyzing polymerase kinetic signatures", "odgi/layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "odgi/viz": "Visualize a variation graph in 1D.", "odgi/draw": "Draw previously-determined 2D layouts of the graph with diverse annotations."}}, "target": "odgi/viz", "target_idx": 3}
{"id": "local_subworkflow_daisribosome_2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for DAISRIBOSOME (dais).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow daisribosome": null, "Local subworkflow DAISRIBOSOME": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 3}
{"id": "mod_ivar_trim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim primer sequences rom a BAM file with iVar (tools: ivar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eido_convert": null, "bbmap_bbduk": null, "ivar_trim": null, "gatk4_estimatelibrarycomplexity": null, "ivar_variants": null}}, "target": "ivar_trim", "target_idx": 2}
{"id": "mod_shasum_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Print SHA256 (256-bit) checksums. (tools: md5sum)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone/check": "Check that files in source and destination paths match", "shasum": "Print SHA256 (256-bit) checksums.", "shigeifinder": "Determine Shigella serotype from assemblies or Illumina paired-end reads", "clair3": "Clair3 is a germline small variant caller for long-reads", "md5sum": "Create MD5 (128-bit) checksums"}}, "target": "shasum", "target_idx": 1}
{"id": "mod_miniprot_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: miniprot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"miniprot/align": null, "anota2seq/anota2seqrun": null, "ampcombi2/cluster": null, "parabricks/starfusion": null, "bamaligncleaner": null}}, "target": "miniprot/align", "target_idx": 0}
{"id": "resource_atlas_pmd_3", "category": "resource_profiling", "state": {"process": "ATLAS_PMD", "tool": "atlas/pmd", "description": "Estimate the post-mortem damage patterns of DNA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_PMD (Estimate the post-mortem damage patterns of DNA) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "intent_prepare_data_10", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "prepare_data", "target_idx": 1}
{"id": "mod_seqkit_head_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subset FASTA/FASTQ files to some number of sequences (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "seqkit/head": "Subset FASTA/FASTQ files to some number of sequences", "idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)", "bbmap/filterbyname": "Filter out sequences by sequence header name(s)", "odgi/viz": "Visualize a variation graph in 1D."}}, "target": "seqkit/head", "target_idx": 1}
{"id": "mod_gcta_bivariateremlldms_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run bivariate REML-LDMS analysis with an MGRM manifest (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "gcta_calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups", "seqkit_sana": "Sanitize broken single line FASTQ files", "plink_indep": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other.", "gcta_fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs"}}, "target": "gcta_bivariateremlldms", "target_idx": 0}
{"id": "noul_process_conditional_execution_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/chipseq --input samplesheet.csv (Assay: ChIP-seq with IP and input control design)", "question": {"type": "choice", "instructions": "Which columns are standard for ChIP-seq with IP and input control design input samplesheet?", "criteria": {"sample,antibody,control": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "samplesheet_arch_bulk_small_rna_3_0", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Small RNA / miRNA sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_12", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_3_2", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Trio exome/genome sequencing (Proband, Mother, Father) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_blobtk_plot_4", "category": "resource_profiling", "state": {"process": "BLOBTK_PLOT", "tool": "blobtk/plot", "description": "Creates differing styles of blobplots depending on provided arguments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_PLOT (Creates differing styles of blobplots depending on provided arguments.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_fastq_2_1_6", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "mod_variantextractor_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deterministic and standard extractor of SNVs, indels and structural variants (SVs)\nfrom VCF files. Homogenizes multiallelic variants, MNPs and SVs (including imprecise\npaired breakends and single breakends) to facilitate downstream processing. (tools: variant-extractor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aria2": "CLI Download utility", "upd": "Simple software to call UPD regions from germline exome/wgs trios.", "variantextractor": "Deterministic and standard extractor of SNVs, indels and structural variants (SVs)\nfrom VCF files. Homogenizes", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "variantextractor", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_9", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_abyss_abysspe_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes. (tools: abyss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertspgff2tsv": null, "abyss_abysspe": null, "agat_convertspgxf2gxf": null, "variancepartition_dream": null, "metabat2_metabat2": null}}, "target": "abyss_abysspe", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Trio exome/genome sequencing (Proband, Mother, Father))", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_fastq_2_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "mod_stranger_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates output files from ExpansionHunter with the pathologic implications of the repeat sizes. (tools: stranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_filtersamreads": null, "expansionhunterdenovo_profile": null, "pigz_uncompress": null, "gangstr": null, "stranger": null}}, "target": "stranger", "target_idx": 4}
{"id": "mod_picard_filtersamreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters SAM/BAM files to include/exclude either aligned/unaligned reads or based on a read list (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylphtax_merge": "Merge multiple taxonomic profiles from sylphtaxt/taxprof into a tsv table", "ascat": "copy number profiles of tumour cells.", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "blast_blastdbcmd": "Retrieve entries from a BLAST database", "picard_filtersamreads": "Filters SAM/BAM files to include/exclude either aligned/unaligned reads or based on a read list"}}, "target": "picard_filtersamreads", "target_idx": 4}
{"id": "resource_annotsv_installannotations_0", "category": "resource_profiling", "state": {"process": "ANNOTSV_INSTALLANNOTATIONS", "tool": "annotsv/installannotations", "description": "Install the AnnotSV annotations"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_INSTALLANNOTATIONS (Install the AnnotSV annotations) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_sylph_sketch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sketching/indexing sequencing reads (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylph/sketch": null, "skani/dist": null, "seqtk/sample": null, "mcstaging/macsima2mc": null, "mash/sketch": null}}, "target": "sylph/sketch", "target_idx": 0}
{"id": "field_constraint_bam_0_3", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "subworkflow_pkg_bam_stats_mirna_mirtop_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STATS_MIRNA_MIRTOP", "modules": ["mirtop/gff", "mirtop/counts", "mirtop/export", "mirtop/stats"], "description": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 format."}, "question": {"type": "choice", "instructions": "How should BAM_STATS_MIRNA_MIRTOP (mirtop/gff, mirtop/counts, mirtop/export, mirtop/stats) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_stats_mirna_mirtop": null, "Leave them out": null, "Local subworkflow BAM_STATS_MIRNA_MIRTOP": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_stats_mirna_mirtop", "target_idx": 0}
{"id": "mod_bam_markduplicates_picard_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats (tools: bam_markduplicates_picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_markduplicates_picard": null, "biobambam/bammarkduplicates2": null, "optitype": null, "picard/markduplicates": null, "biscuit/align": null}}, "target": "bam_markduplicates_picard", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_pypgx_computecontrolstatistics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute summary statistics for control gene from BAM files. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paraphase": "HiFi-based caller for highly homologous genes", "gatk4/cnnscorevariants": "Apply a Convolutional Neural Net to filter annotated variants", "pypgx/computecontrolstatistics": "Compute summary statistics for control gene from BAM files.", "pypgx/preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "pypgx/createinputvcf": "Call SNVs/indels from BAM files for all target genes."}}, "target": "pypgx/computecontrolstatistics", "target_idx": 2}
{"id": "mod_busco_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download database for BUSCO (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp_estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "emboss_revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "busco_busco": "Benchmarking Universal Single Copy Orthologs", "busco_plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "busco_download": "Download database for BUSCO"}}, "target": "busco_download", "target_idx": 4}
{"id": "samplesheet_arch_riboseq_profiling_3_2", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Ribosome profiling (Ribo-seq) footprint sequencing with entry step FASTQC.", "criteria": {"sample,cdna_fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "local_subworkflow_preparereports_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should PREPAREREPORTS (custom/preparereports, multiqc) be built?", "criteria": {"Local subworkflow PREPAREREPORTS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow preparereports": null, "Leave them out": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 0}
{"id": "schema_std_riboseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "description": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/riboseq?", "criteria": {"id,fasta,reference,optional_data,template": null, "sample,fastq_1,fastq_2,strandedness,type": null, "family_id,sample,file_path,hpo_terms,sex": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness,type", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_10", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic cancer variant calling with tumor-normal pairs. Input files: Paired-end FASTQs for patient tumor and germline normal tissue.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_multiple_script_sections_invalid_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/metatdenovo --input samplesheet.csv (Assay: Environmental community metatranscriptomics de novo assembly)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "mod_truvari_bench_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Given baseline and comparison sets of variants, calculate the recall/precision/f-measure (tools: truvari)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_runl1": "Finish REGENIE step 1 from split level-0 prediction files", "truvari_bench": "Given baseline and comparison sets of variants, calculate the recall/precision/f-measure", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "vclust_prefilter": "The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by ", "caddsv_run": "Score structural variants with CADD-SV."}}, "target": "truvari_bench", "target_idx": 1}
{"id": "mod_kraken2_buildstandard_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads and builds Kraken2 standard database (tools: kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/bracken": null, "vrhyme/extractunbinned": null, "gatk4/printsvevidence": null, "kraken2/buildstandard": null, "argnorm": null}}, "target": "kraken2/buildstandard", "target_idx": 3}
{"id": "field_constraint_bam_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "core_tool_samtools_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Coordinate-sorting, indexing, and statistics generation for genome-aligned BAM binary alignment files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bamtools": "C++ API and toolkit for BAM", "sambamba": "Fast BAM manipulation", "samtools": "Reading/writing/sorting/indexing/viewing SAM/BAM/CRAM format alignments", "bedtools": "Genomic arithmetic tools", "picard": "Java-based BAM utilities"}}, "target": "samtools", "target_idx": 2}
{"id": "resource_bcftools_csq_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CSQ", "tool": "bcftools/csq", "description": "bcftools Haplotype-aware consequence caller"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CSQ (bcftools Haplotype-aware consequence caller) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_merquryfk_katcomp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A reimplemenation of Kat Comp to work with FastK databases (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastk/fastk": null, "osfclient/fetch": null, "fastk/merge": null, "merquryfk/katcomp": null, "haplogrep3/classify": null}}, "target": "merquryfk/katcomp", "target_idx": 3}
{"id": "mod_biobambam_bammarkduplicates2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Locate and tag duplicate reads in a BAM file (tools: biobambam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_markduplicates": "Locate and tag duplicate reads in a BAM file", "vcflib_vcfuniq": "List unique genotypes. Like GNU uniq, but for VCF records. Remove records which have the same position, ref, a", "sambamba_markdup": "find and mark duplicate reads in BAM file", "dupblaster": "Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline ", "biobambam_bammarkduplicates2": "Locate and tag duplicate reads in a BAM file"}}, "target": "biobambam_bammarkduplicates2", "target_idx": 4}
{"id": "intent_ask_question_0", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "ask_question", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_5_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ", "pipeline": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/genomeassembler, determine the input samplesheet column structure for: Long-read Pacific Biosciences HiFi sequencing.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_47", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "intent_prepare_data_4", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "prepare_data", "target_idx": 1}
{"id": "mod_trnascanse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detection of tRNA sequences using covariance models (tools: trnascanse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"transdecoder_predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "trnascanse": "Detection of tRNA sequences using covariance models", "msisensorpro_pro": "MSIsensor-pro/pro is a tool used to evaluate MSI using single (tumor) sample sequencing data", "kraken2_buildstandard": "Downloads and builds Kraken2 standard database", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope"}}, "target": "trnascanse", "target_idx": 1}
{"id": "mod_bedtools_subtract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining portion of A. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "preseq_ccurve": "Software for predicting library complexity and genome coverage in high-throughput sequencing", "sentieon_dnamodelapply": "modifies the input VCF file by adding the MLrejected FILTER to the variants", "bedtools_subtract": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining po"}}, "target": "bedtools_subtract", "target_idx": 4}
{"id": "samplesheet_arch_amplicon_16s_paired_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for 16S rRNA / ITS microbiome amplicon profiling. Input files: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,otu_table": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_5_3", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral genome sequencing on Oxford Nanopore MinION / GridION.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_33", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_syri_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements. (tools: syri)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"irescue": "Quantification of transposable elements expression in scRNA-seq", "syri": "Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearran", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "hmmer/hmmrank": "R script that scores output from multiple runs of hmmer/hmmsearch"}}, "target": "syri", "target_idx": 1}
{"id": "core_tool_cellranger_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Demultiplexing, barcode processing, alignment, and UMI counting for 10x Genomics single-cell RNA-seq libraries.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"starsolo": null, "alevin": null, "kallisto_bustools": null, "cellranger": null, "seurat": null}}, "target": "cellranger", "target_idx": 3}
{"id": "noul_channel_operator_map_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_catpack_contigs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/download": "Downloads the required files for either Nr or GTDB for building into a CAT database", "catpack/contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).", "catpack/reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "dssp/mkdssp": "Calculates secondary structure assignments from PDB files using mkdssp (DSSP).\nDSSP is a standard tool for ass", "bedtools/bamtobed": "Converts a bam file to a bed12 file."}}, "target": "catpack/contigs", "target_idx": 1}
{"id": "mod_busco_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BUSCO summary plot generation using the built-in 'busco --plot' command (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "amulety_balmpaired": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety.", "busco_plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "abacas": "Contiguate draft genome assembly"}}, "target": "busco_plot", "target_idx": 2}
{"id": "mod_mashtree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly create a tree using Mash distances (tools: mashtree)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "mashtree": "Quickly create a tree using Mash distances", "custom_bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "pbptyper": "Assign PBP type of Streptococcus pneumoniae assemblies", "orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics."}}, "target": "mashtree", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_26", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_bcftools_plugintag2tag_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINTAG2TAG", "tool": "bcftools/plugintag2tag", "description": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINTAG2TAG (Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_vcfexpress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter a VCF/BCF and optionally print by template expression. If no template is given the output will be VCF/BCF (tools: vcfexpress)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequenzautils/gcwiggle": "Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggl", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "vcfexpress": "Filter a VCF/BCF and optionally print by template expression. If no template is given the output will be VCF/B", "fastq_align_dna": "Align fastq files to a reference genome", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "vcfexpress", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_7_0", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "data_format": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "resource_busco_download_4", "category": "resource_profiling", "state": {"process": "BUSCO_DOWNLOAD", "tool": "busco/download", "description": "Download database for BUSCO"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_DOWNLOAD (Download database for BUSCO) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_22", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_proovframe_fix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: frame-shift correction for long read (meta)genomics - fix frameshifts in reads (tools: proovframe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju/kaiju2krona": "Convert Kaiju's tab-separated output file into a tab-separated text file which can be imported into Krona.", "transrate": "Reference-free and reference-based quality assessment of de novo transcriptome\nassemblies. Only sequence-based", "primerprospector/analyzeprimers": "Score PCR primers for binding to target sequences", "savana/to": "Tumour-only somatic SV calling with optional copy-number analysis in SAVANA", "proovframe/fix": "frame-shift correction for long read (meta)genomics - fix frameshifts in reads"}}, "target": "proovframe/fix", "target_idx": 4}
{"id": "mod_bedgraph_bedclip_bedgraphtobigwig_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert bedgraph to bigwig with clip (tools: bedgraph_bedclip_bedgraphtobigwig)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedgraph_bedclip_bedgraphtobigwig": "Convert bedgraph to bigwig with clip", "openms_peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)", "bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity", "bedtools_unionbedg": "Combines multiple BedGraph files into a single file"}}, "target": "bedgraph_bedclip_bedgraphtobigwig", "target_idx": 0}
{"id": "resource_amulety_antiberta2_5", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTA2", "tool": "amulety/antiberta2", "description": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTA2 (A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_1_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "schema_std_fastquorum_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/fastquorum. Description: Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/fastquorum.", "criteria": {"sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,library_id,lane": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "sample,fastq_1,fastq_2,library_id,lane", "target_idx": 1}
{"id": "field_constraint_fastq_1_1_14", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "resource_ataqv_mkarv_3", "category": "resource_profiling", "state": {"process": "ATAQV_MKARV", "tool": "ataqv/mkarv", "description": "mkarv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_MKARV (mkarv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_autocycler_resolve_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Resolve trimmed assembly graphs into final contigs within Autocycler. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_combine": null, "stainwarpy_extractchannel": null, "fasta_consensus_autocycler": null, "diamond_deepclust": null, "autocycler_resolve": null}}, "target": "autocycler_resolve", "target_idx": 4}
{"id": "samplesheet_arch_proteomics_dia_4_1", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions?", "criteria": {"sample,fasta": null, "sample,raw_file,condition": null, "sample,peptides_tsv": null, "sample,mzml": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_0_3", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "noul_channel_mix_operator_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_7_2", "category": "samplesheet_schema", "state": {"technology": "Microbial Assembly", "workflow_entry": "FASTQC", "library_inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "resource_bedgovcf_5", "category": "resource_profiling", "state": {"process": "BEDGOVCF", "tool": "bedgovcf", "description": "Convert a BED file to a VCF file according to a YAML config"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDGOVCF (Convert a BED file to a VCF file according to a YAML config) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_createpanelrefs_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createpanelrefs", "assay": "createpanelrefs pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/createpanelrefs (Generate Panel of Normals, models or other similar reference)?", "criteria": {"id,fasta": null, "sample,bam,bai,cram,crai": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "sample,bam,bai,cram,crai", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_1_5", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "template": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "mod_mcquant_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mcquant extracts single-cell data given a multi-channel image and a segmentation mask. (tools: mcquant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"oarfish_alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "seqkit_split2": "Split single or paired-end fastq.gz files", "mcquant": "Mcquant extracts single-cell data given a multi-channel image and a segmentation mask.", "centrifuger_quantification": "Quantification (taxonomic profiling) of Centrifuger model", "mdust": "mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences"}}, "target": "mcquant", "target_idx": 2}
{"id": "resource_bigslice_downloaddb_5", "category": "resource_profiling", "state": {"process": "BIGSLICE_DOWNLOADDB", "tool": "bigslice/downloaddb", "description": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_DOWNLOADDB (Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nu) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_createtaxdb_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createtaxdb", "assay": "createtaxdb pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/createtaxdb (Parallelised and automated construction of metagenomic class)?", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "id,fasta,reference,optional_data,template": null, "id,taxid,fasta_dna,fasta_aa": null}}, "target": "id,taxid,fasta_dna,fasta_aa", "target_idx": 3}
{"id": "mod_iqtree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a Newick format phylogeny from a multiple sequence alignment using the maximum likelihood algorithm. Capable of bacterial genome size alignments. (tools: iqtree)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"iqtree": "Produces a Newick format phylogeny from a multiple sequence alignment using the maximum likelihood algorithm. ", "fasttree": "Produces a Newick format phylogeny from a multiple sequence alignment. Capable of bacterial genome size alignm", "metabuli/build": "Builds a database for classification with metabuli from FASTA files and a taxonomy", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "cooltools/eigscis": "Perform eigen value decomposition on a cooler matrix to calculate compartment signal by finding the eigenvecto"}}, "target": "iqtree", "target_idx": 0}
{"id": "mod_gatk4_postprocessgermlinecnvcalls_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Postprocesses the output of GermlineCNVCaller and generates VCFs and denoised copy ratios (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"orfm": null, "ascat": null, "gatk4/postprocessgermlinecnvcalls": null, "slamdunk/all": null, "cnvkit/antitarget": null}}, "target": "gatk4/postprocessgermlinecnvcalls", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_16", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "noul_named_output_channel_access_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_7_0", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_14", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_bam_0_12", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "resource_basicpy_3", "category": "resource_profiling", "state": {"process": "BASICPY", "tool": "basicpy", "description": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is developed based on the Matlab version of BaSiC tool with major improvements in the algorithm."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASICPY (BaSiCPy is a python package for background and shading correction of optical mic) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gatk4_genotypegvcfs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform joint genotyping on one or more samples pre-called with HaplotypeCaller. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gecco_run": "GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomi", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4_genotypegvcfs": "Perform joint genotyping on one or more samples pre-called with HaplotypeCaller.", "amulety_antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}}, "target": "gatk4_genotypegvcfs", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "10x Multiome single-cell joint RNA and ATAC chromatin", "data_format": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,matrix": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/metatdenovo --input samplesheet.csv (Assay: Environmental community metatranscriptomics de novo assembly)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/metatdenovo, determine the input samplesheet column structure for: Environmental community metatranscriptomics de novo assembly.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_5_5", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Single-end Oxford Nanopore direct RNA.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_rpbp_preparegenome_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an annotation GTF. Enumerates every\ncandidate open reading frame (ORF) in the annotation (annotated CDSs plus\nalternative start codons within transcript exons), records their genomic\nand per-exon coordinates, and labels them with the transcript and gene\nthey belong to.\n\nInvokes Rp-Bp's `get_orfs` Python function directly, chaining the upstream\nhelpers `gtf-to-bed12`, `extract-bed-sequences`, `extract-orf-coordinates`,\n`split-bed12-blocks` and `label-orfs`. Bypasses Rp-Bp's `prepare-rpbp-genome`\numbrella script, which would also build `bowtie2` (rRNA filtering) and\n`STAR` (alignment) indices - neither is consumed by the Rp-Bp tools\nwrapped here, since alignment is supplied externally as a BAM.\n\nA minimal `chrName.txt` (one contig name per line) is seeded from the\nFASTA headers because `gtf-to-bed12` reads it via `--chr-name-file` to\ncontrol output sort order.\n\nNote: emits the `*.annotated.bed.gz` filenames produced by `get_orfs`\ndirectly, rather than the `*.bed.gz`-renamed forms that the upstream\numbrella `prepare-rpbp-genome` script produces. The downstream module\noutputs and consumers in this module set reference these names\nexplicitly, so the two are functionally equivalent. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqwish_induce": "Induce a variation graph in GFA format from alignments in PAF format", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "samtools_samples": "Write sample names and path to reference genome of an alignment to a text file.", "rpbp_estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "rpbp_preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a"}}, "target": "rpbp_preparegenome", "target_idx": 4}
{"id": "mod_pychopper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify, orient and trim nanopore cDNA reads (tools: pychopper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/sort": null, "biobambam/bamsormadup": null, "gatk4/preprocessintervals": null, "samtools/collatefastq": null, "pychopper": null}}, "target": "pychopper", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_0_25", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_pureclip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as iCLIP and eCLIP. (tools: pureclip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "icountmini/peaks": "Runs iCount peaks on a BED file of crosslinks", "clippy": "Runs the Clippy CLIP peak caller", "utils_nextflow_pipeline": "Subworkflow with functionality that may be useful for any Nextflow pipeline", "multiseqdemux": "Identify singlets, doublets and negative cells from multiplexing experiments. Annotate singlets by tags."}}, "target": "pureclip", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_newick_epang_gappa_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_NEWICK_EPANG_GAPPA", "modules": ["hmmer/hmmbuild", "hmmer/hmmalign", "hmmer/eslalimask", "hmmer/eslreformat", "clustalo/align", "mafft/align", "epang/place", "epang/split", "gappa/examinegraft", "gappa/examineassign", "gappa/examineheattree"], "description": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in nf-core/phyloplace."}, "question": {"type": "choice", "instructions": "How should FASTA_NEWICK_EPANG_GAPPA (hmmer/hmmbuild, hmmer/hmmalign, hmmer/eslalimask, hmmer/eslreformat, clustalo/align, mafft/align, epang/place, epang/split, gappa/examinegraft, gappa/examineassign, gappa/examineheattree) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_newick_epang_gappa": null, "Leave them out": null, "Local subworkflow FASTA_NEWICK_EPANG_GAPPA": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_newick_epang_gappa", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_1_5", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral amplicon sequencing with primers?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bcftools_filter_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_FILTER", "tool": "bcftools/filter", "description": "Filters VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_FILTER (Filters VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bamutil_clipoverlap_0", "category": "resource_profiling", "state": {"process": "BAMUTIL_CLIPOVERLAP", "tool": "bamutil/clipoverlap", "description": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_CLIPOVERLAP (clips overlapping read pairs. When two mates overlap, this tool will clip the re) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_agat_spaddintrons_2", "category": "resource_profiling", "state": {"process": "AGAT_SPADDINTRONS", "tool": "agat/spaddintrons", "description": "Add intron features to gtf/gff file without intron features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPADDINTRONS (Add intron features to gtf/gff file without intron features.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_fgbio_callmolecularconsensusreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls consensus sequences from reads with the same unique molecular tag. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio/callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag.", "metacache/build": "Taxonomic profiling database building with MetaCache", "fgumi/downsample": "Downsample a BAM by UMI family using streaming with fgumi", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "fgbio/collectduplexseqmetrics": "Collects a suite of metrics to QC duplex sequencing data."}}, "target": "fgbio/callmolecularconsensusreads", "target_idx": 0}
{"id": "mod_nanocomp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare multiple runs of long read sequencing data and alignments (tools: nanocomp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "nanocomp": "Compare multiple runs of long read sequencing data and alignments", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "fcs/fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi"}}, "target": "nanocomp", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_2", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_plasmidfinder_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify plasmids in bacterial sequences and assemblies (tools: plasmidfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "dastool_dastool": "DAS Tool binning step.", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "plasmidfinder": "Identify plasmids in bacterial sequences and assemblies", "deseq2_differential": "runs a differential expression analysis with DESeq2"}}, "target": "plasmidfinder", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_0_46", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_24", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_deepsomatic_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepSomatic is an extension of deep learning-based variant caller DeepVariant that takes aligned reads (in BAM or CRAM format) from tumor and normal data, produces pileup image tensors from them, classifies each tensor using a convolutional neural network, and finally reports somatic variants in a standard VCF or gVCF file. (tools: deepsomatic)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_call": null, "deepsomatic": null, "bcftools_consensus": null, "bam_markduplicates_samtools": null, "fasta_consensus_autocycler": null}}, "target": "deepsomatic", "target_idx": 1}
{"id": "intent_debug_error_5", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "debug_error": null, "prepare_data": null}}, "target": "debug_error", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_2", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking. Input files: Circulating tumor DNA FASTQs across patient clinical draw intervals.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking.", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "data_format": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Circulating tumor DNA FASTQs across patient clinical draw intervals?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_ariba_getref_0", "category": "resource_profiling", "state": {"process": "ARIBA_GETREF", "tool": "ariba/getref", "description": "Download and prepare database for Ariba analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_GETREF (Download and prepare database for Ariba analysis) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral genome sequencing on Oxford Nanopore MinION / GridION. Input files: Demultiplexed single-end long reads from tiled viral amplicons.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral genome sequencing on Oxford Nanopore MinION / GridION.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_1_5", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/taxprofiler) for Multi-taxonomic profiling of complex metagenomic shotgun reads. Input files: Short or long reads with run accession and library instrument platform.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,kraken_db": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_fastq_fastqc_umitools_trimgalore_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read QC, UMI extraction and trimming (tools: fastq_fastqc_umitools_trimgalore)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba_getref": "Download and prepare database for Ariba analysis", "ariba_run": "Query input FASTQs against Ariba formatted databases", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "fastq_fastqc_umitools_trimgalore": "Read QC, UMI extraction and trimming", "ldak_thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne"}}, "target": "fastq_fastqc_umitools_trimgalore", "target_idx": 3}
{"id": "mod_drep_compare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs rapid genome comparisons for a group of genomes and visualize their relatedness (tools: drep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"drep_compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "entrezdirect_xtract": "Queries an NCBI database using an UID", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file"}}, "target": "drep_compare", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_31", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bedtools_map_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAP", "tool": "bedtools/map", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAP (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_utils_references_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functionality for dealing with references that may be useful for any Nextflow pipeline (tools: utils_references)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sratools_prefetch": "Download sequencing data from the NCBI Sequence Read Archive (SRA).", "utils_nfcore_pipeline": "Subworkflow with utility functions specific to the nf-core pipeline template", "bam_methyldackel": "Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignmen", "fusioncatcher_build": "Build references for fusioncatcher", "utils_references": "Functionality for dealing with references that may be useful for any Nextflow pipeline"}}, "target": "utils_references", "target_idx": 4}
{"id": "schema_std_proteinannotator_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinannotator", "description": "Generation of sequence-level annotations for amino acid sequences", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/proteinannotator?", "criteria": {"vcf,fasta,genome,site,source": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample_id,img_directory,parameter_file": null, "id,fasta": null}}, "target": "id,fasta", "target_idx": 3}
{"id": "samplesheet_arch_mira_influenza_sc2_6_4", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels", "pipeline": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "Which columns are standard for Custom MIRA-NF Influenza / SC2 pipeline input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_container_environment_specification_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_allelecounter_4", "category": "resource_profiling", "state": {"process": "ALLELECOUNTER", "tool": "allelecounter", "description": "Generates a count of coverage of alleles"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALLELECOUNTER (Generates a count of coverage of alleles) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "core_tool_cellranger_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Demultiplexing, barcode processing, alignment, and UMI counting for 10x Genomics single-cell RNA-seq libraries.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"seurat": "R analysis package", "kallisto_bustools": "Single-cell quantifier", "starsolo": "STAR single-cell mode", "alevin": "Salmon single-cell", "cellranger": "Set of analysis pipelines that process Chromium single cell data to output expression matrices"}}, "target": "cellranger", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_0_16", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_mcmicro_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data.. Topics: bioformats, image-analysis, image-processing, microscopy, multiplexed-imaging, ome-tiff. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "mcmicro", "target_idx": 1}
{"id": "resource_autocycler_compress_5", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMPRESS", "tool": "autocycler/compress", "description": "Package candidate assemblies for clustering by Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMPRESS (Package candidate assemblies for clustering by Autocycler.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_nonpareil_nonpareilcurvesr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate summary reports with raw data for Nonpareil NPO curves, including MultiQC compatible JSON/TSV files (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "ssuissero": "Serotype prediction of Streptococcus suis assemblies", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "vizgenpostprocessing_compiletilesegmentation": "The module compiles segmentation tiles using Vizgen's post-processing tool.", "nonpareil_nonpareilcurvesr": "Generate summary reports with raw data for Nonpareil NPO curves, including MultiQC compatible JSON/TSV files"}}, "target": "nonpareil_nonpareilcurvesr", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_0_40", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_5_5", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: FAIRE-seq / DNAse-seq open chromatin profiling.", "criteria": {"sample,vcf": null, "sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_37", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_atlas_recal_1", "category": "resource_profiling", "state": {"process": "ATLAS_RECAL", "tool": "atlas/recal", "description": "Gives an estimation of the sequencing bias based on known invariant sites"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_RECAL (Gives an estimation of the sequencing bias based on known invariant sites) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_picard_fixmateinformation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Verify mate-pair information between mates and fix if needed (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "transdecoder_predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "minimap2_index": "Provides fasta index required by minimap2 alignment.", "picard_fixmateinformation": "Verify mate-pair information between mates and fix if needed", "gatk4_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group"}}, "target": "picard_fixmateinformation", "target_idx": 3}
{"id": "mod_xeniumranger_resegment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger resegment module allows you to generate a new segmentation of the morphology image space by rerunning the Xenium Onboard Analysis (XOA) segmentation algorithms with modified parameters. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xeniumranger/resegment": "The xeniumranger resegment module allows you to generate a new segmentation of the morphology image space by r", "hisat2/extractsplicesites": "Extracts splicing sites from a gtf files", "xeniumranger/importsegmentation": "The xeniumranger importsegmentation module runs `xeniumranger import-segmentation`\nto recompute Xenium Onboard", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "umitools/dedup": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read."}}, "target": "xeniumranger/resegment", "target_idx": 0}
{"id": "mod_odgi_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct a dynamic succinct variation graph in ODGI format from a GFAv1. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scvitools_scar": null, "odgi_stats": null, "odgi_layout": null, "svdb_merge": null, "odgi_build": null}}, "target": "odgi_build", "target_idx": 4}
{"id": "resource_bismark_methylationextractor_5", "category": "resource_profiling", "state": {"process": "BISMARK_METHYLATIONEXTRACTOR", "tool": "bismark/methylationextractor", "description": "Extracts methylation information for individual cytosines from alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_METHYLATIONEXTRACTOR (Extracts methylation information for individual cytosines from alignments.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_cellranger_mkref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkref command. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs", "arriba_download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "cellranger_mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkref command."}}, "target": "cellranger_mkref", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_3_2", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_bwafastalign_mem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA-FastAlign. (tools: bwafastalign)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3", "slamdunk_map": "Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings.", "sentieon_bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "hmmcopy_generatemap": "Perl script (generateMap.pl) generates the mappability of a genome given a certain size of reads, for input to"}}, "target": "bwafastalign_mem", "target_idx": 0}
{"id": "mod_gatk4_shiftfasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a fasta with the bases shifted by offset (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/shiftfasta": null, "finaletoolkit/fraglengthbins": null, "gatk4/baserecalibrator": null, "homer/findpeaks": null, "gatk4/analyzecovariates": null}}, "target": "gatk4/shiftfasta", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wgs_pe_4_2", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Raw paired-end Illumina WGS FASTQs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_46", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_bio2zarr_vcfpartition_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing. (tools: bio2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_runl0": "Run one REGENIE step 1 level-0 job from a split master file", "bio2zarr_vcfpartition": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing.", "propr_grea": "Perform Gene Ratio Enrichment Analysis", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "atlas_call": "generate VCF file from a BAM file using various calling methods"}}, "target": "bio2zarr_vcfpartition", "target_idx": 1}
{"id": "pipe_all101_nascent_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Nascent Transcription Processing Pipeline. Topics: gro-seq, nascent, pro-seq, rna, transcription, tss. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"marsseq": null, "variantbenchmarking": null, "viralrecon": null, "reportho": null, "nascent": null, "nanoseq": null, "multiplesequencealign": null, "pixelator": null}}, "target": "nascent", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_bam_0_2", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"sample,vcf": null, "patient,sample,bam": null, "patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_1_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "pipe_all101_genomeqc_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Compare the quality of multiple genomes, along with their annotations.. Topics: genome-assembly-evaluation, genomics, phylogenetic-trees, quality-control. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet"}}, "target": "genomeqc", "target_idx": 4}
{"id": "subworkflow_pkg_h5ad_removebackground_barcodes_cellbender_anndata_0", "category": "subworkflow_packaging", "state": {"subworkflow": "H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA", "modules": ["cellbender/removebackground", "anndata/barcodes"], "description": "Use cellbender for empty droplet removal"}, "question": {"type": "choice", "instructions": "How should H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA (cellbender/removebackground, anndata/barcodes) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow h5ad_removebackground_barcodes_cellbender_anndata": null}}, "target": "Use nf-core subworkflow h5ad_removebackground_barcodes_cellbender_anndata", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_23", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_sratools_fasterqdump_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA). (tools: sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"repeatmodeler/builddatabase": "Create a database for RepeatModeler", "geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "crispresso2": "A software pipeline for the analysis of genome editing outcomes from deep sequencing data", "samtools/splitheader": "Extract header lines from a SAM/BAM/CRAM file into separate files depending on type", "sratools/fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA)."}}, "target": "sratools/fasterqdump", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_explore_search_plot_tidk_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_EXPLORE_SEARCH_PLOT_TIDK", "modules": ["seqkit/seq", "seqkit/sort", "tidk/explore", "tidk/plot", "tidk/search"], "description": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats"}, "question": {"type": "choice", "instructions": "How should FASTA_EXPLORE_SEARCH_PLOT_TIDK (seqkit/seq, seqkit/sort, tidk/explore, tidk/plot, tidk/search) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_explore_search_plot_tidk": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_EXPLORE_SEARCH_PLOT_TIDK": null}}, "target": "Use nf-core subworkflow fasta_explore_search_plot_tidk", "target_idx": 0}
{"id": "mod_cnvkit_coverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "bam_dedup_stats_samtools_umicollapse": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats", "cnvkit_coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "paftools_sam2paf": "A program to convert bam into paf.", "cnvkit_batch": "Copy number variant detection from high-throughput sequencing data"}}, "target": "cnvkit_coverage", "target_idx": 2}
{"id": "mod_genin2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genin2 is a lightining-fast bioinformatic tool to predict genotypes for H5 viruses belonging to the European clade 2.3.4.4b. (tools: genin2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genin2": "Genin2 is a lightining-fast bioinformatic tool to predict genotypes for H5 viruses belonging to the European c", "vsearch/sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).", "gatk4/genotypegvcfs": "Perform joint genotyping on one or more samples pre-called with HaplotypeCaller.", "bcftools/pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "pretextsnapshot": "A module to generate images from Pretext contact maps."}}, "target": "genin2", "target_idx": 0}
{"id": "mod_vt_decompose_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: decomposes multiallelic variants into biallelic in a VCF file. (tools: vt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quilt/quilt2": null, "vt/decompose": null, "vcf_impute_glimpse": null, "snpsites": null, "vt/decomposeblocksub": null}}, "target": "vt/decompose", "target_idx": 1}
{"id": "local_subworkflow_prepontreads_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should this step (porechop, nanoplot) be packaged: Nanopore adapter trimming and read quality visualization?", "criteria": {"Local subworkflow PREPONTREADS": null, "Use nf-core subworkflow prepontreads": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 0}
{"id": "pipe_all101_fastqrepair_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, and settles reads that became disordered. Topics: corruption, data-cleaning, data-recovery, fastq, fastq-corrupted, fastq-format. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, "}}, "target": "fastqrepair", "target_idx": 0}
{"id": "mod_minimap2_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides fasta index required by minimap2 alignment. (tools: minimap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": null, "minimap2_index": null, "bowtie_build": null, "crisprcleanr_normalize": null, "htseq_count": null}}, "target": "minimap2_index", "target_idx": 1}
{"id": "mod_sawfish_discover_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SV candidate discovery from PacBio HiFi data (tools: sawfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sawfish/discover": "SV candidate discovery from PacBio HiFi data", "sawfish/jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "saltshaker/plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "metaspace/converter": "Export METASPACE datasets to AnnData and SpatialData objects", "leafcutter/clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter"}}, "target": "sawfish/discover", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_11", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "field_constraint_sample_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"format: file-path": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "resource_agat_convertspgff2gtf_2", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2GTF", "tool": "agat/convertspgff2gtf", "description": "Converts a GFF/GTF file into a proper GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2GTF (Converts a GFF/GTF file into a proper GTF file) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_truvari_segment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalization of SVs into disjointed genomic regions (tools: truvari)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hostile/fetch": "Downloads required reference genomes for Hostile", "annotsv/installannotations": "Install the AnnotSV annotations", "truvari/segment": "Normalization of SVs into disjointed genomic regions", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "circexplorer2/parse": "CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate."}}, "target": "truvari/segment", "target_idx": 2}
{"id": "resource_autocycler_subsample_3", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_SUBSAMPLE", "tool": "autocycler/subsample", "description": "Downsample long-read sequencing data to the requested coverage using Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_SUBSAMPLE (Downsample long-read sequencing data to the requested coverage using Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_callingcards_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline for processing calling cards data. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": null, "mhcquant": null, "callingcards": null, "seqinspector": null, "proteinannotator": null}}, "target": "callingcards", "target_idx": 2}
{"id": "resource_bcftools_plotvcfstats_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLOTVCFSTATS", "tool": "bcftools/plotvcfstats", "description": "Plots the output of bcftools stats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLOTVCFSTATS (Plots the output of bcftools stats) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_6", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cancer_longitudinal_5_4", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Longitudinal cancer monitoring across multiple timepoints.", "criteria": {"patient,sample,bam": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Single-end Oxford Nanopore direct RNA. Input files: Single fastq per sample.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Oxford Nanopore direct RNA with entry step NANOPLOT.", "criteria": {"sample,fastq_1": null, "sample,fast5": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "pipe_all101_createpanelrefs_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Generate Panel of Normals, models or other similar references from lots of samples. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": null, "longraredisease": null, "spatialaxe": null, "clipseq": null, "viralrecon": null, "ribomsqc": null, "isoseq": null, "createpanelrefs": null}}, "target": "createpanelrefs", "target_idx": 7}
{"id": "resource_braker3_4", "category": "resource_profiling", "state": {"process": "BRAKER3", "tool": "braker3", "description": "Gene prediction in novel genomes using RNA-seq and protein homology information"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRAKER3 (Gene prediction in novel genomes using RNA-seq and protein homology information) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_expected_cells_1_10", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "pipe_all101_hadge_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Comprehensive pipeline for donor demultiplexing in single cell. Topics: cell-hashing, deconvolution, demultiplexing, donor-assignment, donor-deconvolution, genetic-demultiplexing. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]"}}, "target": "hadge", "target_idx": 2}
{"id": "pipe_core10_ampliseq_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Fungal ITS1/ITS2 marker gene sequencing to profile soil mycobiome diversity and community composition.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"eager": null, "rnaseq": null, "taxprofiler": null, "scrnaseq": null, "ampliseq": null, "atacseq": null, "chipseq": null, "mag": null, "sarek": null, "viralrecon": null}}, "target": "ampliseq", "target_idx": 4}
{"id": "mod_busco_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BUSCO summary plot generation using the built-in 'busco --plot' command (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "busco/plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "unzipfiles": "Unzip ZIP archive files", "abacas": "Contiguate draft genome assembly", "lofreq/viterbi": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl"}}, "target": "busco/plot", "target_idx": 1}
{"id": "mod_truvari_segment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalization of SVs into disjointed genomic regions (tools: truvari)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quantmsutils_mzmlstatistics": "Generate statistics from mzML files using quantms-utils", "truvari_segment": "Normalization of SVs into disjointed genomic regions", "gstama_polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "truvari_segment", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/methylseq) for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq). Input files: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs.", "question": {"type": "choice", "instructions": "Which columns are standard for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "subworkflow_pkg_bam_variant_demix_boot_freyja_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_DEMIX_BOOT_FREYJA", "modules": ["freyja/variants", "freyja/demix", "freyja/update", "freyja/boot"], "description": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to the Hu-1 reference)"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_DEMIX_BOOT_FREYJA (freyja/variants, freyja/demix, freyja/update, freyja/boot) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VARIANT_DEMIX_BOOT_FREYJA": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_variant_demix_boot_freyja": null}}, "target": "Use nf-core subworkflow bam_variant_demix_boot_freyja", "target_idx": 3}
{"id": "samplesheet_arch_cutandrun_pe_8_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay_type": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "data_format": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,spikein,fastq": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "subworkflow_pkg_abundance_differential_filter_0", "category": "subworkflow_packaging", "state": {"subworkflow": "ABUNDANCE_DIFFERENTIAL_FILTER", "modules": ["limma/differential", "deseq2/differential", "propr/propd", "custom/filterdifferentialtable", "variancepartition/dream"], "description": "A subworkflow for filtering differential abundance results"}, "question": {"type": "choice", "instructions": "How should ABUNDANCE_DIFFERENTIAL_FILTER (limma/differential, deseq2/differential, propr/propd, custom/filterdifferentialtable, variancepartition/dream) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow ABUNDANCE_DIFFERENTIAL_FILTER": null, "Leave them out": null, "Use nf-core subworkflow abundance_differential_filter": null}}, "target": "Use nf-core subworkflow abundance_differential_filter", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Standard Paired-end Whole Genome Sequencing (WGS)", "data_format": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for Standard Paired-end Whole Genome Sequencing (WGS) input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_freyja_demix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: specify the relative abundance of each known haplotype (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja_demix": "specify the relative abundance of each known haplotype", "cnvkit_export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "coverm_genome": "Calculate read coverage per-genome", "delly_call": "Call structural variants", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va"}}, "target": "freyja_demix", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_36", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_kallisto_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create kallisto index (tools: kallisto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tbprofiler/profile": "A tool to detect resistance and lineages of M. tuberculosis genomes", "kallisto/quant": "Computes equivalence classes for reads and quantifies abundances", "saltshaker/plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "quant_tximport_summarizedexperiment": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedEx", "kallisto/index": "Create kallisto index"}}, "target": "kallisto/index", "target_idx": 4}
{"id": "mod_artic_guppyplex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregates fastq files with demultiplexed reads (tools: artic)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"artic_guppyplex": null, "artic_aligntrim": null, "amulety_esm2": null, "artic_minion": null, "xengsort_index": null}}, "target": "artic_guppyplex", "target_idx": 0}
{"id": "mod_picard_collecthsmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects hybrid-selection (HS) metrics for a SAM or BAM file. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "ensemblvep_download": "Ensembl Variant Effect Predictor (VEP). The cache downloading options are controlled through `task.ext.args`.", "graphmap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "picard_collecthsmetrics": "Collects hybrid-selection (HS) metrics for a SAM or BAM file.", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "picard_collecthsmetrics", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_30", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_epang_place_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: phylogenetic placement of query sequences in a reference tree (tools: epang)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cafe": "Analysis of gene family evolution", "epang/place": "phylogenetic placement of query sequences in a reference tree", "gappa/examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "ultra/index": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment", "bedtools/complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}}, "target": "epang/place", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for ATAC-seq chromatin accessibility with biological replicates. Input files: Paired-end Tn5 transposed FASTQs across conditions and replicates.", "question": {"type": "choice", "instructions": "Which columns are standard for ATAC-seq chromatin accessibility with biological replicates input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "mod_pigz_compress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses files with pigz. (tools: pigz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tabix_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files", "crumble": "Controllable lossy compression of BAM/CRAM files", "gcta_reml": "Run univariate REML heritability estimation with a dense GRM", "pigz_compress": "Compresses files with pigz.", "rseqc_junctionsaturation": "compare detected splice junctions to reference gene model"}}, "target": "pigz_compress", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_star_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_STAR", "modules": ["star/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bowtie2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_STAR (star/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_STAR": null, "Use nf-core subworkflow fastq_align_star": null}}, "target": "Use nf-core subworkflow fastq_align_star", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_3_1", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "template": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for RNA gene fusion detection (Arriba, STAR-Fusion) with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_cmaple_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm (tools: cmaple)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_flank": null, "fasttree": null, "cmaple": null, "epang_place": null, "methbat_profile": null}}, "target": "cmaple", "target_idx": 2}
{"id": "schema_std_isoseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/isoseq", "assay": "isoseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/isoseq (Genome annotation with PacBio Iso-Seq. Takes raw subreads as)?", "criteria": {"id,raw_file": null, "id,fasta,sequence": null, "sample,seq_data,pbi,start_from": null, "sample,bundle,image": null}}, "target": "sample,seq_data,pbi,start_from", "target_idx": 2}
{"id": "mod_fasttree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a Newick format phylogeny from a multiple sequence alignment. Capable of bacterial genome size alignments. (tools: fasttree)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"megan_daa2info": "Analyses a DAA file and exports information in text format", "cafe": "Analysis of gene family evolution", "cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm", "catpack_reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "fasttree": "Produces a Newick format phylogeny from a multiple sequence alignment. Capable of bacterial genome size alignm"}}, "target": "fasttree", "target_idx": 4}
{"id": "mod_plink_bmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge a second PLINK binary fileset into the first and write a new combined PLINK binary fileset (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_impute_stitch": "Subworkflow to impute BAM files using STITCH software.\nVariants location to impute are obtain through the lege", "plink/genome": "Calculates identity-by-descent over autosomal SNPs", "plink/indep": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other.", "fastqe": "fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data.", "plink/bmerge": "Merge a second PLINK binary fileset into the first and write a new combined PLINK binary fileset"}}, "target": "plink/bmerge", "target_idx": 4}
{"id": "schema_std_genomeqc_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/genomeqc. Description: Compare the quality of multiple genomes, along with their annotations..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/genomeqc.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,nuclear_image,spot_table,membrane_image": null, "fasta,assembly,ncbi,gff,fastq": null}}, "target": "fasta,assembly,ncbi,gff,fastq", "target_idx": 3}
{"id": "mod_blast_blastn_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a BLAST DNA database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dastool/dastool": "DAS Tool binning step.", "jellyfish/dump": "Dumps the results from a jellyfish binary file into a human readable format", "blast/blastn": "Queries a BLAST DNA database", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "blast/blastn", "target_idx": 2}
{"id": "mod_haplogrep2_classify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: classification into haplogroups (tools: haplogrep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last/split": "Find split or spliced alignments in a MAF file", "segemehl/index": "Generate genome indices for segemehl align", "haplogrep2/classify": "classification into haplogroups", "haplogrep3/classify": "classification into haplogroups", "ganon/classify": "Classify FASTQ files against ganon database"}}, "target": "haplogrep2/classify", "target_idx": 2}
{"id": "mod_upp_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns protein structures using UPP (tools: upp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "ldak_thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "utils_annotation_cache": "Check the path to the annotation cache depending if local or on the cloud, or using annotation-cache itself", "upp_align": "Aligns protein structures using UPP"}}, "target": "upp_align", "target_idx": 4}
{"id": "samplesheet_arch_viral_ont_single_1_4", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_mmseqs_databases_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download an mmseqs-formatted database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_databases": "Download an mmseqs-formatted database", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "samshee": "Module to validate illumina® Sample Sheet v2 files.", "blast_makeblastdb": "Builds a BLAST database", "bigslice_downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big"}}, "target": "mmseqs_databases", "target_idx": 0}
{"id": "noul_mix_operator_async_emission_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_metapep_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze From metagenomes to epitopes and beyond. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"callingcards": null, "metapep": null, "atacseq": null, "smrnaseq": null, "mag": null, "ampliseq": null, "longraredisease": null, "readsimulator": null, "mhcquant": null, "nanoseq": null}}, "target": "metapep", "target_idx": 1}
{"id": "field_constraint_sex_0_1", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "subworkflow_pkg_gtf_hybridmerge_gffcompare_0", "category": "subworkflow_packaging", "state": {"subworkflow": "GTF_HYBRIDMERGE_GFFCOMPARE", "modules": ["gffcompare", "gawk", "bedtools/intersect"], "description": "Build a hybrid GTF by classifying a novel-transcript GTF against a reference"}, "question": {"type": "choice", "instructions": "How should GTF_HYBRIDMERGE_GFFCOMPARE (gffcompare, gawk, bedtools/intersect) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow GTF_HYBRIDMERGE_GFFCOMPARE": null, "Leave them out": null, "Use nf-core subworkflow gtf_hybridmerge_gffcompare": null}}, "target": "Use nf-core subworkflow gtf_hybridmerge_gffcompare", "target_idx": 3}
{"id": "mod_ataqv_mkarv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mkarv function of a corresponding ataqv tool (tools: ataqv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ataqv/ataqv": "ataqv function of a corresponding ataqv tool", "macs3/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "ataqv/mkarv": "mkarv function of a corresponding ataqv tool", "dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "metamaps/mapdirectly": "Maps long reads to a metamaps database"}}, "target": "ataqv/mkarv", "target_idx": 2}
{"id": "resource_abritamr_run_0", "category": "resource_profiling", "state": {"process": "ABRITAMR_RUN", "tool": "abritamr/run", "description": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRITAMR_RUN (A NATA accredited tool for reporting the presence of antimicrobial resistance ge) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedtools_groupby_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GROUPBY", "tool": "bedtools/groupby", "description": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another column."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GROUPBY (Groups features in a BED file by given column(s) and computes summary statistics) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_bai_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "field_constraint_bam_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "field_constraint_bai_1_3", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_46", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_raxmlng_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: RAxML-NG is a phylogenetic tree inference tool which uses maximum-likelihood (ML) optimality criterion. (tools: raxmlng)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"epang_split": null, "cafe": null, "raxmlng": null, "truvari_segment": null, "csvtk_concat": null}}, "target": "raxmlng", "target_idx": 2}
{"id": "schema_std_methylong_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylong", "description": "Extract methylation calls from long reads (ONT/ PacBio) ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/methylong?", "criteria": {"sample,fastq_1,fastq_2,library_id,lane": null, "sample,group,path,ref,method": null, "sample,bam,bai": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null}}, "target": "sample,group,path,ref,method", "target_idx": 1}
{"id": "resource_ampir_5", "category": "resource_profiling", "state": {"process": "AMPIR", "tool": "ampir", "description": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ampir uses a supervised statistical machine learning approach to predict AMPs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPIR (A fast and user-friendly method to predict antimicrobial peptides (AMPs) from an) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hic", "assay_type": "Hi-C chromosome conformation capture mapping", "data_format": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hi-C chromosome conformation capture mapping?", "criteria": {"sample,bed": null, "sample,bam": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_dshbio_splitbed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split features in gzipped BED format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio/splitbed": "Split features in gzipped BED format", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods.", "yak/count": "a tool to build k-mer hash table for fasta and fastq files"}}, "target": "dshbio/splitbed", "target_idx": 0}
{"id": "field_constraint_bam_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_2_0", "category": "samplesheet_schema", "state": {"technology": "Small RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,mirna_id": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "noul_include_modular_process_syntax_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_24", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_single_hyphen_cli_params_error_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_0_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_1_5", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "mod_chewbbaca_createschema_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a schema to determine the allelic profiles of a genome (tools: chewbbaca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chewbbaca/createschema": "Create a schema to determine the allelic profiles of a genome", "cnaqc": "Quality control of copy number data from bulk WGS assays", "mapad/map": "Map short-reads to an indexed reference genome", "ichorcna/createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "humann3/renorm": "Normalizing RPKs to relative abundance"}}, "target": "chewbbaca/createschema", "target_idx": 0}
{"id": "mod_ascat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: copy number profiles of tumour cells. (tools: ascat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_plotheatmap": "plots values produced by deeptools_computematrix as a heatmap", "bamclipper": "This module is used to clip primer sequences from your alignments.", "plastid_metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "ascat": "copy number profiles of tumour cells.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "ascat", "target_idx": 3}
{"id": "intent_debug_error_1", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "debug_error": null, "build_pipeline": null, "prepare_data": null}}, "target": "debug_error", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_3_1", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ATAC-seq chromatin accessibility with biological replicates with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "assay_type": "RNA gene fusion detection (Arriba, STAR-Fusion)", "data_format": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns are standard for RNA gene fusion detection (Arriba, STAR-Fusion) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1": null, "sample,fusion_bed": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_tbprofiler_profile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to detect resistance and lineages of M. tuberculosis genomes (tools: tbprofiler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcroni": null, "bismark_genomepreparation": null, "upp_align": null, "ariba_getref": null, "tbprofiler_profile": null}}, "target": "tbprofiler_profile", "target_idx": 4}
{"id": "noul_default_empty_channel_behavior_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_dedup_bismark_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BISMARK", "modules": ["bismark/align", "samtools/sort", "samtools/index", "bismark/deduplicate", "bismark/methylationextractor", "bismark/coverage2cytosine", "bismark/report", "bismark/summary"], "description": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BISMARK (bismark/align, samtools/sort, samtools/index, bismark/deduplicate, bismark/methylationextractor, bismark/coverage2cytosine, bismark/report, bismark/summary) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_DEDUP_BISMARK": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_dedup_bismark": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bismark", "target_idx": 3}
{"id": "mod_deepsomatic_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepSomatic is an extension of deep learning-based variant caller DeepVariant that takes aligned reads (in BAM or CRAM format) from tumor and normal data, produces pileup image tensors from them, classifies each tensor using a convolutional neural network, and finally reports somatic variants in a standard VCF or gVCF file. (tools: deepsomatic)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepsomatic": "DeepSomatic is an extension of deep learning-based variant caller DeepVariant that takes aligned reads (in BAM", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "metator/pipeline": "Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing an", "bacphlip": "A bacteriophage lifestyle prediction tool", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "deepsomatic", "target_idx": 0}
{"id": "subworkflow_pkg_h5ad_removebackground_barcodes_cellbender_anndata_2", "category": "subworkflow_packaging", "state": {"subworkflow": "H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA", "modules": ["cellbender/removebackground", "anndata/barcodes"], "description": "Use cellbender for empty droplet removal"}, "question": {"type": "choice", "instructions": "How should H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA (cellbender/removebackground, anndata/barcodes) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA": null, "Leave them out": null, "Use nf-core subworkflow h5ad_removebackground_barcodes_cellbender_anndata": null}}, "target": "Use nf-core subworkflow h5ad_removebackground_barcodes_cellbender_anndata", "target_idx": 3}
{"id": "mod_openms_filefilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters peptide/protein identification results by different criteria. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamcmp": null, "agat_spkeeplongestisoform": null, "openms_filefilter": null, "glimpse_phase": null, "umitools_group": null}}, "target": "openms_filefilter", "target_idx": 2}
{"id": "pipe_core10_chipseq_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Mapping transcription factor occupancy across the genome using cross-linked chromatin immunoprecipitation followed by sequencing.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": null, "eager": null, "atacseq": null, "sarek": null, "viralrecon": null, "mag": null, "taxprofiler": null, "scrnaseq": null, "chipseq": null, "rnaseq": null}}, "target": "chipseq", "target_idx": 8}
{"id": "resource_bioawk_4", "category": "resource_profiling", "state": {"process": "BIOAWK", "tool": "bioawk", "description": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOAWK (Bioawk is an extension to Brian Kernighan's awk, adding the support of several c) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bamtools_convert_1", "category": "resource_profiling", "state": {"process": "BAMTOOLS_CONVERT", "tool": "bamtools/convert", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_CONVERT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_miranda_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: miRanda is an algorithm for finding genomic targets for microRNAs (tools: miranda)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop/gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations", "methyldackel/extract": "Extracts per-base methylation metrics from alignments", "miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "tagbam": "A tool for tagging BAM files.", "mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package"}}, "target": "miranda", "target_idx": 2}
{"id": "core_tool_salmon_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Transcript-level abundance estimation and pseudo-alignment directly from raw paired-end RNA-seq FASTQ reads without full genome mapping.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"kallisto": "Near-optimal RNA-seq quantification", "salmon": "Highly accurate and fast transcript-level quantification from RNA-seq reads", "samtools": "Utilities for manipulating SAM/BAM files", "featurecounts": "Count mapped reads for genomic features", "rsem": "Quantification of transcript abundances"}}, "target": "salmon", "target_idx": 1}
{"id": "mod_vembrane_table_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates tabular (TSV) files from VCF/BCF data with flexible Python expressions (tools: vembrane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sawfish_discover": null, "vembrane_table": null, "last_split": null, "atlas_call": null, "aardvark_compare": null}}, "target": "vembrane_table", "target_idx": 1}
{"id": "resource_bedgovcf_3", "category": "resource_profiling", "state": {"process": "BEDGOVCF", "tool": "bedgovcf", "description": "Convert a BED file to a VCF file according to a YAML config"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDGOVCF (Convert a BED file to a VCF file according to a YAML config) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_references_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/references. Description: nf-core/references is a bioinformatics pipeline that build references, for multiple use cases.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/references.", "criteria": {"id,raw_file": null, "vcf,fasta,genome,site,source": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,alleles,mhc_class,filename": null}}, "target": "vcf,fasta,genome,site,source", "target_idx": 1}
{"id": "mod_gcta_calculateldscores_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate LD scores with GCTA and derive GREML-LDMS SNP groups (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptmhmm": null, "gcta_addgrms": null, "gcta_adjustgrm": null, "mirtop_export": null, "gcta_calculateldscores": null}}, "target": "gcta_calculateldscores", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wes_pe_6_0", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Whole Exome Sequencing (WES) target capture input samplesheet?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bedtools_multiinter_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MULTIINTER", "tool": "bedtools/multiinter", "description": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MULTIINTER (Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_kaiju_kaiju2table_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler/digest": "Generate fragment-delimited genomic bins", "conifer": "Calculate confidence scores from Kraken2 output", "kaiju/kaiju2table": "write your description here", "centrifuge/centrifuge": "Classifies metagenomic sequence data", "gatk4/reblockgvcf": "Condenses homRef blocks in a single-sample GVCF"}}, "target": "kaiju/kaiju2table", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_48", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_merquryfk_katgc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A reimplemenation of KatGC to work with FastK databases (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files.", "cnvkit/fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "merquryfk/hapmaker": "Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables", "tcoffee/tcs": "Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just", "merquryfk/katgc": "A reimplemenation of KatGC to work with FastK databases"}}, "target": "merquryfk/katgc", "target_idx": 4}
{"id": "samplesheet_arch_ancient_dna_eager_6_4", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status", "pipeline": "nf-core/eager"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment input samplesheet?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_jellyfish_dump_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dumps the results from a jellyfish binary file into a human readable format (tools: jellyfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_buildcustom": null, "fastk_fastk": null, "artic_minion": null, "jellyfish_dump": null, "ivar_variants": null}}, "target": "jellyfish_dump", "target_idx": 3}
{"id": "pipe_all101_rnavar_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze gatk4 RNA variant calling pipeline. Topics: gatk4, rna, rnaseq, variant-calling, worflow. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": null, "rnavar": null, "dualrnaseq": null, "scnanoseq": null, "rnasplice": null}}, "target": "rnavar", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay_type": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "data_format": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns are standard for CUT&RUN / CUT&TAG chromatin profiling with IgG control input samplesheet?", "criteria": {"sample,spikein,fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_0_2", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_2_5", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_gatk4_samtofastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts BAM/SAM file to FastQ format (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"longphase_haplotag": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi", "bwa_aln": "Find SA coordinates of the input reads for bwa short-read mapping", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "gatk4_samtofastq": "Converts BAM/SAM file to FastQ format"}}, "target": "gatk4_samtofastq", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_2_41", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "schema_std_eager_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay": "eager pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/eager (A fully reproducible and state-of-the-art ancient DNA analys)?", "criteria": {"sample,fastq_1,fastq_2,vcf": null, "sample_id,bam,vcf,library_id,lane": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample_id,mapped,index,file_type": null}}, "target": "sample_id,bam,vcf,library_id,lane", "target_idx": 1}
{"id": "mod_sentieon_hsmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects hybrid-selection (HS) metrics for a SAM or BAM file. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_hisat2": null, "sentieon_hsmetrics": null, "vrhyme_vrhyme": null, "bcftools_pluginimputeinfo": null, "gatk4_collectsvevidence": null}}, "target": "sentieon_hsmetrics", "target_idx": 1}
{"id": "mod_ngscheckmate_vafncm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determining whether sequencing data comes from the same individual by using SNP matching. This module generates PT files from a bed file containing individual positions. (tools: ngscheckmate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngscheckmate/patterngenerator": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "mygene": "Fetch the GO concepts for a list of genes", "ngscheckmate/vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "fastq_ngscheckmate": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set"}}, "target": "ngscheckmate/vafncm", "target_idx": 2}
{"id": "mod_concoct_extractfastabins_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a FASTA file for each new cluster assigned by CONCOCT (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "fusioncatcher/build": "Build references for fusioncatcher", "dastool/dastool": "DAS Tool binning step.", "concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl"}}, "target": "concoct/extractfastabins", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_star_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_STAR", "modules": ["star/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bowtie2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_STAR (star/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_ALIGN_STAR": null, "Use nf-core subworkflow fastq_align_star": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_star", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/pacvar --input samplesheet.csv (Assay: PacBio HiFi unaligned BAM variant calling)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/pacvar, determine the input samplesheet column structure for: PacBio HiFi unaligned BAM variant calling.", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_14", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_1_2", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate", "pipeline": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "resource_bowtie2_align_4", "category": "resource_profiling", "state": {"process": "BOWTIE2_ALIGN", "tool": "bowtie2/align", "description": "Align reads to a reference genome using bowtie2"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_ALIGN (Align reads to a reference genome using bowtie2) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_shapeit5_switch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Program to compute switch error rate and genotyping error rate given simulated or trio data. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shapeit5/switch": "Program to compute switch error rate and genotyping error rate given simulated or trio data.", "fastq_removeadapters_merge": "Remove adapters and merge reads based on various module choices", "glimpse2/splitreference": "Tool to create a binary reference panel for quick reading time.", "hmmer/hmmstat": "display summary statistics for each profile HMM in an HMM database file", "hiphase": "Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across "}}, "target": "shapeit5/switch", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_0_1", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_differential_functional_enrichment_1", "category": "subworkflow_packaging", "state": {"subworkflow": "DIFFERENTIAL_FUNCTIONAL_ENRICHMENT", "modules": ["gprofiler2/gost", "gsea/gsea", "decoupler/decoupler", "propr/grea", "custom/tabulartogseagct", "custom/tabulartogseacls", "custom/tabulartogseachip"], "description": "Run functional analysis on differential abundance analysis output"}, "question": {"type": "choice", "instructions": "How should DIFFERENTIAL_FUNCTIONAL_ENRICHMENT (gprofiler2/gost, gsea/gsea, decoupler/decoupler, propr/grea, custom/tabulartogseagct, custom/tabulartogseacls, custom/tabulartogseachip) be structured in DSL2?", "criteria": {"Local subworkflow DIFFERENTIAL_FUNCTIONAL_ENRICHMENT": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow differential_functional_enrichment": null}}, "target": "Use nf-core subworkflow differential_functional_enrichment", "target_idx": 3}
{"id": "schema_std_variantbenchmarking_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/variantbenchmarking", "description": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/variantbenchmarking?", "criteria": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "id,test_vcf,test_regions,caller,subsample": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample,seed": null}}, "target": "id,test_vcf,test_regions,caller,subsample", "target_idx": 1}
{"id": "pipe_all101_taxprofiler_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for classification. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "metapep": "From metagenomes to epitopes and beyond", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina"}}, "target": "taxprofiler", "target_idx": 4}
{"id": "pipe_all101_hlatyping_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Precision HLA typing from next-generation sequencing data. Topics: dna, hla, hla-typing, immunology, optitype, personalized-medicine. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "seqsubmit": "nf-core pipeline for data submission to ENA", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders"}}, "target": "hlatyping", "target_idx": 4}
{"id": "pipe_all101_spatialaxe_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data. Topics: 10x-genomics, atera, image-processing, spatial, spatial-data-analysis, spatial-transcriptomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": null, "viralintegration": null, "cageseq": null, "spatialaxe": null, "seqinspector": null, "rnasplice": null, "drugresponseeval": null, "rnafusion": null}}, "target": "spatialaxe", "target_idx": 3}
{"id": "mod_tesorter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An accurate and fast method to classify LTR-retrotransposons in plant genomes (tools: tesorter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "tesorter": "An accurate and fast method to classify LTR-retrotransposons in plant genomes", "eklipse": "tool for detection and quantification of large mtDNA rearrangements.", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "tesorter", "target_idx": 1}
{"id": "field_constraint_phenotype_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "format: file-path": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_0_2", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_core10_eager_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Ancient DNA (aDNA) analysis pipeline for damage pattern estimation and paleogenomic mapping.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"atacseq": null, "viralrecon": null, "chipseq": null, "sarek": null, "mag": null, "eager": null, "ampliseq": null, "scrnaseq": null, "rnaseq": null, "taxprofiler": null}}, "target": "eager", "target_idx": 5}
{"id": "samplesheet_arch_smartseq_plate_based_4_2", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates?", "criteria": {"sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,matrix": null, "plate,sample,bam": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_module_metadata_propagation_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_prepare_data_12", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "prepare_data", "target_idx": 1}
{"id": "mod_concoct_concoctcoveragetable_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate the input coverage table for CONCOCT using a BEDFile (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/mergecutupclustering": "Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py", "concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "concoct/cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "gatk4spark/markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat"}}, "target": "concoct/concoctcoveragetable", "target_idx": 1}
{"id": "resource_baysor_preview_4", "category": "resource_profiling", "state": {"process": "BAYSOR_PREVIEW", "tool": "baysor/preview", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_PREVIEW (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_status_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_gatk4_mutect2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call somatic SNVs and indels via local assembly of haplotypes. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer/pos2bed": "Converting from HOMER peak to BED file formats", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4/mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "fastk/merge": "A tool to merge FastK histograms"}}, "target": "gatk4/mutect2", "target_idx": 3}
{"id": "mod_samtools_getrg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: filter/convert SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/sortsam": "Sorts BAM/SAM files based on a variety of picard specific criteria", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "infernal/cmsearch": "Search covariance models against a sequence database", "samtools/getrg": "filter/convert SAM/BAM/CRAM file"}}, "target": "samtools/getrg", "target_idx": 4}
{"id": "noul_undeclared_process_file_inputs_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_6_5", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Multiome single-cell joint RNA and ATAC chromatin input samplesheet?", "criteria": {"sample,bam": null, "sample,matrix": null, "sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/chipseq) for ChIP-seq with IP and input control design. Input files: Paired-end FASTQ reads for immunoprecipitation and input chromatin.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "mod_mobsuite_typer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bacterial plasmid typing and mobility prediction (tools: mobsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mobsuite/typer": null, "amrfinderplus/run": null, "ltrharvest": null, "gzrt": null, "abricate/run": null}}, "target": "mobsuite/typer", "target_idx": 0}
{"id": "local_subworkflow_nextclade_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should this step (nextclade/run) be packaged: Viral clade typing and QC?", "criteria": {"Leave them out": null, "Local subworkflow NEXTCLADE": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow nextclade": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 1}
{"id": "mod_gatk_unifiedgenotyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SNP and Indel variant caller on a per-locus basis (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamclipper": "This module is used to clip primer sequences from your alignments.", "gatk_unifiedgenotyper": "SNP and Indel variant caller on a per-locus basis", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "glimpse_phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods"}}, "target": "gatk_unifiedgenotyper", "target_idx": 1}
{"id": "samplesheet_arch_scrna_multiome_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "10x Multiome single-cell joint RNA and ATAC chromatin", "data_format": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Multiome single-cell joint RNA and ATAC chromatin with entry step FASTQC.", "criteria": {"sample,matrix": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq. Input files: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,matrix": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_abricate_run_3", "category": "resource_profiling", "state": {"process": "ABRICATE_RUN", "tool": "abricate/run", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_RUN (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_ariba_run_1", "category": "resource_profiling", "state": {"process": "ARIBA_RUN", "tool": "ariba/run", "description": "Query input FASTQs against Ariba formatted databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_RUN (Query input FASTQs against Ariba formatted databases) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "assay_type": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "data_format": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "core_tool_bwa_mem_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Fast short-read DNA sequence alignment against reference genome creating sorted SAM/BAM alignments for variant calling.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bowtie2": "Short read aligner", "star": "RNA-seq aligner", "salmon": "Pseudo-aligner", "bwa_mem": "Burrows-Wheeler Aligner for short-read DNA mapping", "minimap2": "Long/short read aligner"}}, "target": "bwa_mem", "target_idx": 3}
{"id": "schema_std_spatialaxe_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/spatialaxe. Description: A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/spatialaxe.", "criteria": {"sample,fastq_1": null, "family_id,sample,file_path,hpo_terms,sex": null, "gene_name,alignment,tree,suite,tool": null, "sample,bundle,image": null}}, "target": "sample,bundle,image", "target_idx": 3}
{"id": "mod_viber_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multisample subclonal deconvolution of cancer genome sequencing data. (tools: viber)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hackgap_count": "Fast, JIT-compiled k-mer counter supporting both contiguous and gapped k-mers using multi-way bucketed Cuckoo ", "pairtools_sort": "Sort a .pairs/.pairsam file", "viber": "Multisample subclonal deconvolution of cancer genome sequencing data.", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "viber", "target_idx": 2}
{"id": "mod_viennarna_rnalfold_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculate locally stable secondary structures of RNAs (tools: viennarna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"viennarna_rnalfold": "calculate locally stable secondary structures of RNAs", "macse_refinealignment": "improves the input nucleotide alignment in a codon-aware manner", "fusioncatcher_build": "Build references for fusioncatcher", "last_lastal": "Aligns query sequences to target sequences indexed with lastdb", "fusioncatcher_fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data"}}, "target": "viennarna_rnalfold", "target_idx": 0}
{"id": "subworkflow_pkg_bam_qc_picard_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_PICARD", "modules": ["picard/collectmultiplemetrics", "picard/collectwgsmetrics", "picard/collecthsmetrics"], "description": "Produces comprehensive statistics from BAM file"}, "question": {"type": "choice", "instructions": "How should BAM_QC_PICARD (picard/collectmultiplemetrics, picard/collectwgsmetrics, picard/collecthsmetrics) be structured in DSL2?", "criteria": {"Local subworkflow BAM_QC_PICARD": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_qc_picard": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_qc_picard", "target_idx": 2}
{"id": "field_constraint_bai_0_10", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "mod_gstama_collapse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collapse redundant transcript models in Iso-Seq data. (tools: tama_collapse.py)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_tumor_normal_somatic_variant_calling_gatk": "Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode.\nf1r2 output o", "gstama_polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)", "gstama_merge": "Merge multiple transcriptomes while maintaining source information.", "vclust_prefilter": "The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by ", "gstama_collapse": "Collapse redundant transcript models in Iso-Seq data."}}, "target": "gstama_collapse", "target_idx": 4}
{"id": "mod_autocycler_subsample_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downsample long-read sequencing data to the requested coverage using Autocycler. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_consensus_autocycler": null, "midas/run": null, "entrezdirect/esearch": null, "autocycler/subsample": null, "autocycler/cluster": null}}, "target": "autocycler/subsample", "target_idx": 3}
{"id": "mod_openmsthirdparty_cometadapter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates MS/MS spectra using Comet. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openmsthirdparty_cometadapter": "Annotates MS/MS spectra using Comet.", "gatk4_splitncigarreads": "Splits reads that contain Ns in their cigar string", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O"}}, "target": "openmsthirdparty_cometadapter", "target_idx": 0}
{"id": "resource_bismark_coverage2cytosine_3", "category": "resource_profiling", "state": {"process": "BISMARK_COVERAGE2CYTOSINE", "tool": "bismark/coverage2cytosine", "description": "Relates methylation calls back to genomic cytosine contexts."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_COVERAGE2CYTOSINE (Relates methylation calls back to genomic cytosine contexts.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_46", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_paraphrase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parse and annotate paraphrase JSONs (tools: paraphrase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_trim": null, "scds": null, "autocycler_combine": null, "plink_hwe": null, "paraphrase": null}}, "target": "paraphrase", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/pacvar) for PacBio HiFi unaligned BAM variant calling. Input files: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities.", "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "mod_bwa_sampe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert paired-end bwa SA coordinate files to SAM format (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt/hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "bwa/aln": "Find SA coordinates of the input reads for bwa short-read mapping", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "bwa/sampe": "Convert paired-end bwa SA coordinate files to SAM format", "bwa/samse": "Convert bwa SA coordinate file to SAM format"}}, "target": "bwa/sampe", "target_idx": 3}
{"id": "pipe_all101_hadge_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for cell-hashing. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr"}}, "target": "hadge", "target_idx": 8}
{"id": "intent_build_pipeline_0", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "build_pipeline", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_0_0", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "mod_cnvpytor_partition_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate segmentation for specified bin size (multiple bin sizes separate by space) (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "longstitch": "\"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - ", "cnvpytor/partition": "Calculate segmentation for specified bin size (multiple bin sizes separate by space)", "sourmash/compare": "Compare many FracMinHash signatures generated by sourmash sketch."}}, "target": "cnvpytor/partition", "target_idx": 3}
{"id": "field_constraint_sex_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for VARIANTSOFINT (custom/variantsofint).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow VARIANTSOFINT": null, "Use nf-core subworkflow variantsofint": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 2}
{"id": "noul_mix_operator_async_emission_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "field_constraint_fastq_1_0_10", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_4", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_ltrharvest_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts LTR retrotransposons using the parallel version of GenomeTools gt-ltrharvest\nutility included in the EDTA toolchain (tools: LTR_HARVEST_parallel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ltrharvest": "Predicts LTR retrotransposons using the parallel version of GenomeTools gt-ltrharvest\nutility included in the ", "hhsuite_reformat": "Reformat a Multiple Sequence Alignment (MSA) file", "alignoth": "Creating alignment plots from bam files", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "custom_sratoolsncbisettings": "Test for the presence of suitable NCBI settings or create them on the fly."}}, "target": "ltrharvest", "target_idx": 0}
{"id": "schema_std_hadge_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/hadge. Description: Comprehensive pipeline for donor demultiplexing in single cell.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/hadge.", "criteria": {"sample,fastq_1,fastq_2,bam,seq_type": null, "id,path": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,bam,vcf,rna_matrix,hto_matrix": null}}, "target": "sample,bam,vcf,rna_matrix,hto_matrix", "target_idx": 3}
{"id": "mod_plink_vcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analyses variant calling files using plink (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/createsequencedictionary": null, "plink/bcf": null, "plink/vcf": null, "custom/addmostseverepli": null, "plink/bmerge": null}}, "target": "plink/vcf", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_2_5", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,bed": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_scimap_spatiallda_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SpatialLDA uses an LDA based approach for the identification of cellular neighborhoods, using cell type identities. (tools: scimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools/merge": "Merge multiple pairs/pairsam files", "scimap/spatiallda": "SpatialLDA uses an LDA based approach for the identification of cellular neighborhoods, using cell type identi", "utils_annotation_cache": "Check the path to the annotation cache depending if local or on the cloud, or using annotation-cache itself", "htseq/count": "count how many reads map to each feature", "deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell"}}, "target": "scimap/spatiallda", "target_idx": 1}
{"id": "resource_agat_convertspgxf2gxf_0", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGXF2GXF", "tool": "agat/convertspgxf2gxf", "description": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGXF2GXF (Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_whatshap_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute statistics from phased variant file using Whatshap (tools: whatshap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whatshap/stats": "Compute statistics from phased variant file using Whatshap", "atlas/call": "generate VCF file from a BAM file using various calling methods", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "tximeta/tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages", "minimap2/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences"}}, "target": "whatshap/stats", "target_idx": 0}
{"id": "schema_std_createtaxdb_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createtaxdb", "assay": "createtaxdb pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/createtaxdb (Parallelised and automated construction of metagenomic class)?", "criteria": {"sample,fastq_1,strandedness": null, "sample,seed": null, "id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "id,taxid,fasta_dna,fasta_aa", "target_idx": 2}
{"id": "field_constraint_fastq_1_3_2", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "mod_eggnogmapper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast genome-wide functional annotation through orthology assignment. (tools: eggnogmapper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_makepaddedseqdb": "Create an MMseqs padded database from an existing MMseqs database", "eggnogmapper": "Fast genome-wide functional annotation through orthology assignment.", "fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "eggnogmapper", "target_idx": 1}
{"id": "mod_fastq_qc_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate statistics for short read sequencing data using multiple tools (tools: fastq_qc_stats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_qc_stats": "Generate statistics for short read sequencing data using multiple tools", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "isoseq3/tag": "Extract UMI and cell barcodes", "samtools/view": "filter/convert SAM/BAM/CRAM file"}}, "target": "fastq_qc_stats", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_2_6", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_agat_spstatistics_1", "category": "resource_profiling", "state": {"process": "AGAT_SPSTATISTICS", "tool": "agat/spstatistics", "description": "Provides different type of statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPSTATISTICS (Provides different type of statistics in text format from a GFF/GTF annotation f) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_modular_subworkflow_composition_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_amulety_antiberty_3", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTY", "tool": "amulety/antiberty", "description": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTY (A module to create antiberty embeddings of antibody (BCR) amino acid sequences u) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_channel_operator_map_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_mm2plus_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: mm2plus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_cluster": null, "proseg_proseg": null, "narfmap_align": null, "mm2plus_align": null, "ampcombi2_complete": null}}, "target": "mm2plus_align", "target_idx": 3}
{"id": "mod_gridss_gridss_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss_extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "baysor_preview": "Extract neighborhood composition vectors (NVCs) from a dataset.", "gridss_gridss": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "meningotype": "Serotyping of Neisseria meningitidis assemblies", "gridss_call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment"}}, "target": "gridss_gridss", "target_idx": 2}
{"id": "pipe_all101_cutandrun_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis.. Topics: cutandrun, cutandrun-seq, cutandtag, cutandtag-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnasplice": null, "stableexpression": null, "pacvar": null, "pathogensurveillance": null, "airrflow": null, "atacseq": null, "cutandrun": null, "chipseq": null}}, "target": "cutandrun", "target_idx": 6}
{"id": "mod_oatk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An nf-core module for the OATK (tools: oatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"oatk": "An nf-core module for the OATK", "octopusv/plotcircos": "Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file.", "mitohifi/mitohifi": "A python workflow that assembles mitogenomes from Pacbio HiFi reads", "quast": "Quality Assessment Tool for Genome Assemblies", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database"}}, "target": "oatk", "target_idx": 0}
{"id": "resource_bedtools_coverage_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COVERAGE", "tool": "bedtools/coverage", "description": "computes both the depth and breadth of coverage of features in file B on the features in file A"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COVERAGE (computes both the depth and breadth of coverage of features in file B on the fea) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_12", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "subworkflow_pkg_bam_markduplicates_picard_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_PICARD", "modules": ["picard/markduplicates", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_PICARD (picard/markduplicates, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_markduplicates_picard": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_MARKDUPLICATES_PICARD": null}}, "target": "Use nf-core subworkflow bam_markduplicates_picard", "target_idx": 0}
{"id": "pipe_all101_rnaseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.. Topics: rna, rna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot"}}, "target": "rnaseq", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_create_umi_consensus_fgbio_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_CREATE_UMI_CONSENSUS_FGBIO", "modules": ["bwa/index", "bwa/mem", "bwamem2/mem", "bwamem2/index", "fgbio/fastqtobam", "fgbio/groupreadsbyumi", "fgbio/callmolecularconsensusreads", "fgbio/callduplexconsensusreads", "fgbio/filterconsensusreads", "samblaster", "samtools/bam2fq", "samtools/sort", "samtools/index", "samtools/fastq", "fgbio/zipperbams"], "description": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads"}, "question": {"type": "choice", "instructions": "How should FASTQ_CREATE_UMI_CONSENSUS_FGBIO (bwa/index, bwa/mem, bwamem2/mem, bwamem2/index, fgbio/fastqtobam, fgbio/groupreadsbyumi, fgbio/callmolecularconsensusreads, fgbio/callduplexconsensusreads, fgbio/filterconsensusreads, samblaster, samtools/bam2fq, samtools/sort, samtools/index, samtools/fastq, fgbio/zipperbams) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_CREATE_UMI_CONSENSUS_FGBIO": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_create_umi_consensus_fgbio": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_create_umi_consensus_fgbio", "target_idx": 2}
{"id": "intent_ask_question_8", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "ask_question", "target_idx": 2}
{"id": "noul_single_hyphen_cli_params_error_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_mindagap_mindagap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes a single panorama image and fills the empty grid lines with neighbour-weighted values. (tools: mindagap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op", "mapad/index": "Create mapAD index for reference genome", "bftools/showinf": "Extract OME xml data from OME-tif", "mindagap/mindagap": "Takes a single panorama image and fills the empty grid lines with neighbour-weighted values.", "bamtools/split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "mindagap/mindagap", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_shortreads_preprocess_qc_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SHORTREADS_PREPROCESS_QC", "modules": ["fastq_qc_stats", "fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp", "fastq_preprocess_seqkit", "fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup", "umitools/extract", "fastq_removeadapters_merge", "trimmomatic", "cutadapt", "trimgalore", "bbmap/bbduk", "leehom", "fastp", "adapterremoval", "cat/fastq", "fastq_complexity_filter", "prinseqplusplus", "bbmap/clumpify", "fastq_decontaminate_deacon_hostile", "fastq_index_filter_deacon", "fastq_fetch_clean_hostile", "hostile/fetch", "hostile/clean", "bowtie2/build", "deacon/filter", "deacon/index"], "description": "Quality check and preprocessing subworkflow of Illumina short reads"}, "question": {"type": "choice", "instructions": "How should FASTQ_SHORTREADS_PREPROCESS_QC (fastq_qc_stats, fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp, fastq_preprocess_seqkit, fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup, umitools/extract, fastq_removeadapters_merge, trimmomatic, cutadapt, trimgalore, bbmap/bbduk, leehom, fastp, adapterremoval, cat/fastq, fastq_complexity_filter, prinseqplusplus, bbmap/clumpify, fastq_decontaminate_deacon_hostile, fastq_index_filter_deacon, fastq_fetch_clean_hostile, hostile/fetch, hostile/clean, bowtie2/build, deacon/filter, deacon/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_shortreads_preprocess_qc": null, "Leave them out": null, "Local subworkflow FASTQ_SHORTREADS_PREPROCESS_QC": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_shortreads_preprocess_qc", "target_idx": 0}
{"id": "mod_baysor_preview_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract neighborhood composition vectors (NVCs) from a dataset. (tools: baysor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"circexplorer2_parse": "CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate.", "picard_sortvcf": "Sorts vcf files", "quilt_quilt2": "QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased re", "custom_sratoolsncbisettings": "Test for the presence of suitable NCBI settings or create them on the fly.", "baysor_preview": "Extract neighborhood composition vectors (NVCs) from a dataset."}}, "target": "baysor_preview", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_2", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_ont_metagenome_single_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Long-read Oxford Nanopore environmental metagenomic sequencing", "data_format": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "mod_sparsesignatures_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mutational signature deconvolution of cancer cells (tools: sparsesignatures)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_mutectcaller": null, "sparsesignatures": null, "haplogrep2_classify": null, "sigprofiler": null, "numorph_intensity": null}}, "target": "sparsesignatures", "target_idx": 1}
{"id": "noul_modular_subworkflow_composition_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_popscle_demuxlet_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing and external genotyping data for each sample is available. (tools: popscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gmmdemux": null, "skani/search": null, "popscle/freemuxlet": null, "popscle/demuxlet": null, "bam2fastx/bam2fastq": null}}, "target": "popscle/demuxlet", "target_idx": 3}
{"id": "mod_gatk4_fastqtosam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts FastQ file to SAM/BAM format (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ragtag_patch": "Homology-based assembly patching: Make continuous joins and fill gaps in 'target.fa' using sequences from 'que", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "gatk4_fastqtosam": "Converts FastQ file to SAM/BAM format", "bedtools_shuffle": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a gen", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "gatk4_fastqtosam", "target_idx": 2}
{"id": "mod_bamtools_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files. (tools: bamtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools/stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bcftools/plotvcfstats": "Plots the output of bcftools stats", "gt/stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "s4pred/runmodel": "Prediction of a protein's secondary structure from its amino acid sequence", "shigatyper": "Determine Shigella serotype from Illumina or Oxford Nanopore reads"}}, "target": "bamtools/stats", "target_idx": 0}
{"id": "resource_busco_download_0", "category": "resource_profiling", "state": {"process": "BUSCO_DOWNLOAD", "tool": "busco/download", "description": "Download database for BUSCO"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_DOWNLOAD (Download database for BUSCO) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_1_4", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,cram": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "subworkflow_pkg_abundance_differential_filter_2", "category": "subworkflow_packaging", "state": {"subworkflow": "ABUNDANCE_DIFFERENTIAL_FILTER", "modules": ["limma/differential", "deseq2/differential", "propr/propd", "custom/filterdifferentialtable", "variancepartition/dream"], "description": "A subworkflow for filtering differential abundance results"}, "question": {"type": "choice", "instructions": "How should ABUNDANCE_DIFFERENTIAL_FILTER (limma/differential, deseq2/differential, propr/propd, custom/filterdifferentialtable, variancepartition/dream) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow abundance_differential_filter": null, "Local subworkflow ABUNDANCE_DIFFERENTIAL_FILTER": null}}, "target": "Use nf-core subworkflow abundance_differential_filter", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_37", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_6_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns are standard for ChIP-seq with IP and input control design input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "mod_svtk_rdtest2vcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert an RdTest-formatted bed to the standard VCF format. (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"emboss/cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "svtk/countsvtypes": "Count the instances of each SVTYPE observed in each sample in a VCF.", "svtk/standardize": "Convert SV calls to a standardized format.", "regenie/step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions", "svtk/rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format."}}, "target": "svtk/rdtest2vcf", "target_idx": 4}
{"id": "mod_dshbio_filtergff3_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter features in gzipped GFF3 format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gnu/sort": "Writes a sorted concatenation of file/s", "vcftools": "A set of tools written in Perl and C++ for working with VCF files", "gt/gff3validator": "GenomeTools gt-gff3validator utility to strictly validate a GFF3 file", "dshbio/filtergff3": "Filter features in gzipped GFF3 format", "gt/stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files"}}, "target": "dshbio/filtergff3", "target_idx": 3}
{"id": "mod_gapseq_find_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict metabolic pathways from genomic data using gapseq (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clame": "binning of metagenomic sequences", "gapseq/find": "Predict metabolic pathways from genomic data using gapseq", "custom/pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "gapseq/find", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_impute_glimpse_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_GLIMPSE", "modules": ["glimpse/chunk", "glimpse/phase", "glimpse/ligate", "bcftools/index"], "description": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_GLIMPSE (glimpse/chunk, glimpse/phase, glimpse/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Local subworkflow VCF_IMPUTE_GLIMPSE": null, "Use nf-core subworkflow vcf_impute_glimpse": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_impute_glimpse", "target_idx": 1}
{"id": "mod_nextclade_datasetget_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation) (tools: nextclade)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/annotate": null, "nextclade/datasetget": null, "ferrohgvs/parse": null, "mitorsaw/haplotype": null, "nextclade/run": null}}, "target": "nextclade/datasetget", "target_idx": 1}
{"id": "resource_basicpy_0", "category": "resource_profiling", "state": {"process": "BASICPY", "tool": "basicpy", "description": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is developed based on the Matlab version of BaSiC tool with major improvements in the algorithm."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASICPY (BaSiCPy is a python package for background and shading correction of optical mic) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_msisensor_msi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate microsattelite instability (MSI) using paired tumor-normal sequencing data (tools: msisensor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro_msisomatic": null, "agrvate": null, "msisensor_msi": null, "msisensor_scan": null, "folddisco_index": null}}, "target": "msisensor_msi", "target_idx": 2}
{"id": "resource_bcftools_split_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SPLIT", "tool": "bcftools/split", "description": "Split a vcf file into files per chromosome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SPLIT (Split a vcf file into files per chromosome) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_6_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Oxford Nanopore environmental metagenomic sequencing input samplesheet?", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "core_tool_fastqc_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Quality control metric evaluation including per-base sequence quality scores, GC content distributions, and k-mer overrepresentation for raw FASTQ data.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"falco": "FastQC C++ drop-in", "qualimap": "BAM QC tool", "nanoplot": "Nanopore plotting", "fastqc": "Quality control tool for high throughput sequence data", "multiqc": "Aggregate report tool"}}, "target": "fastqc", "target_idx": 3}
{"id": "schema_std_hadge_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hadge", "assay": "hadge pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/hadge (Comprehensive pipeline for donor demultiplexing in single ce)?", "criteria": {"sample,bam,vcf,rna_matrix,hto_matrix": null, "id,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam,vcf,rna_matrix,hto_matrix", "target_idx": 0}
{"id": "subworkflow_pkg_bam_subsampledepth_samtools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SUBSAMPLEDEPTH_SAMTOOLS", "modules": ["samtools/coverage", "samtools/view"], "description": "Subsample a BAM/CRAM/SAM file using samtools to a given mean depth."}, "question": {"type": "choice", "instructions": "How should BAM_SUBSAMPLEDEPTH_SAMTOOLS (samtools/coverage, samtools/view) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_SUBSAMPLEDEPTH_SAMTOOLS": null, "Use nf-core subworkflow bam_subsampledepth_samtools": null}}, "target": "Use nf-core subworkflow bam_subsampledepth_samtools", "target_idx": 3}
{"id": "resource_anndata_barcodes_1", "category": "resource_profiling", "state": {"process": "ANNDATA_BARCODES", "tool": "anndata/barcodes", "description": "Module to subset AnnData object to cells with matching barcodes from the csv file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_BARCODES (Module to subset AnnData object to cells with matching barcodes from the csv fil) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_33", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_47", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "schema_std_nanostring_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanostring", "description": "An analysis pipeline for Nanostring nCounter expression data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/nanostring?", "criteria": {"sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,fastq_1,strandedness": null}}, "target": "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT", "target_idx": 1}
{"id": "schema_std_bamtofastq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bamtofastq", "description": "Converts bam or cram files to fastq format and does quality control.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/bamtofastq?", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "sample_id,mapped,index,file_type": null}}, "target": "sample_id,mapped,index,file_type", "target_idx": 3}
{"id": "resource_binette_1", "category": "resource_profiling", "state": {"process": "BINETTE", "tool": "binette", "description": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BINETTE (A fast and accurate binning refinement tool to construct high quality MAGs from ) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_2_3", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_flash_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform merging of mate paired-end sequencing reads (tools: flash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam/bamsormadup": null, "sourmash/taxannotate": null, "flash": null, "bedtools/sort": null, "glimpse2/ligate": null}}, "target": "flash", "target_idx": 2}
{"id": "mod_fusioninspector_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validation of Fusion Transcript Predictions (tools: fusioninspector)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa_psiperisoform": null, "angsd_docounts": null, "fusioninspector": null, "arriba_arriba": null, "starfusion_detect": null}}, "target": "fusioninspector", "target_idx": 2}
{"id": "mod_pangolin_updatedata_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Phylogenetic Assignment of Named Global Outbreak LINeages (tools: pangolin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigslice_downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "ska_distance": "Calculate pairwise distances and basic clustering from SKA sketches", "gatk4_printsvevidence": "WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end an", "pangolin_updatedata": "Phylogenetic Assignment of Named Global Outbreak LINeages", "pangolin_run": "Phylogenetic Assignment of Named Global Outbreak LINeages"}}, "target": "pangolin_updatedata", "target_idx": 3}
{"id": "mod_gprofiler2_gost_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: runs a functional enrichment analysis with gprofiler2 (tools: gprofiler2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq_requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "gprofiler2_gost": "runs a functional enrichment analysis with gprofiler2", "gsea_gsea": "run the Broad Gene Set Enrichment tool in GSEA mode", "homer_findpeaks": "Find peaks with HOMER suite", "shapeit5_phaserare": "Tool to phase rare variants onto a scaffold of common variants (output of phase_common / ligate).\nRequire feat"}}, "target": "gprofiler2_gost", "target_idx": 1}
{"id": "mod_vcontact3_prepareddatabases_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare and format databases for vCONTACT3 viral taxonomic analysis (tools: vcontact3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wisecondorx_gender": null, "cnaqc": null, "vcontact3_prepareddatabases": null, "genomad_download": null, "checkv_downloaddatabase": null}}, "target": "vcontact3_prepareddatabases", "target_idx": 2}
{"id": "mod_mageck_test_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mageck test performs a robust ranking aggregation (RRA) to identify positively or negatively selected genes in functional genomics screens. (tools: mageck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hisat3n_align": null, "duphold": null, "biobambam_bamsormadup": null, "mageck_test": null, "metaeuk_easypredict": null}}, "target": "mageck_test", "target_idx": 3}
{"id": "subworkflow_pkg_tiff_segmentation_vpt_1", "category": "subworkflow_packaging", "state": {"subworkflow": "TIFF_SEGMENTATION_VPT", "modules": ["vizgenpostprocessing/preparesegmentation", "vizgenpostprocessing/runsegmentationontile", "vizgenpostprocessing/compiletilesegmentation"], "description": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool"}, "question": {"type": "choice", "instructions": "How should TIFF_SEGMENTATION_VPT (vizgenpostprocessing/preparesegmentation, vizgenpostprocessing/runsegmentationontile, vizgenpostprocessing/compiletilesegmentation) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow tiff_segmentation_vpt": null, "Local subworkflow TIFF_SEGMENTATION_VPT": null}}, "target": "Use nf-core subworkflow tiff_segmentation_vpt", "target_idx": 2}
{"id": "pipe_all101_rnadnavar_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline for RNA and DNA integrated analysis for somatic mutation detection. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]"}}, "target": "rnadnavar", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_preprocess_seqkit_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_PREPROCESS_SEQKIT", "modules": ["fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup"], "description": "Subworkflow that preprocesses FASTQ files"}, "question": {"type": "choice", "instructions": "How should FASTQ_PREPROCESS_SEQKIT (fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_PREPROCESS_SEQKIT": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_preprocess_seqkit": null}}, "target": "Use nf-core subworkflow fastq_preprocess_seqkit", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Long-read Oxford Nanopore environmental metagenomic sequencing. Input files: High molecular weight environmental metagenomic long reads per sampling site.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Oxford Nanopore environmental metagenomic sequencing with entry step NANOPLOT.", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "pipe_core10_atacseq_2_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? ATAC-seq peak calling with MACS2 and Genrich, QC analysis, and nucleosome-free region identification.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"viralrecon": null, "rnaseq": null, "ampliseq": null, "sarek": null, "chipseq": null, "eager": null, "taxprofiler": null, "mag": null, "scrnaseq": null, "atacseq": null}}, "target": "atacseq", "target_idx": 9}
{"id": "mod_merquryfk_katgc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A reimplemenation of KatGC to work with FastK databases (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani_sketch": "Storing skani sketches/indices on disk.", "merquryfk_katgc": "A reimplemenation of KatGC to work with FastK databases", "nucmer": "NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences.", "merquryfk_hapmaker": "Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables", "bedtools_nuc": "Profiles the nucleotide content of intervals in a fasta file."}}, "target": "merquryfk_katgc", "target_idx": 1}
{"id": "resource_anndata_barcodes_4", "category": "resource_profiling", "state": {"process": "ANNDATA_BARCODES", "tool": "anndata/barcodes", "description": "Module to subset AnnData object to cells with matching barcodes from the csv file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_BARCODES (Module to subset AnnData object to cells with matching barcodes from the csv fil) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_retry_errorstrategy_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_scrna_10x_v3_1_4", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,matrix,barcodes,features": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 3}
{"id": "resource_antismash_antismashlite_4", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITE", "tool": "antismash/antismashlite", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITE (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_genomeqc_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Compare the quality of multiple genomes, along with their annotations.. Topics: genome-assembly-evaluation, genomics, phylogenetic-trees, quality-control. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinfold": null, "viralintegration": null, "drop": null, "seqinspector": null, "pacvar": null, "viralmetagenome": null, "mcmicro": null, "circdna": null, "mnaseseq": null, "genomeqc": null}}, "target": "genomeqc", "target_idx": 9}
{"id": "resource_bcftools_pluginscatter_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSCATTER", "tool": "bcftools/pluginscatter", "description": "Split VCF by chunks or regions, creating multiple VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSCATTER (Split VCF by chunks or regions, creating multiple VCFs.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_atlas_pmd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate the post-mortem damage patterns of DNA (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"damageprofiler": null, "plink2_score": null, "bam_sort_stats_samtools": null, "endorspy": null, "atlas_pmd": null}}, "target": "atlas_pmd", "target_idx": 4}
{"id": "local_subworkflow_nextclade_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for NEXTCLADE (nextclade/run).", "criteria": {"Leave them out": null, "Local subworkflow NEXTCLADE": null, "Use nf-core subworkflow nextclade": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_49", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "16S rRNA / ITS microbiome amplicon profiling", "data_format": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 16S rRNA / ITS microbiome amplicon profiling with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,otu_table": null, "sample,primer_fwd,primer_rev": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_anota2seq_anota2seqrun_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq (tools: anota2seq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "bismark_report": "Collects bismark alignment reports", "gedi_indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "icountmini_sigxls": "Runs iCount sigxls on a BED file of crosslinks", "plastid_psite": "Estimate position of ribosomal P-site within ribosome profiling read alignments as a function of read length"}}, "target": "anota2seq_anota2seqrun", "target_idx": 0}
{"id": "mod_allelecounter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a count of coverage of alleles (tools: allelecounter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gamma_gamma": "Gene Allele Mutation Microbial Assessment", "catpack_contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).", "allelecounter": "Generates a count of coverage of alleles", "cellranger_count": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expressi", "mirtop_counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns "}}, "target": "allelecounter", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_3", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_20", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_2_0", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null, "sample,unite_fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_varscan_processsomatic_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, and copy number variations in both somatic and germline samples. It is particularly useful for analyzing tumor/normal sample pairs. This subtool divides variants based on status (germline, somatic, loss of heterozygosity) and confidence level (high-confidence or not) and outputs them in separate VCF files. (tools: varscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/createreadcountpanelofnormals": "Creates a panel of normals (PoN) for read-count denoising given the read counts for samples in the panel.", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "varscan/processsomatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "bcftools/consensus": "Compresses VCF files", "clustalo/guidetree": "Renders a guidetree in clustalo"}}, "target": "varscan/processsomatic", "target_idx": 2}
{"id": "samplesheet_arch_ont_metagenome_single_2_0", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "NANOPLOT", "library_inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "mod_bam_impute_quilt2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Impute low-coverage BAM or CRAM inputs with QUILT2 and ligate chunked outputs per chromosome.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: bam_impute_quilt2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_splitmerge": "split single end read groups by length and merge paired end reads", "bam_impute_quilt2": "Impute low-coverage BAM or CRAM inputs with QUILT2 and ligate chunked outputs per chromosome.\n\"regionout\", \"re", "samtools_samples": "Write sample names and path to reference genome of an alignment to a text file.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "mtmalign_align": "Aligns protein structures using mTM-align"}}, "target": "bam_impute_quilt2", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_0_39", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_ampcombi2_cluster_3", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_CLUSTER", "tool": "ampcombi2/cluster", "description": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete using MMseqs2 cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_CLUSTER (A submodule that clusters the merged AMP hits generated from ampcombi2/parsetabl) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "intent_prepare_data_9", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "prepare_data": null, "ask_question": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 1}
{"id": "mod_mmseqs_makepaddedseqdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create an MMseqs padded database from an existing MMseqs database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/createdb": "Create an MMseqs database from an existing FASTA/Q file", "picard/positionbaseddownsamplesam": "Samples a SAM/BAM/CRAM file using flowcell position information for the best approximation of having sequenced", "deeparg/predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "mmseqs/makepaddedseqdb": "Create an MMseqs padded database from an existing MMseqs database", "mmseqs/createindex": "Creates sequence index for mmseqs database"}}, "target": "mmseqs/makepaddedseqdb", "target_idx": 3}
{"id": "noul_dynamic_resource_allocation_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_narfmap_hashtable_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create DRAGEN hashtable for reference genome (tools: narfmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"narfmap/hashtable": "Create DRAGEN hashtable for reference genome", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "sratools/fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA).", "bowtie/build": "Create bowtie index for reference genome", "hmmer/hmmemit": "emit sequences from a profile HMM"}}, "target": "narfmap/hashtable", "target_idx": 0}
{"id": "resource_agat_spflagshortintrons_5", "category": "resource_profiling", "state": {"process": "AGAT_SPFLAGSHORTINTRONS", "tool": "agat/spflagshortintrons", "description": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting the data to EBI.\n(Typical EBI error message: ********ERROR: Intron usually expected to be at least 10 nt long. Please check the accuracy)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFLAGSHORTINTRONS (The script flags the short introns with the attribute <pseudo>. Is is usefull to) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_channel_filter_operator_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_amulety_esm2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": null, "custom_pcaclustering": null, "amulety_esm2": null, "openms_fileconverter": null, "amulety_embed": null}}, "target": "amulety_esm2", "target_idx": 2}
{"id": "pipe_all101_hgtseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for bwa-mem. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]"}}, "target": "hgtseq", "target_idx": 5}
{"id": "samplesheet_arch_proteomics_dia_0_4", "category": "samplesheet_schema", "state": {"technology": "Mass Spectrometry", "workflow_entry": "INPUT_CHECK", "library_inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,fasta": null, "sample,raw_file,condition": null, "sample,mzml": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "resource_backsub_4", "category": "resource_profiling", "state": {"process": "BACKSUB", "tool": "backsub", "description": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACKSUB (Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_12", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_helitronscanner_scan_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes (tools: helitronscanner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "helitronscanner_scan": "HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes", "custom_tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "dragmap_hashtable": "Create DRAGEN hashtable for reference genome"}}, "target": "helitronscanner_scan", "target_idx": 1}
{"id": "mod_bam_docounts_contamination_angsd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate contamination of the X-chromosome with ANGSD (tools: bam_docounts_contamination_angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_docounts_contamination_angsd": null, "angsd/docounts": null, "angsd/soapsnpcalibration": null, "openms/idmassaccuracy": null, "svdss/index": null}}, "target": "bam_docounts_contamination_angsd", "target_idx": 0}
{"id": "mod_bedtools_map_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Allows one to screen for overlaps between two sets of genomic features. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "bedtools/map": "Allows one to screen for overlaps between two sets of genomic features.", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "cnvpytor/importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file.", "ngmerge": "Merging paired-end reads and removing sequencing adapters."}}, "target": "bedtools/map", "target_idx": 1}
{"id": "samplesheet_arch_pediatric_trio_somatic_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "data_format": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_cnvkit_genemetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number variant detection from high-throughput sequencing data (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja_boot": "Bootstrap sample demixing by resampling each site based on a multinomial distribution of read depth across all", "last_train": "Find suitable score parameters for sequence alignment", "cnvkit_export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "cnvkit_genemetrics": "Copy number variant detection from high-throughput sequencing data", "cnvkit_fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera"}}, "target": "cnvkit_genemetrics", "target_idx": 3}
{"id": "noul_process_conditional_execution_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_fastq_2_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "intent_prepare_data_18", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "prepare_data", "target_idx": 3}
{"id": "mod_deeptools_plotprofile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: plots values produced by deeptools_computematrix as a profile plot (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/vcf2bed": null, "deeptools/plotfingerprint": null, "last/train": null, "deeptools/plotprofile": null, "deeptools/multibigwigsummary": null}}, "target": "deeptools/plotprofile", "target_idx": 3}
{"id": "samplesheet_arch_ont_direct_rna_se_7_2", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_deeptools_alignmentsieve_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool filters alignments in a BAM/CRAM file according the the specified parameters. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qcatch": "Cell-filtering and QC reporting tool for alevin-fry quantification results", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "biscuit_bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "deeptools_alignmentsieve": "This tool filters alignments in a BAM/CRAM file according the the specified parameters.", "plotsr": "Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes."}}, "target": "deeptools_alignmentsieve", "target_idx": 3}
{"id": "noul_process_conditional_execution_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_glimpse2_chunk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Defines chunks where to run imputation (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse2/chunk": "Defines chunks where to run imputation", "bam_vcf_impute_glimpse2": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow\ntakes VCF files, phased ref", "amulety/embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "gatk4/composestrtablefile": "This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Drags", "bamtools/split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "glimpse2/chunk", "target_idx": 0}
{"id": "mod_untarfiles_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract files. (tools: untar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"untarfiles": "Extract files.", "stringtie_merge": "Merges the annotation gtf file and the stringtie output gtf files", "untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "tar": "Compress directories into tarballs with various compression options"}}, "target": "untarfiles", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cutandrun) for CUT&RUN / CUT&TAG chromatin profiling with IgG control. Input files: Paired-end low-input fragment FASTQs with target antibody and IgG negative control.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CUT&RUN / CUT&TAG chromatin profiling with IgG control with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_25", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_xeniumranger_rename_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all the Xenium Onboard Analysis output files that contain this information. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scimap/mcmicro": "SCIMAP is a suite of tools that enables spatial single-cell analyses", "xeniumranger/rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "shigapass": "ShigaPass is an in silico tool used to predict Shigella serotypes and to differentiate between Shigella, EIEC ", "svtk/rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format."}}, "target": "xeniumranger/rename", "target_idx": 1}
{"id": "subworkflow_pkg_bam_split_by_region_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SPLIT_BY_REGION", "modules": ["samtools/view", "samtools/index"], "description": "Split the reads in the input bam by specified genomic region."}, "question": {"type": "choice", "instructions": "How should BAM_SPLIT_BY_REGION (samtools/view, samtools/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_split_by_region": null, "Local subworkflow BAM_SPLIT_BY_REGION": null}}, "target": "Use nf-core subworkflow bam_split_by_region", "target_idx": 2}
{"id": "schema_std_airrflow_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/airrflow", "description": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/airrflow?", "criteria": {"id,fasta": null, "sample_id,name,description,path,path_2": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "sample_id,subject_id,species,pcr_target_locus,tissue", "target_idx": 3}
{"id": "mod_ichorcna_createpon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, particularly for use in cell-free DNA. This module generates a panel of normals (tools: ichorcna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ichorcna_createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "fibertoolsrs_extract": "Extract Fiber-seq information (such as m6A, CpG, nucleosomes, and MSPs) from BAM file into BED file", "cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions.", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples).", "sentieon_bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM"}}, "target": "ichorcna_createpon", "target_idx": 0}
{"id": "resource_bbmap_bbsplit_5", "category": "resource_profiling", "state": {"process": "BBMAP_BBSPLIT", "tool": "bbmap/bbsplit", "description": "Split sequencing reads by mapping them to multiple references simultaneously"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBSPLIT (Split sequencing reads by mapping them to multiple references simultaneously) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_raredisease_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/raredisease. Description: Call and score variants from WGS/WES of rare disease patients..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/raredisease.", "criteria": {"sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,fastq_1,fastq_2,condition,reference": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 2}
{"id": "mod_cellranger_vdj_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Immune Profiling. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": null, "cellranger/vdj": null, "ampcombi2/parsetables": null, "rastair/call": null, "bedtools/complement": null}}, "target": "cellranger/vdj", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_34", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_25", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_atacseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: ATAC-seq peak-calling and QC analysis pipeline. Topics: atac-seq, chromatin-accessibiity. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]"}}, "target": "atacseq", "target_idx": 1}
{"id": "resource_beagle5_beagle_2", "category": "resource_profiling", "state": {"process": "BEAGLE5_BEAGLE", "tool": "beagle5/beagle", "description": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEAGLE5_BEAGLE (Beagle v5.5 is a software package for phasing genotypes and for imputing ungenot) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Multi-lane Illumina sequencing run of clinical samples. Input files: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-lane Illumina sequencing run of clinical samples with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null, "lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bcftools_isec_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ISEC", "tool": "bcftools/isec", "description": "Apply set operations to VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ISEC (Apply set operations to VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_rseqc_splitbam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split BAM file based on gene list in BED format (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "cache_download_ensemblvep_snpeff": "downlad annotation cache for snpeff and ensemblvep", "ascat": "copy number profiles of tumour cells.", "rseqc_splitbam": "Split BAM file based on gene list in BED format", "krakentools_combinekreports": "Takes multiple kraken-style reports and combines them into a single report file"}}, "target": "rseqc_splitbam", "target_idx": 3}
{"id": "resource_bedtools_makewindows_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAKEWINDOWS", "tool": "bedtools/makewindows", "description": "Makes adjacent or sliding windows across a genome or BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAKEWINDOWS (Makes adjacent or sliding windows across a genome or BED file.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_strdrop_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build reference json from sequencing coverage in STR VCFs (tools: strdrop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "expansionhunterdenovo_profile": "Compute genome-wide STR profile", "gangstr": "GangSTR is a tool for genome-wide profiling tandem repeats from short reads.", "deeparg_predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "strdrop_build": "Build reference json from sequencing coverage in STR VCFs"}}, "target": "strdrop_build", "target_idx": 4}
{"id": "schema_std_atacseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/atacseq. Description: ATAC-seq peak-calling and QC analysis pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/atacseq.", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "id,raw_file": null, "sample,fastq_1,fastq_2,replicate,control": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,replicate,control", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral genome sequencing on Oxford Nanopore MinION / GridION)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral genome sequencing on Oxford Nanopore MinION / GridION.", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_pypgx_createinputvcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call SNVs/indels from BAM files for all target genes. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx_computecontrolstatistics": "Compute summary statistics for control gene from BAM files.", "bigslice_bigslice": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenB", "snippy_core": "Core-SNP alignment from Snippy outputs", "pypgx_createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va"}}, "target": "pypgx_createinputvcf", "target_idx": 3}
{"id": "mod_pcne_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimates plasmid copy number from assembled genome (tools: pcne)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pcne": "Estimates plasmid copy number from assembled genome", "seqkit_concat": "Concatenating multiple uncompressed sequence files together", "genomad_download": "Download geNomad databases and related files", "genomad_endtoend": "Identify mobile genetic elements present in genomic assemblies", "presto_filterseq": "Filter reads by quality score."}}, "target": "pcne", "target_idx": 0}
{"id": "resource_bakta_baktadbdownload_1", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTADBDOWNLOAD", "tool": "bakta/baktadbdownload", "description": "Downloads BAKTA database from Zenodo"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTADBDOWNLOAD (Downloads BAKTA database from Zenodo) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_exit_code_137_cause_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bismark_report_0", "category": "resource_profiling", "state": {"process": "BISMARK_REPORT", "tool": "bismark/report", "description": "Collects bismark alignment reports"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_REPORT (Collects bismark alignment reports) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_42", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_5_4", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/chipseq, determine the input samplesheet column structure for: ChIP-seq with IP and input control design.", "criteria": {"sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "field_constraint_bam_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_2_0", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "local_subworkflow_daisribosome_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for DAISRIBOSOME (dais).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow DAISRIBOSOME": null, "Use nf-core subworkflow daisribosome": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 2}
{"id": "noul_modular_subworkflow_composition_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2", "modules": ["kraken2/add", "kraken2/build"], "description": "KRAKEN2 build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2 (kraken2/add, kraken2/build) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fasta_build_add_kraken2": null, "Local subworkflow FASTA_BUILD_ADD_KRAKEN2": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_2_46", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_ribomsqc_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for ribomsqc. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"callingcards": "A pipeline for processing calling cards data", "metapep": "From metagenomes to epitopes and beyond", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders"}}, "target": "ribomsqc", "target_idx": 6}
{"id": "mod_sourmash_taxannotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genometester4/glistmaker": "Create and count k-mer lists from nucelotide sequences.", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "finaletoolkit/delfi": "Calculate the DELFI scores (Cristiano et al., 2019) from a BAM file.", "dupradar": "Assessment of duplication rates in RNA-Seq datasets"}}, "target": "sourmash/taxannotate", "target_idx": 2}
{"id": "local_subworkflow_irma_2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for IRMA (irma).", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow IRMA": null, "Use nf-core subworkflow irma": null}}, "target": "Local subworkflow IRMA", "target_idx": 2}
{"id": "field_constraint_status_0_6", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "mod_bamtools_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files. (tools: bamtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bamtools_stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "svdb_query": "Query a structural variant database, using a vcf file as query", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "samtools_convert": "convert and then index CRAM -> BAM or BAM -> CRAM file"}}, "target": "bamtools_convert", "target_idx": 3}
{"id": "noul_channel_filter_operator_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "core_tool_fastp_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? All-in-one FASTQ preprocessor performing automated adapter trimming, polyG tail clipping, quality filtering, and base correction.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"cutadapt": "Removes adapter sequences", "fastqc": "Quality control for FASTQ", "multiqc": "Report aggregator", "trimmomatic": "Read trimming tool", "fastp": "An ultra-fast all-in-one FASTQ preprocessor (QC, adapter trimming, filtering, splitting)"}}, "target": "fastp", "target_idx": 4}
{"id": "mod_deeptmhmm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A Deep Learning Model for Transmembrane Topology Prediction and Classification (tools: deeptmhmm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_readwriter": "Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality S", "midas_run": "A tool to estimate bacterial species abundance", "deeptmhmm": "A Deep Learning Model for Transmembrane Topology Prediction and Classification", "clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "caalm_caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES"}}, "target": "deeptmhmm", "target_idx": 2}
{"id": "mod_autocycler_trim_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim cluster assembly graphs to remove unsupported segments prior to resolution. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/cluster": "Cluster replicons in compressed assemblies with Autocycler.", "samtools/coverage": "produces a histogram or table of coverage per chromosome", "autocycler/trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "autocycler/combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "segemehl/align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection"}}, "target": "autocycler/trim", "target_idx": 2}
{"id": "mod_minimac4_compressref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compression of a reference panel for genotype imputation to `.msav` format (tools: minimac4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whatshap/phase": null, "expansionhunter": null, "agat/spextractsequences": null, "gatk4/calibratedragstrmodel": null, "minimac4/compressref": null}}, "target": "minimac4/compressref", "target_idx": 4}
{"id": "samplesheet_arch_amplicon_16s_paired_1_5", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_ltrretriever_lai_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric IDs without comments (tools: lai)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"circexplorer2/annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "ltrretriever/lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric ", "mirdeep2/mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs.", "alignoth": "Creating alignment plots from bam files"}}, "target": "ltrretriever/lai", "target_idx": 2}
{"id": "mod_biomformat_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HDF5) formats are supported (tools: biomformat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "pilon": "Automatically improve draft assemblies and find variation among strains, including large event detection", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "md5sum": "Create MD5 (128-bit) checksums"}}, "target": "biomformat/convert", "target_idx": 2}
{"id": "mod_star_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using STAR (tools: star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"methyldackel/mbias": null, "eautils/fastqstats": null, "star/align": null, "bamaligncleaner": null, "ampcombi2/parsetables": null}}, "target": "star/align", "target_idx": 2}
{"id": "mod_traitar_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Traitar3 - predict microbial phenotypes from genomic sequences using protein families (tools: traitar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hisat2_build": "Builds HISAT2 index for reference genome", "ldak_thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "deeparg_downloaddata": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "traitar_run": "Traitar3 - predict microbial phenotypes from genomic sequences using protein families", "traitar_pfamget": "Download PFAM database for traitar phenotype prediction"}}, "target": "traitar_run", "target_idx": 3}
{"id": "local_subworkflow_positionsofint_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should POSITIONSOFINT (custom/positionsofint) be built?", "criteria": {"Local subworkflow POSITIONSOFINT": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_vcftools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A set of tools written in Perl and C++ for working with VCF files (tools: vcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv_annotsv": null, "arriba_arriba": null, "vcftools": null, "bcftools_call": null, "samtools_fixmate": null}}, "target": "vcftools", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking)", "question": {"type": "choice", "instructions": "Which columns are standard for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_cageseq_transcription_4_0", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping", "pipeline": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,tss_bed": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_index_filter_deacon_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_INDEX_FILTER_DEACON", "modules": ["deacon/index", "deacon/filter"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon"}, "question": {"type": "choice", "instructions": "How should FASTQ_INDEX_FILTER_DEACON (deacon/index, deacon/filter) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_INDEX_FILTER_DEACON": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_index_filter_deacon": null}}, "target": "Use nf-core subworkflow fastq_index_filter_deacon", "target_idx": 3}
{"id": "resource_blobtk_depth_2", "category": "resource_profiling", "state": {"process": "BLOBTK_DEPTH", "tool": "blobtk/depth", "description": "Creates a bed file containing the depth of data at intervals of an aligned bam."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_DEPTH (Creates a bed file containing the depth of data at intervals of an aligned bam.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_agat_spstatistics_4", "category": "resource_profiling", "state": {"process": "AGAT_SPSTATISTICS", "tool": "agat/spstatistics", "description": "Provides different type of statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPSTATISTICS (Provides different type of statistics in text format from a GFF/GTF annotation f) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_mmseqs_fasta_cluster_1", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_FASTA_CLUSTER", "modules": ["mmseqs/createdb", "mmseqs/cluster", "mmseqs/linclust", "mmseqs/createtsv"], "description": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file."}, "question": {"type": "choice", "instructions": "How should MMSEQS_FASTA_CLUSTER (mmseqs/createdb, mmseqs/cluster, mmseqs/linclust, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Local subworkflow MMSEQS_FASTA_CLUSTER": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow mmseqs_fasta_cluster": null, "Leave them out": null}}, "target": "Use nf-core subworkflow mmseqs_fasta_cluster", "target_idx": 2}
{"id": "schema_std_crisprseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/crisprseq", "description": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`).", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/crisprseq?", "criteria": {"sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,fastq_1,fastq_2,condition,reference": null, "id,fasta,reference,optional_data,template": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null}}, "target": "sample,fastq_1,fastq_2,condition,reference", "target_idx": 1}
{"id": "mod_delly_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call structural variants (tools: delly)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "delly/call": "Call structural variants", "abacas": "Contiguate draft genome assembly", "mirtrace/qc": "A tool for quality control and tracing taxonomic origins of microRNA sequencing data"}}, "target": "delly/call", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_1_5", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_cellbender_removebackground_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data (tools: cellbender)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender/merge": null, "cellbender/removebackground": null, "anndata/barcodes": null, "gatk4/createsequencedictionary": null, "propr/propd": null}}, "target": "cellbender/removebackground", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_0", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bbmap_clumpify_3", "category": "resource_profiling", "state": {"process": "BBMAP_CLUMPIFY", "tool": "bbmap/clumpify", "description": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_CLUMPIFY (Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_custom_clustervisualization_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates UMAP and t-SNE visualizations colored by cluster (tools: scikit-learn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq/draft": "Create draft metabolic model from pathway and transporter predictions", "custom/clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "autocycler/cluster": "Cluster replicons in compressed assemblies with Autocycler.", "gtfsort": "Sort GTF files in chr/pos/feature order"}}, "target": "custom/clustervisualization", "target_idx": 1}
{"id": "intent_ask_question_3", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "build_pipeline": null, "debug_error": null}}, "target": "ask_question", "target_idx": 1}
{"id": "resource_bedtools_multiinter_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MULTIINTER", "tool": "bedtools/multiinter", "description": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MULTIINTER (Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bismark_report_3", "category": "resource_profiling", "state": {"process": "BISMARK_REPORT", "tool": "bismark/report", "description": "Collects bismark alignment reports"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_REPORT (Collects bismark alignment reports) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/eager) for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment. Input files: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bbmap_sendsketch_1", "category": "resource_profiling", "state": {"process": "BBMAP_SENDSKETCH", "tool": "bbmap/sendsketch", "description": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_SENDSKETCH (Compares query sketches to reference sketches hosted on a remote server via the ) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_invalid_process_communication_via_globals_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_ganon_report_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a ganon report file from the output of ganon classify (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paftools/sam2paf": "A program to convert bam into paf.", "rtgtools/svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "ganon/table": "Generate a multi-sample report file from the output of ganon report runs", "ganon/report": "Generate a ganon report file from the output of ganon classify"}}, "target": "ganon/report", "target_idx": 4}
{"id": "samplesheet_arch_taxprofiler_shotgun_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/taxprofiler) for Multi-taxonomic profiling of complex metagenomic shotgun reads. Input files: Short or long reads with run accession and library instrument platform.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_motus_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic meta-omics profiling using universal marker genes (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon/classify": null, "motus/merge": null, "sambamba/depth": null, "haplogrep3/classify": null, "umitools/extract": null}}, "target": "motus/merge", "target_idx": 1}
{"id": "resource_blast_updateblastdb_2", "category": "resource_profiling", "state": {"process": "BLAST_UPDATEBLASTDB", "tool": "blast/updateblastdb", "description": "Downloads a BLAST database from NCBI"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_UPDATEBLASTDB (Downloads a BLAST database from NCBI) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_megan_daa2info_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analyses a DAA file and exports information in text format (tools: megan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fcs_fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi", "megan_rma2info": "Analyses an RMA file and exports information in text format", "megan_daa2info": "Analyses a DAA file and exports information in text format", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "diamond_deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust"}}, "target": "megan_daa2info", "target_idx": 2}
{"id": "mod_antismash_antismashlite_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters. (tools: antismashlite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepbgc_pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "snpeff_download": "Genetic variant annotation and functional effect prediction toolbox", "rpbp_getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "antismash_antismashlite": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt"}}, "target": "antismash_antismashlite", "target_idx": 3}
{"id": "resource_bowtie_align_5", "category": "resource_profiling", "state": {"process": "BOWTIE_ALIGN", "tool": "bowtie/align", "description": "Align reads to a reference genome using bowtie"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_ALIGN (Align reads to a reference genome using bowtie) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bracken_combinebrackenoutputs_4", "category": "resource_profiling", "state": {"process": "BRACKEN_COMBINEBRACKENOUTPUTS", "tool": "bracken/combinebrackenoutputs", "description": "Combine output of metagenomic samples analyzed by bracken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_COMBINEBRACKENOUTPUTS (Combine output of metagenomic samples analyzed by bracken.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_24", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_verifybamid_verifybamid_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure high quality sequence reads and reliable downstream analysis. (tools: verifybamid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm2_predict": "CheckM2 bin quality prediction", "presto_filterseq": "Filter reads by quality score.", "gens_preparecovandbaf": "Tools for preparing inputs for visualization in Gens", "verifybamid_verifybamid": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "authentict_deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries"}}, "target": "verifybamid_verifybamid", "target_idx": 3}
{"id": "mod_mirtop_gff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop gff generates the GFF3 adapter format to capture miRNA variations (tools: mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem3/index": "Create bwa-mem3 index for reference genome", "mirtop/gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations", "nacho/normalize": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "kmcp/index": "Construct KMCP database from k-mer files", "mirdeep2/mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs."}}, "target": "mirtop/gff", "target_idx": 1}
{"id": "field_constraint_status_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "mod_ichorcna_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, particularly for use in cell-free DNA (tools: ichorcna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "sgdemux": "Demultiplex bgzip'd fastq files", "ichorcna/run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "cnvkit/target": "Transform bait intervals into targets more suitable for CNVkit.", "cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads."}}, "target": "ichorcna/run", "target_idx": 2}
{"id": "mod_biscuit_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexes a reference genome for use with Biscuit (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "strdust": "Tandem repeat genotyper for long reads", "parabricks/fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "biscuit/epiread": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compl", "biscuit/index": "Indexes a reference genome for use with Biscuit"}}, "target": "biscuit/index", "target_idx": 4}
{"id": "resource_ampcombi2_complete_2", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_COMPLETE", "tool": "ampcombi2/complete", "description": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_COMPLETE (A submodule that merges all output summary tables from ampcombi/parsetables in o) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_segemehl_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate genome indices for segemehl align (tools: segemehl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "segemehl_index": "Generate genome indices for segemehl align", "pbtk_pbindex": "Minimalistic tool which creates an index file that enables random access into PacBio BAM files", "gcta_makegrmpart": "Compute one partition of a GCTA genetic relationship matrix", "biscuit_index": "Indexes a reference genome for use with Biscuit"}}, "target": "segemehl_index", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_46", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_7", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_bam_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "resource_anarcii_5", "category": "resource_profiling", "state": {"process": "ANARCII", "tool": "anarcii", "description": "A language model for antigen receptor numbering"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANARCII (A language model for antigen receptor numbering) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_cowpy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Print any text in a cow or other characters (tools: cowpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem2_mem": null, "cowpy": null, "ultra_align": null, "genmod_compound": null, "msisensor_scan": null}}, "target": "cowpy", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/smrnaseq --input samplesheet.csv (Assay: Small RNA / miRNA sequencing)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/smrnaseq, determine the input samplesheet column structure for: Small RNA / miRNA sequencing.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_module_metadata_propagation_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_purgedups_getseqs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Separates out sequences purged of falsely duplicated sequences. (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purgedups/purgedups": "Purge haplotigs and overlaps for an assembly", "purgedups/getseqs": "Separates out sequences purged of falsely duplicated sequences.", "snpsift/annmemcreate": "Create memory-optimized SnpSift vardb databases from VCF files for use with SnpSift annMem annotation.\nConvert", "fqtk": "Demultiplex fastq files", "methurator/plot": "Plots results produced by methurator gtestimator."}}, "target": "purgedups/getseqs", "target_idx": 1}
{"id": "mod_lofreq_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to call low frequency variants from alignments (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "lofreq/call": "Lofreq subcommand to call low frequency variants from alignments", "genmod/annotate": "for annotating regions, frequencies, cadd scores", "biscuit/biscuitblaster": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit", "bcftools/consensus": "Compresses VCF files"}}, "target": "lofreq/call", "target_idx": 1}
{"id": "resource_bacphlip_4", "category": "resource_profiling", "state": {"process": "BACPHLIP", "tool": "bacphlip", "description": "A bacteriophage lifestyle prediction tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACPHLIP (A bacteriophage lifestyle prediction tool) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_sex_0_8", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral amplicon sequencing with primers)", "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_retry_errorstrategy_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_retry_errorstrategy_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_blobtk_create_2", "category": "resource_profiling", "state": {"process": "BLOBTK_CREATE", "tool": "blobtk/create", "description": "Creates a minimal blobdir."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_CREATE (Creates a minimal blobdir.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gatk_indelrealigner_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs local realignment around indels to correct for mapping errors (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk_indelrealigner": null, "atlas_pmd": null, "bcftools_call": null, "somalier_relate": null, "abra2": null}}, "target": "gatk_indelrealigner", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_3_2", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ChIP-seq with IP and input control design with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "schema_std_proteinfold_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinfold", "description": "Protein 3D structure prediction pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/proteinfold?", "criteria": {"id,fasta,sequence": null, "sample,fastq_1,fastq_2,antibody,control": null, "id,fasta": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "id,fasta,sequence", "target_idx": 0}
{"id": "field_constraint_sex_0_12", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "mod_atlas_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: generate VCF file from a BAM file using various calling methods (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "atlas_call": "generate VCF file from a BAM file using various calling methods", "bcftools_consensus": "Compresses VCF files", "sigprofiler": "mutational signature deconvolution of cancer cells", "dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with"}}, "target": "atlas_call", "target_idx": 1}
{"id": "field_constraint_strandedness_1_9", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"format: file-path": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_force_cube_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spatially restrict downstream analysis tasks. (tools: force)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ltrretriever_ltrretriever": "Identifies LTR retrotransposons using LTR_retriever", "force_tileextent": "Compute valid tiles for a given datacube definition and area of interest.\nThis list can be used by downstream ", "archive_extract": "Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip", "repeatmasker_repeatmasker": "Screening DNA sequences for interspersed repeats and low complexity DNA sequences", "force_cube": "Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spat"}}, "target": "force_cube", "target_idx": 4}
{"id": "resource_antismash_antismashdownloaddatabases_2", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHDOWNLOADDATABASES", "tool": "antismash/antismashdownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_bamtofastq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bamtofastq", "assay": "bamtofastq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/bamtofastq (Converts bam or cram files to fastq format and does quality )?", "criteria": {"sample_id,mapped,index,file_type": null, "sample,nuclear_image,spot_table,membrane_image": null, "id,fasta,query": null, "sample,fastq_1,fastq_2,batch,condition": null}}, "target": "sample_id,mapped,index,file_type", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_2_0", "category": "samplesheet_schema", "state": {"technology": "Mass Spectrometry", "workflow_entry": "INPUT_CHECK", "library_inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,raw_file,condition": null, "sample,mzml": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "local_subworkflow_prepilluminareads_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should PREPILLUMINAREADS (trimmomatic) be built?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPILLUMINAREADS": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 2}
{"id": "mod_seq2hla_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Precision HLA typing and expression from RNA-seq data using seq2HLA (tools: seq2hla)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_build_add_kraken2": "KRAKEN2 build custom database subworkflow", "hlala_preparegraph": "Pre-compute the graph index structure.", "hlala_typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs", "seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA"}}, "target": "seq2hla", "target_idx": 4}
{"id": "samplesheet_arch_spatial_visium_2_5", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,bam": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "pipe_all101_ampliseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Amplicon sequencing analysis workflow using DADA2 and QIIME2. Topics: 16s, 18s, amplicon-sequencing, edna, illumina, iontorrent. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "ampliseq", "target_idx": 1}
{"id": "mod_shasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using DNA reads generated by Oxford Nanopore flow cells as input. Please note Assembler is design to focus on speed, so assembly may be considered somewhat non-deterministic as final assembly may vary across executions. See https://github.com/chanzuckerberg/shasta/issues/296. (tools: shasta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo_merge": "Merge STR profiles into a multi-sample STR profile", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "purgedups_histplot": "Plots the read coverage from a purge dups statistics file and cutoffs.", "filtlong": "Filtlong filters long reads based on quality measures or short read data.", "shasta": "The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using DNA reads g"}}, "target": "shasta", "target_idx": 4}
{"id": "mod_ska_fasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create genome sketch using split k-mers (tools: ska)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "jvarkit/dict2bed": "Extract BED file from hts files containing a dictionary (VCF,BAM, CRAM, DICT, etc...)", "ska/fasta": "Create genome sketch using split k-mers", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate"}}, "target": "ska/fasta", "target_idx": 3}
{"id": "mod_resfinder_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteria (tools: resfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kma_index": "This module wraps the index module of the KMA alignment tool.", "ucsc_bigwigaverageoverbed": "compute average score of bigwig over bed file", "checkm_lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "resfinder_run": "ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteri", "vcflib_vcfuniq": "List unique genotypes. Like GNU uniq, but for VCF records. Remove records which have the same position, ref, a"}}, "target": "resfinder_run", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_3_0", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Metagenomic MAG assembly with comparative groups with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_1_5", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bamcmp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For instance, filtering out mouse reads from patient derived xenograft mouse models (PDX). (tools: bamcmp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "vembrane/sort": "Sort VCF/BCF files by custom Python expressions for variant prioritization", "survivor/merge": "Compare or merge VCF files to generate a consensus or multi sample VCF files.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "chopper": "Filter and trim long read data."}}, "target": "bamcmp", "target_idx": 0}
{"id": "field_constraint_sex_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "format: file-path": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Paired-end Whole Exome Sequencing (WES) target capture", "data_format": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Whole Exome Sequencing (WES) target capture with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_lofreq_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to remove variants with low coverage or strand bias potential (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "lofreq_filter": "Lofreq subcommand to remove variants with low coverage or strand bias potential", "tidk_plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\"."}}, "target": "lofreq_filter", "target_idx": 1}
{"id": "mod_toulligqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A post sequencing QC tool for Oxford Nanopore sequencers (tools: toulligqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"toulligqc": "A post sequencing QC tool for Oxford Nanopore sequencers", "seqfu/derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th", "busco/generateplot": "BUSCO plot generation tool", "hmmer/hmmsearch": "search profile(s) against a sequence database", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "toulligqc", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Tumor-only somatic variant calling without matched normal. Input files: Paired-end FASTQ reads from tumor biopsy without matched normal.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Tumor-only somatic variant calling without matched normal with entry step FASTQC.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_picrust2_pipeline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data (tools: picrust2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plasmidid": "assembles bacterial plasmids", "metabat2_metabat2": "Metagenome binning of contigs", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "picrust2_pipeline": "Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data"}}, "target": "picrust2_pipeline", "target_idx": 4}
{"id": "mod_quantify_rsem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment objects (tools: quantify_rsem)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "ngsbits_bedannotategc": "Annotates GC content fraction to regions in a BED file.", "ctatsplicing_prepgenomelib": "Reference preparation for CTAT-splicing", "quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje", "fastq_remove_rrna": "Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2"}}, "target": "quantify_rsem", "target_idx": 3}
{"id": "mod_mifaser_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functional annotation of metagenomic reads by assigning enzyme commission (EC) numbers (tools: mifaser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mifaser": "Functional annotation of metagenomic reads by assigning enzyme commission (EC) numbers", "repeatmasker_rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "cutesv": "structural-variant calling with cutesv"}}, "target": "mifaser", "target_idx": 0}
{"id": "subworkflow_pkg_bam_variant_calling_mpileup_bcftools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS", "modules": ["gawk", "tabix/bgzip", "bcftools/mpileup", "bcftools/merge", "bcftools/annotate", "bcftools/concat", "vcf_gather_bcftools"], "description": "Subworkflow to compute genotype likelihoods from BAM files using"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS (gawk, tabix/bgzip, bcftools/mpileup, bcftools/merge, bcftools/annotate, bcftools/concat, vcf_gather_bcftools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_variant_calling_mpileup_bcftools": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_variant_calling_mpileup_bcftools", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/diaproteomics) for Data-Independent Acquisition (DIA) quantitative mass spectrometry. Input files: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions.", "question": {"type": "choice", "instructions": "Which columns are standard for Data-Independent Acquisition (DIA) quantitative mass spectrometry input samplesheet?", "criteria": {"sample,raw_file,condition": null, "sample,fastq_1,fastq_2": null, "sample,mzml": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_1_2", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_scrnaseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection. Topics: 10x-genomics, 10xgenomics, alevin, bustools, cellranger, kallisto. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel"}}, "target": "scrnaseq", "target_idx": 4}
{"id": "resource_bowtie_align_2", "category": "resource_profiling", "state": {"process": "BOWTIE_ALIGN", "tool": "bowtie/align", "description": "Align reads to a reference genome using bowtie"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_ALIGN (Align reads to a reference genome using bowtie) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bcftools_sort_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SORT", "tool": "bcftools/sort", "description": "Sorts VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SORT (Sorts VCF files) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_medium", "target_idx": 1}
{"id": "mod_seqkit_replace_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use seqkit to find/replace strings within sequences and sequence headers (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/replace": "Use seqkit to find/replace strings within sequences and sequence headers", "seqkit/grep": "Select sequences from a large file based on name/ID", "seqkit/pair": "match up paired-end reads from two fastq files", "quant_tximport_summarizedexperiment": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedEx", "snpsift/annotate": "Annotate a VCF file with another VCF file"}}, "target": "seqkit/replace", "target_idx": 0}
{"id": "samplesheet_arch_singlecell_parse_splitseq_5_5", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Parse Biosciences Split-seq combinatorial barcoding.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/genomeassembler) for Long-read Pacific Biosciences HiFi sequencing. Input files: Single HiFi BAM or FastQ.", "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Pacific Biosciences HiFi sequencing input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_3_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Oxford Nanopore environmental metagenomic sequencing with entry step NANOPLOT.", "criteria": {"sample,fastq_1,group": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_38", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_amulety_esm2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/vcf": "Import variant genetic data using plink2", "amulety/esm2": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety.", "deepbgc/download": "Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning.", "amulety/translate": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast.", "amulety/embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu"}}, "target": "amulety/esm2", "target_idx": 1}
{"id": "subworkflow_pkg_dia_proteomics_analysis_2", "category": "subworkflow_packaging", "state": {"subworkflow": "DIA_PROTEOMICS_ANALYSIS", "modules": ["diann", "quantmsutils/dianncfg", "quantmsutils/mzmlstatistics", "quantmsutils/diann2mztab"], "description": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,"}, "question": {"type": "choice", "instructions": "How should DIA_PROTEOMICS_ANALYSIS (diann, quantmsutils/dianncfg, quantmsutils/mzmlstatistics, quantmsutils/diann2mztab) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow DIA_PROTEOMICS_ANALYSIS": null, "Use nf-core subworkflow dia_proteomics_analysis": null}}, "target": "Use nf-core subworkflow dia_proteomics_analysis", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Tumor-only somatic variant calling without matched normal. Input files: Paired-end FASTQ reads from tumor biopsy without matched normal.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_ribotricer_detectorfs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accurate detection of short and long active ORFs using Ribo-seq data (tools: ribotricer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gedi/price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "civicpy/annotate": "A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations o", "minia": "Minia is a short-read assembler based on a de Bruijn graph", "ribotricer/detectorfs": "Accurate detection of short and long active ORFs using Ribo-seq data", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}}, "target": "ribotricer/detectorfs", "target_idx": 3}
{"id": "mod_telseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Telseq: a software for calculating telomere length (tools: telseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"telseq": "Telseq: a software for calculating telomere length", "bamclipper": "This module is used to clip primer sequences from your alignments.", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "wisecondorx/newref": "Create a new reference using healthy reference samples", "seacr/callpeak": "Call peaks using SEACR on sequenced reads in bedgraph format"}}, "target": "telseq", "target_idx": 0}
{"id": "resource_bedtools_intersect_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_INTERSECT", "tool": "bedtools/intersect", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_INTERSECT (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_preprocess_seqkit_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_PREPROCESS_SEQKIT", "modules": ["fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup"], "description": "Subworkflow that preprocesses FASTQ files"}, "question": {"type": "choice", "instructions": "How should FASTQ_PREPROCESS_SEQKIT (fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_preprocess_seqkit": null, "Leave them out": null, "Local subworkflow FASTQ_PREPROCESS_SEQKIT": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_preprocess_seqkit", "target_idx": 0}
{"id": "resource_bedtools_nuc_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_NUC", "tool": "bedtools/nuc", "description": "Profiles the nucleotide content of intervals in a fasta file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_NUC (Profiles the nucleotide content of intervals in a fasta file.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_5_5", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral genome sequencing on Oxford Nanopore MinION / GridION.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_1_5", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_chromap_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_CHROMAP", "modules": ["chromap/chromap", "picard/addorreplacereadgroups", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_CHROMAP (chromap/chromap, picard/addorreplacereadgroups, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_chromap": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_CHROMAP": null}}, "target": "Use nf-core subworkflow fastq_align_chromap", "target_idx": 1}
{"id": "field_constraint_status_1_4", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "format: file-path": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_arriba_visualisation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data. (tools: arriba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba_visualisation": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "samtools_cat": "Concatenate BAM or CRAM file", "parabricks_genotypegvcf": "NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs", "bcftools_rohviz": "Visualise the output of bcftools roh", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}}, "target": "arriba_visualisation", "target_idx": 0}
{"id": "resource_bowtie2_build_4", "category": "resource_profiling", "state": {"process": "BOWTIE2_BUILD", "tool": "bowtie2/build", "description": "Builds bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_BUILD (Builds bowtie index for reference genome) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_qsv_cat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenate two or more CSV (or TSV) tables into a single table (tools: csvtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat/fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "csvtk/concat": "Concatenate two or more CSV (or TSV) tables into a single table", "qsv/cat": "Concatenate two or more CSV (or TSV) tables into a single table", "ltrfinder": "Finds full-length LTR retrotranspsons in genome sequences using the\nparallel version of LTR_Finder", "fcsgx/cleangenome": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome asse"}}, "target": "qsv/cat", "target_idx": 2}
{"id": "mod_simpleaf_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexing of transcriptome for gene expression quantification using SimpleAF (tools: simpleaf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"folddisco_index": "Build a geometric-hashing index of discontinuous structural motifs from a directory of protein structure files", "ganon_buildcustom": "Build ganon database using custom reference sequences.", "mmseqs_createindex": "Creates sequence index for mmseqs database", "paraphrase": "Parse and annotate paraphrase JSONs", "simpleaf_index": "Indexing of transcriptome for gene expression quantification using SimpleAF"}}, "target": "simpleaf_index", "target_idx": 4}
{"id": "resource_atlas_pmd_5", "category": "resource_profiling", "state": {"process": "ATLAS_PMD", "tool": "atlas/pmd", "description": "Estimate the post-mortem damage patterns of DNA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_PMD (Estimate the post-mortem damage patterns of DNA) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_ngsbits_rohhunter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: RohHunter is a tool for run of homozygosity (ROH) detection based on a variant list in VCF format. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rhocall/annotate": "Markup VCF file using rho-calls.", "seqwish/induce": "Induce a variation graph in GFA format from alignments in PAF format", "ngsbits/rohhunter": "RohHunter is a tool for run of homozygosity (ROH) detection based on a variant list in VCF format.", "bcftools/rohviz": "Visualise the output of bcftools roh", "deacon/filter": "Filter DNA sequences using index of reference genome"}}, "target": "ngsbits/rohhunter", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_14", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bedtools_slop_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SLOP", "tool": "bedtools/slop", "description": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SLOP (Adds a specified number of bases in each direction (unique values may be specifi) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnafusion --input samplesheet.csv (Assay: RNA gene fusion detection (Arriba, STAR-Fusion))", "question": {"type": "choice", "instructions": "Which columns are standard for RNA gene fusion detection (Arriba, STAR-Fusion) input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "pipe_core10_taxprofiler_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Shotgun metagenomic profiling combining multiple taxonomic classifiers into harmonized multi-sample reports.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)"}}, "target": "taxprofiler", "target_idx": 7}
{"id": "mod_picard_fixmateinformation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Verify mate-pair information between mates and fix if needed (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/fixmateinformation": "Verify mate-pair information between mates and fix if needed", "genometester4/glistmaker": "Create and count k-mer lists from nucelotide sequences.", "picard/extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at", "picard/bedtointervallist": "Creates an interval list from a bed file and a reference dict", "ctree": "Clone trees for Cancer Evolution studies from bulk sequencing data."}}, "target": "picard/fixmateinformation", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_2_4", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,primer_fwd,primer_rev": null, "sample,otu_table": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_36", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_7", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_sentieon_applyvarcal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the second pass in a two-stage process called Variant Quality Score Recalibration (VQSR).\nSpecifically, it applies filtering to the input variants based on the recalibration table produced\nin the previous step VarCal and a target sensitivity value.\nhttps://support.sentieon.com/manual/usages/general/#applyvarcal-algorithm (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/applyvarcal": null, "sentieon/datametrics": null, "custom/multiqccustombiotype": null, "annosine": null, "sentieon/bwamem": null}}, "target": "sentieon/applyvarcal", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_48", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cutandrun) for CUT&RUN / CUT&TAG chromatin profiling with IgG control. Input files: Paired-end low-input fragment FASTQs with target antibody and IgG negative control.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "resource_annotsv_installannotations_5", "category": "resource_profiling", "state": {"process": "ANNOTSV_INSTALLANNOTATIONS", "tool": "annotsv/installannotations", "description": "Install the AnnotSV annotations"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_INSTALLANNOTATIONS (Install the AnnotSV annotations) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_1_2", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping", "pipeline": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,bam": null, "sample,tss_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "field_constraint_bai_0_2", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "mod_clonalframeml_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict recomination events in bacterial genomes (tools: clonalframeml)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clonalframeml": null, "abritamr_run": null, "amrfinderplus_update": null, "ncbitools_vecscreen": null, "samtools_collate": null}}, "target": "clonalframeml", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Single-end Illumina RNA-seq with strandedness", "data_format": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "resource_bedtools_subtract_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SUBTRACT", "tool": "bedtools/subtract", "description": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining portion of A."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SUBTRACT (Finds overlaps between two sets of regions (A and B), removes the overlaps from ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_core10_rnaseq_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Bulk paired-end RNA sequencing pipeline using STAR, Salmon, and DESeq2 differential expression analysis.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "rnaseq", "target_idx": 1}
{"id": "intent_debug_error_22", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "noul_include_modular_process_syntax_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_single_hyphen_cli_params_error_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_marsseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: MARS-seq v2 pre-processing pipeline with velocity. Topics: facs-sorting, mars-seq, single-cell, single-cell-rna-seq, star-solo, transcriptional-dynamics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanostring": null, "readsimulator": null, "nanoseq": null, "coproid": null, "marsseq": null, "isoseq": null, "pathogensurveillance": null, "cutandrun": null}}, "target": "marsseq", "target_idx": 4}
{"id": "mod_epang_place_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: phylogenetic placement of query sequences in a reference tree (tools: epang)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"epang_place": "phylogenetic placement of query sequences in a reference tree", "affy_justrma": "Read CEL files into an ExpressionSet and generate a matrix", "biohansel": "Use k-mers to rapidly subtype S. enterica genomes", "epang_split": "splits an alignment into reference and query parts", "fasttree": "Produces a Newick format phylogeny from a multiple sequence alignment. Capable of bacterial genome size alignm"}}, "target": "epang_place", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_0_2", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,bam": null, "sample,fastq_1,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "noul_retry_errorstrategy_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_46", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_3_0", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Genome analysis from reference-compressed CRAM files with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,cram": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "pipe_all101_bamtofastq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Converts bam or cram files to fastq format and does quality control.. Topics: bamtofastq, conversion, cramtofastq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanoseq": null, "drugresponseeval": null, "cageseq": null, "pacvar": null, "hic": null, "variantprioritization": null, "bamtofastq": null, "rnavar": null, "pixelator": null, "viralintegration": null}}, "target": "bamtofastq", "target_idx": 6}
{"id": "qc_adapt_ont_nanoplot_2_12", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/chipseq --input samplesheet.csv (Assay: ChIP-seq with IP and input control design)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/chipseq, determine the input samplesheet column structure for: ChIP-seq with IP and input control design.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null, "sample,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/dualrnaseq) for Dual RNA-seq simultaneous host and pathogen transcriptomics. Input files: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,host_fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "schema_std_rnadnavar_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnadnavar", "assay": "rnadnavar pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnadnavar (Pipeline for RNA and DNA integrated analysis for somatic mut)?", "criteria": {"patient,sample,fastq_1,fastq_2,bam": null, "sample_id,idat_red,idat_green,group": null, "sample,trait,pascal,twas,additional_sources": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 0}
{"id": "schema_std_metapep_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metapep", "description": "From metagenomes to epitopes and beyond", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/metapep?", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample,seed": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null}}, "target": "condition,type,microbiome_path,alleles,weights_path", "target_idx": 1}
{"id": "mod_cellbender_removebackground_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data (tools: cellbender)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file", "cellbender_removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "kaiju_mergeoutputs": "Merge two tab-separated output files of Kaiju and Kraken in the column format", "bff": "Generating cell hashing calls from a matrix of count data.", "wipertools_fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files"}}, "target": "cellbender_removebackground", "target_idx": 1}
{"id": "local_subworkflow_daisribosome_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for DAISRIBOSOME (dais).", "criteria": {"Leave them out": null, "Use nf-core subworkflow daisribosome": null, "Keep the modules in the main workflow": null, "Local subworkflow DAISRIBOSOME": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 3}
{"id": "core_tool_interproscan_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Scan protein and nucleotide sequences against multiple member databases to identify structural domains, functional sites, and protein families.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"blastp": "Protein blast", "eggnog": "Orthology mapper", "diamond": "Fast protein aligner", "hmmer": "HMM protein search", "interproscan": "Scans protein sequences against InterPro member databases (Pfam, PRINTS, PROSITE)"}}, "target": "interproscan", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_1_29", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for POSITIONSOFINT (custom/positionsofint).", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null, "Leave them out": null, "Local subworkflow POSITIONSOFINT": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_29", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_all101_diaproteomics_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for data-independent-proteomics analysis? Specific context: Automated quantitative analysis of DIA proteomics mass spectrometry measurements.. Topics: data-independent-proteomics, dia-proteomics, openms, proteomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "metapep": "From metagenomes to epitopes and beyond", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]"}}, "target": "diaproteomics", "target_idx": 5}
{"id": "schema_std_rnastructurome_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnastructurome. Description: a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnastructurome.", "criteria": {"sample,group,ref_fasta,ref_gff,use_ref": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,sample_id,fastq_1,fastq_2,method": null}}, "target": "sample,sample_id,fastq_1,fastq_2,method", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_4_1", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Aligned BAM files?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_2_0", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/metatdenovo) for Environmental community metatranscriptomics de novo assembly. Input files: Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null, "sample,bam": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "local_subworkflow_daisribosome_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should this step (dais) be packaged: Custom ribosomal frameshift translation analysis?", "criteria": {"Local subworkflow DAISRIBOSOME": null, "Use nf-core subworkflow daisribosome": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 0}
{"id": "mod_svtk_rdtest2vcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert an RdTest-formatted bed to the standard VCF format. (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtk_rdtest2vcf": null, "faqcs": null, "glimpse_chunk": null, "agat_convertgff2bed": null, "agat_convertbed2gff": null}}, "target": "svtk_rdtest2vcf", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_30", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_33", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "pipe_core10_viralrecon_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Assembly and intrahost low-frequency variant calling for viral isolates and SARS-CoV-2 samples.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"viralrecon": null, "sarek": null, "ampliseq": null, "atacseq": null, "mag": null, "eager": null, "rnaseq": null, "taxprofiler": null, "chipseq": null, "scrnaseq": null}}, "target": "viralrecon", "target_idx": 0}
{"id": "mod_seqkit_sample_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sample sequences from FASTA/FASTQ files by number or proportion (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spmergeannotations": null, "seqkit_sample": null, "ichorcna_createpon": null, "cutesv": null, "agat_spflagshortintrons": null}}, "target": "seqkit_sample", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_5_2", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status", "pipeline": "nf-core/eager"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/eager, determine the input samplesheet column structure for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_34", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_autocycler_trim_1", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_TRIM", "tool": "autocycler/trim", "description": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_TRIM (Trim cluster assembly graphs to remove unsupported segments prior to resolution.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_glimpse2_phase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool for imputation and phasing from vcf file or directly from bam files. (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiasm": "Whole-genome assembly using PacBio HiFi reads", "beagle5_beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "glimpse2_phase": "Tool for imputation and phasing from vcf file or directly from bam files.", "parabricks_genotypegvcf": "NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs", "panaroo_run": "A fast and scalable tool for bacterial pangenome analysis"}}, "target": "glimpse2_phase", "target_idx": 2}
{"id": "noul_process_conditional_execution_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "core_tool_fastp_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? All-in-one FASTQ preprocessor performing automated adapter trimming, polyG tail clipping, quality filtering, and base correction.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"multiqc": null, "cutadapt": null, "trimmomatic": null, "fastp": null, "fastqc": null}}, "target": "fastp", "target_idx": 3}
{"id": "resource_agat_spmergeannotations_4", "category": "resource_profiling", "state": {"process": "AGAT_SPMERGEANNOTATIONS", "tool": "agat/spmergeannotations", "description": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated names and fixes other oddities met in those files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPMERGEANNOTATIONS (This script merge different gff annotation files in one. It uses the AGAT parser) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_37", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_samtools_reheader_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Replace the header in the bam file with the header generated by the command.\nThis command is much faster than replacing the header with a BAM→SAM→BAM conversion. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mdust": "mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences", "samtools/reheader": "Replace the header in the bam file with the header generated by the command.\nThis command is much faster than ", "bwafastalign/mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "ascat": "copy number profiles of tumour cells.", "famsa/align": "Aligns sequences using FAMSA"}}, "target": "samtools/reheader", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_6_0", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "resource_bedops_gtf2bed_1", "category": "resource_profiling", "state": {"process": "BEDOPS_GTF2BED", "tool": "bedops/gtf2bed", "description": "Convert gtf format to bed format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_GTF2BED (Convert gtf format to bed format) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "intent_build_pipeline_2", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 2}
{"id": "mod_seqkit_grep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select sequences from a large file based on name/ID (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spatyper": "Computational method for finding spa types.", "bbmap/filterbyname": "Filter out sequences by sequence header name(s)", "openms/idscoreswitcher": "Switches between different scores of peptide or protein hits in identification data", "seqkit/grep": "Select sequences from a large file based on name/ID", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in"}}, "target": "seqkit/grep", "target_idx": 3}
{"id": "noul_channel_filter_operator_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_34", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_gridss_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignments. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stacks/refmap": "ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available.", "gridss/preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and ", "gridss/generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "methyldackel/mbias": "Generates methylation bias plots from alignments", "gridss/call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment"}}, "target": "gridss/call", "target_idx": 4}
{"id": "noul_include_modular_process_syntax_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_5_3", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic tumor-normal calling from pre-aligned BAM files.", "criteria": {"patient,sample,bam": null, "sample,bam,bai": null, "sample,vcf": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "pipe_all101_sarek_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing. Topics: annotation, cancer, gatk4, genomics, germline, pre-processing. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "sarek", "target_idx": 4}
{"id": "samplesheet_arch_germline_lane_split_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Multi-lane Illumina sequencing run of clinical samples", "data_format": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_foldmason_createdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a database for Foldmason. (tools: foldmason)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": null, "busco_phylogenomics": null, "lofreq_somatic": null, "foldmason_createdb": null, "ldak_thinpredictors": null}}, "target": "foldmason_createdb", "target_idx": 3}
{"id": "mod_autocycler_resolve_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Resolve trimmed assembly graphs into final contigs within Autocycler. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "glimpse/sample": "Generates haplotype calls by sampling haplotype estimates", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "shasum": "Print SHA256 (256-bit) checksums."}}, "target": "autocycler/resolve", "target_idx": 0}
{"id": "mod_haplogrep3_classify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: classification into haplogroups (tools: haplogrep3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep2/classify": "classification into haplogroups", "centrifuge/centrifuge": "Classifies metagenomic sequence data", "haplogrep3/classify": "classification into haplogroups", "picard/scatterintervalsbyns": "Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into inte", "cnvpytor/importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file."}}, "target": "haplogrep3/classify", "target_idx": 2}
{"id": "field_constraint_bam_1_5", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_25", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_diamond_linclust_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast protein sequence clustering using a greedy incremental approach (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond_linclust": "Fast protein sequence clustering using a greedy incremental approach", "crabs_import": "In-house generated or curated data can be imported into CRABS.", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga"}}, "target": "diamond_linclust", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_4_4", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FastQ reads per sample?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_bai_0_7", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "mod_fastq_fetch_clean_hostile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files (tools: fastq_fetch_clean_hostile)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_decontaminate_deacon_hostile": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile", "fastq_fetch_clean_hostile": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files", "hostile/clean": "Removes host reads from short- and long-read FASTQ sequencing files", "sourmash/index": "Create a database of sourmash signatures (a group of FracMinHash sketches) to be used as references.", "ea-utils/gtf2bed": "Convert a GTF/GFF annotation file to BED12 format"}}, "target": "fastq_fetch_clean_hostile", "target_idx": 1}
{"id": "subworkflow_pkg_bam_docounts_contamination_angsd_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DOCOUNTS_CONTAMINATION_ANGSD", "modules": ["angsd/docounts", "angsd/contamination"], "description": "Calculate contamination of the X-chromosome with ANGSD"}, "question": {"type": "choice", "instructions": "How should BAM_DOCOUNTS_CONTAMINATION_ANGSD (angsd/docounts, angsd/contamination) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_DOCOUNTS_CONTAMINATION_ANGSD": null, "Use nf-core subworkflow bam_docounts_contamination_angsd": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_docounts_contamination_angsd", "target_idx": 2}
{"id": "mod_rundbcan_cazymeannotation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CAZyme annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZymes) from genomic data using the dbCAN annotation tool. (tools: dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "rundbcan/cazymeannotation": "CAZyme annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (", "cobrameta": "A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining o", "rundbcan/easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "aria2": "CLI Download utility"}}, "target": "rundbcan/cazymeannotation", "target_idx": 1}
{"id": "mod_sexdeterrmine_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the relative coverage on the Gonosomes vs Autosomes from the output of samtools depth, with error bars. (tools: sexdeterrmine)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "sexdeterrmine": "Calculate the relative coverage on the Gonosomes vs Autosomes from the output of samtools depth, with error ba", "stainwarpy_extractchannel": "Extract a single channel image from multiplexed tissue images using stainwarpy", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "leehom": "Bayesian reconstruction of ancient DNA fragments"}}, "target": "sexdeterrmine", "target_idx": 1}
{"id": "pipe_all101_detaxizer_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.. Topics: de-identification, decontamination, edna, fastq, filter, long-reads. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"riboseq": null, "spatialaxe": null, "drop": null, "diaproteomics": null, "sarek": null, "rnafusion": null, "mag": null, "references": null, "raredisease": null, "detaxizer": null}}, "target": "detaxizer", "target_idx": 9}
{"id": "samplesheet_arch_bulk_rnaseq_se_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Single-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "resource_atlas_pmd_1", "category": "resource_profiling", "state": {"process": "ATLAS_PMD", "tool": "atlas/pmd", "description": "Estimate the post-mortem damage patterns of DNA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_PMD (Estimate the post-mortem damage patterns of DNA) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_ampir_0", "category": "resource_profiling", "state": {"process": "AMPIR", "tool": "ampir", "description": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ampir uses a supervised statistical machine learning approach to predict AMPs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPIR (A fast and user-friendly method to predict antimicrobial peptides (AMPs) from an) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bamutil_trimbam_1", "category": "resource_profiling", "state": {"process": "BAMUTIL_TRIMBAM", "tool": "bamutil/trimbam", "description": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_TRIMBAM (trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality ) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_fastp_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_FASTP", "modules": ["fastqc", "umitools/extract", "fastp"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_FASTP (fastqc, umitools/extract, fastp) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_fastqc_umitools_fastp": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_FASTQC_UMITOOLS_FASTP": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_fastp", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_9", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_trim_fastp_fastqc_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TRIM_FASTP_FASTQC", "modules": ["fastqc", "fastp"], "description": "Read QC, fastp trimming and read qc"}, "question": {"type": "choice", "instructions": "How should FASTQ_TRIM_FASTP_FASTQC (fastqc, fastp) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_trim_fastp_fastqc": null, "Local subworkflow FASTQ_TRIM_FASTP_FASTQC": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_trim_fastp_fastqc", "target_idx": 1}
{"id": "field_constraint_fastq_2_0_2", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "intent_debug_error_24", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "debug_error", "target_idx": 0}
{"id": "mod_leafcutter_differentialsplicing_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform differential splicing analysis to identify junctions with significant changes in splicing between conditions (tools: leafcutter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leafcutter_differentialsplicing": "Perform differential splicing analysis to identify junctions with significant changes in splicing between cond", "platypus": "Platypus is a tool that efficiently and accurately calling genetic variants from next-generation DNA sequencin", "suppa_generateevents": "Generates alternative splicing events from a GTF file using SUPPA.", "suppa_clusterevents": "Cluster events based on PSI values and significantly differentially spliced events using SUPPA2.", "krona_ktimporttaxonomy": "KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot."}}, "target": "leafcutter_differentialsplicing", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_11", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_taxpasta_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Standardise and merge two or more taxonomic profiles into a single table (tools: taxpasta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rrnatranscripts": "Ribosomal RNA extraction from a GTF file.", "svtyper_svtypersso": "SVTyper-sso computes structural variant (SV) genotypes based on breakpoint depth on a SINGLE sample", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "taxpasta_merge": "Standardise and merge two or more taxonomic profiles into a single table", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "taxpasta_merge", "target_idx": 3}
{"id": "pipe_all101_coproid_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Coprolite host Identification pipeline. Topics: adna, ancient-dna, coprolite, microbiome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "metapep": "From metagenomes to epitopes and beyond", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]"}}, "target": "coproid", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/taxprofiler --input samplesheet.csv (Assay: Multi-taxonomic profiling of complex metagenomic shotgun reads)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-taxonomic profiling of complex metagenomic shotgun reads with entry step FASTQC.", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bcftools_plotvcfstats_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLOTVCFSTATS", "tool": "bcftools/plotvcfstats", "description": "Plots the output of bcftools stats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLOTVCFSTATS (Plots the output of bcftools stats) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_funcscan_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/funcscan", "description": "(Meta-)genome screening for functional and natural product gene sequences", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/funcscan?", "criteria": {"sample,fasta,protein,gbk,gff": null, "id,fasta,query": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,tools,file,index": null}}, "target": "sample,fasta,protein,gbk,gff", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_2_45", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic cancer variant calling with tumor-normal pairs", "data_format": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Single-end Oxford Nanopore direct RNA)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fast5": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for Fungal ITS1/ITS2 marker gene amplicon surveillance. Input files: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Fungal ITS1/ITS2 marker gene amplicon surveillance with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,unite_fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_fetchngs_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline to fetch metadata and raw FastQ files from public databases. Topics: ddbj, download, ena, fastq, geo, sra. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c"}}, "target": "fetchngs", "target_idx": 0}
{"id": "field_constraint_bam_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "mod_mashmap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mashmap is an approximate long read or contig mapper based on Jaccard similarity (tools: mashmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirdeep2_mapper": "miRDeep2 Mapper is a tool that prepares deep sequencing reads for downstream miRNA detection by collapsing rea", "fastq_align_dedup_bismark": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity", "biscuit_align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "seqtk_mergepe": "Interleave pair-end reads from FastQ files"}}, "target": "mashmap", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_42", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_pangolin_updatedata_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Phylogenetic Assignment of Named Global Outbreak LINeages (tools: pangolin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_create_som_pon_gatk": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a geno", "skani/sketch": "Storing skani sketches/indices on disk.", "blast/blastdbcmd": "Retrieve entries from a BLAST database", "pangolin/updatedata": "Phylogenetic Assignment of Named Global Outbreak LINeages", "bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big"}}, "target": "pangolin/updatedata", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_1_33", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_samtools_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_index": "Indexes a reference genome for use with Biscuit", "samtools_index": "Index SAM/BAM/CRAM file", "alignoth": "Creating alignment plots from bam files", "orfipy": "orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner.", "bowtie_build": "Create bowtie index for reference genome"}}, "target": "samtools_index", "target_idx": 1}
{"id": "resource_antismash_antismash_0", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASH", "tool": "antismash/antismash", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASH (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_coproid_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Coprolite host Identification pipeline. Topics: adna, ancient-dna, coprolite, microbiome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rangeland": null, "scrnaseq": null, "rnadnavar": null, "rnastructurome": null, "rnafusion": null, "molkart": null, "fetchngs": null, "coproid": null, "viralmetagenome": null, "bacass": null}}, "target": "coproid", "target_idx": 7}
{"id": "samplesheet_arch_ont_direct_rna_se_0_3", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fast5": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_1_5", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,bam": null, "sample,fast5": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_10", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_cmseq_polymut_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates polymorphic site rates over protein coding genes (tools: cmseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"t1k_run": "write your description here", "cmseq_polymut": "Calculates polymorphic site rates over protein coding genes", "catpack_addnames": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "kraken2_kraken2": "Classifies metagenomic sequence data", "quilt_quilt2": "QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased re"}}, "target": "cmseq_polymut", "target_idx": 1}
{"id": "resource_bakta_bakta_3", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTA", "tool": "bakta/bakta", "description": "Annotation of bacterial genomes (isolates, MAGs) and plasmids"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTA (Annotation of bacterial genomes (isolates, MAGs) and plasmids) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gatk4_estimatelibrarycomplexity_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimates the numbers of unique molecules in a sequencing library. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellsnp/modea": "Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A ", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "gatk4/estimatelibrarycomplexity": "Estimates the numbers of unique molecules in a sequencing library.", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "samtools/collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma"}}, "target": "gatk4/estimatelibrarycomplexity", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_1_3", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,strandedness": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "schema_std_hlatyping_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hlatyping", "assay": "hlatyping pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/hlatyping (Precision HLA typing from next-generation sequencing data)?", "criteria": {"sample,fastq_1,fastq_2,bam,seq_type": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample,fastq_1": null, "fasta,assembly,ncbi,gff,fastq": null}}, "target": "sample,fastq_1,fastq_2,bam,seq_type", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_qc_trim_filter_setstrandedness_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS", "modules": ["bbmap/bbsplit", "cat/fastq", "fastqc", "fq/lint", "fastq_remove_rrna", "fastq_subsample_fq_salmon", "fastq_fastqc_umitools_trimgalore", "fastq_fastqc_umitools_fastp"], "description": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files, preparing them for downstream analysis."}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS (bbmap/bbsplit, cat/fastq, fastqc, fq/lint, fastq_remove_rrna, fastq_subsample_fq_salmon, fastq_fastqc_umitools_trimgalore, fastq_fastqc_umitools_fastp) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness": null, "Local subworkflow FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness", "target_idx": 0}
{"id": "pipe_all101_metatdenovo_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses.. Topics: eukaryotes, metagenomics, metatranscriptomics, prokaryotes, viruses. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mag": null, "nanostring": null, "metatdenovo": null, "scnanoseq": null, "funcprofiler": null}}, "target": "metatdenovo", "target_idx": 2}
{"id": "resource_amrfinderplus_update_5", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_UPDATE", "tool": "amrfinderplus/update", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_UPDATE (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry). Input files: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,matrix,barcodes,features": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "mod_regenie_runl0_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run one REGENIE step 1 level-0 job from a split master file (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsift_split": null, "regenie_runl1": null, "regenie_step2": null, "picard_fastqtosam": null, "regenie_runl0": null}}, "target": "regenie_runl0", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq. Input files: FastQ reads per sample.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_0_3", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,cram,crai": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,cram,crai", "target_idx": 0}
{"id": "mod_sentieon_collectvcmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accelerated implementation of the Picard CollectVariantCallingMetrics tool. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_collectvcmetrics": null, "panaroo_run": null, "bcftools_call": null, "aardvark_compare": null, "gfatools_stat": null}}, "target": "sentieon_collectvcmetrics", "target_idx": 0}
{"id": "mod_samtools_calmd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculates MD and NM tags (tools: samtoolscalmd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": "split single end read groups by length and merge paired end reads", "samtools/calmd": "calculates MD and NM tags", "skani/search": "Memory-efficient ANI database queries with skani.", "gatk4/addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "samtools/calmd", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_2_4", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen", "pipeline": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_2_4", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions", "pipeline": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null, "sample,fasta": null, "sample,mzml": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "mod_vireo_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use vireo to perform donor deconvolution for multiplexed scRNA-seq data (tools: vireo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "traitar/run": "Traitar3 - predict microbial phenotypes from genomic sequences using protein families", "taxonkit/list": "Generate taxonomic subtrees based on taxonids", "fasta_clean_fcs": "Foreign Contamination Screen (FCS) is a tool suite for identifying and removing contaminant sequences in genom", "vireo": "Use vireo to perform donor deconvolution for multiplexed scRNA-seq data"}}, "target": "vireo", "target_idx": 4}
{"id": "resource_busco_plot_4", "category": "resource_profiling", "state": {"process": "BUSCO_PLOT", "tool": "busco/plot", "description": "BUSCO summary plot generation using the built-in 'busco --plot' command"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PLOT (BUSCO summary plot generation using the built-in 'busco --plot' command) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_sylphtax_taxprof_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Incorporates taxonomy into sylph metagenomic classifier (tools: sylphtax)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"windowmasker_ustat": "A program to take a counts file and creates a file of genomic co-ordinates to be masked.", "verifybamid_verifybamid2": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "sylphtax_taxprof": "Incorporates taxonomy into sylph metagenomic classifier", "ganon_buildcustom": "Build ganon database using custom reference sequences.", "ganon_report": "Generate a ganon report file from the output of ganon classify"}}, "target": "sylphtax_taxprof", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_27", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "intent_build_pipeline_21", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "debug_error": null, "prepare_data": null, "build_pipeline": null}}, "target": "build_pipeline", "target_idx": 3}
{"id": "field_constraint_strandedness_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null, "format: file-path": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_35", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_hificnv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number variant calling from PacBio HiFi reads (tools: hificnv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqtk/subseq": "Select only sequences that match the filtering condition", "cnvkit/target": "Transform bait intervals into targets more suitable for CNVkit.", "fastk/merge": "A tool to merge FastK histograms", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples).", "hificnv": "Copy number variant calling from PacBio HiFi reads"}}, "target": "hificnv", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wes_pe_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Paired-end Whole Exome Sequencing (WES) target capture. Input files: Paired-end FASTQs from Agilent/Twist exome target capture.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_agat_spfilterbyorfsize_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The script reads a gff annotation file, and create two output files, one contains the gene models with ORF passing the test, the other contains the rest. By default the test is \"> 100\" that means all gene models that have ORF longer than 100 Amino acids, will pass the test. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "gappa/examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "opt/flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple"}}, "target": "agat/spfilterbyorfsize", "target_idx": 0}
{"id": "core_tool_fastp_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? All-in-one FASTQ preprocessor performing automated adapter trimming, polyG tail clipping, quality filtering, and base correction.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"cutadapt": "Removes adapter sequences", "fastp": "An ultra-fast all-in-one FASTQ preprocessor (QC, adapter trimming, filtering, splitting)", "fastqc": "Quality control for FASTQ", "trimmomatic": "Read trimming tool", "multiqc": "Report aggregator"}}, "target": "fastp", "target_idx": 1}
{"id": "mod_hifitrimmer_trim_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/FASTQ input and emits gzip-compressed FASTA (default) or FASTQ, or SAM, BAM, or CRAM according to the selected output format. (tools: hifi-trimmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "hifiadapterfilt/hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "hifitrimmer/trim": "Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/F", "macs2/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "hificnv": "Copy number variant calling from PacBio HiFi reads"}}, "target": "hifitrimmer/trim", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_33", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_1_3", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null, "sample,target,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "mod_wfmash_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a pangenome-scale aligner (tools: wfmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass.", "cafe": "Analysis of gene family evolution", "coptr_extract": "Computes the coverage map along the reference genome", "wfmash": "a pangenome-scale aligner", "gstama_collapse": "Collapse redundant transcript models in Iso-Seq data."}}, "target": "wfmash", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_4_2", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end Tn5 transposed FASTQs across conditions and replicates?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "resource_bwa_samse_1", "category": "resource_profiling", "state": {"process": "BWA_SAMSE", "tool": "bwa/samse", "description": "Convert bwa SA coordinate file to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMSE (Convert bwa SA coordinate file to SAM format) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_high", "target_idx": 0}
{"id": "mod_kalign_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using kalign (tools: kalign)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "ngmaster": "Serotyping Neisseria gonorrhoeae assemblies", "regenie/splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "bwa/mem": "Performs fastq alignment to a fasta reference using BWA", "kalign/align": "Aligns sequences using kalign"}}, "target": "kalign/align", "target_idx": 4}
{"id": "field_constraint_expected_cells_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_8", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_biscuit_index_0", "category": "resource_profiling", "state": {"process": "BISCUIT_INDEX", "tool": "biscuit/index", "description": "Indexes a reference genome for use with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_INDEX (Indexes a reference genome for use with Biscuit) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_3_1", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "template": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CAGE-seq 5-prime capped transcript end sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_homer_makeucscfile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a UCSC bed graph with the HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer/makeucscfile": "Create a UCSC bed graph with the HOMER suite", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "seacr/callpeak": "Call peaks using SEACR on sequenced reads in bedgraph format", "idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)", "doubletdetection": "Doublet detection in single-cell RNA-seq data"}}, "target": "homer/makeucscfile", "target_idx": 0}
{"id": "resource_blat_1", "category": "resource_profiling", "state": {"process": "BLAT", "tool": "blat", "description": "Queries a sequence subject"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAT (Queries a sequence subject) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_sylph_query_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sylph query command for querying genome databases against reads/metagenomes (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_query": null, "freyja_demix": null, "sylph_query": null, "pydamage_filter": null, "entrezdirect_esummary": null}}, "target": "sylph_query", "target_idx": 2}
{"id": "mod_holodeck_mutate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a VCF of random mutations from a reference genome with holodeck (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"survivor_simsv": "Simulate an SV VCF file based on a reference genome", "hmmer_hmmemit": "emit sequences from a profile HMM", "bbmap_bbnorm": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result i", "learnmsa_align": "Align sequences using learnMSA", "holodeck_mutate": "Generate a VCF of random mutations from a reference genome with holodeck"}}, "target": "holodeck_mutate", "target_idx": 4}
{"id": "mod_hmmer_eslreformat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: reformats sequence files, see HMMER documentation for details. The module requires that the format is specified in ext.args in a config file, and that this comes last. See the tools help for possible values. (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "csvtk/sort": "Sort  CSV (or TSV) tables", "hmmer/eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie", "sentieon/hsmetrics": "Collects hybrid-selection (HS) metrics for a SAM or BAM file.", "mgikit/demultiplex": "Demultiplex MGI fastq files"}}, "target": "hmmer/eslreformat", "target_idx": 2}
{"id": "mod_plasmidid_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: assembles bacterial plasmids (tools: plasmidid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"oarfish_readmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Map r", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "plasmidid": "assembles bacterial plasmids", "fairy_coverage": "Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a Meta", "abacas": "Contiguate draft genome assembly"}}, "target": "plasmidid", "target_idx": 2}
{"id": "resource_bakta_baktadbdownload_0", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTADBDOWNLOAD", "tool": "bakta/baktadbdownload", "description": "Downloads BAKTA database from Zenodo"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTADBDOWNLOAD (Downloads BAKTA database from Zenodo) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_picard_crosscheckfingerprints_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Checks that all data in the set of input files appear to come from the same individual (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "picard_crosscheckfingerprints": "Checks that all data in the set of input files appear to come from the same individual", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bedtools_jaccard": "Calculate Jaccard statistic b/w two feature files.", "mmseqs_createindex": "Creates sequence index for mmseqs database"}}, "target": "picard_crosscheckfingerprints", "target_idx": 1}
{"id": "subworkflow_pkg_bam_markduplicates_samtools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_SAMTOOLS", "modules": ["samtools/collate", "samtools/fixmate", "samtools/sort", "samtools/markdup"], "description": "Samtools markduplicate SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_SAMTOOLS (samtools/collate, samtools/fixmate, samtools/sort, samtools/markdup) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_markduplicates_samtools": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_MARKDUPLICATES_SAMTOOLS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_markduplicates_samtools", "target_idx": 0}
{"id": "mod_bam_applybqsr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-gather across genomic intervals: when\nmore than one interval file is supplied per sample, the interval-level\noutputs are merged back together with samtools merge. When no intervals\nare supplied (num_intervals: 0), ApplyBQSR is run once on the whole\ninput and no merge step is performed. (tools: bam_applybqsr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/bcf": "Analyses binary variant call format (BCF) files using plink", "blast/makeblastdb": "Builds a BLAST database", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "bamclipper": "This module is used to clip primer sequences from your alignments.", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga"}}, "target": "bam_applybqsr", "target_idx": 4}
{"id": "mod_nucmer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences. (tools: nucmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "krona_ktimporttext": "Creates a Krona chart from text files listing quantities and lineages.", "nucmer": "NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences.", "xz_decompress": "Decompresses files with xz."}}, "target": "nucmer", "target_idx": 3}
{"id": "pipe_all101_rnasplice_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis. Topics: alternative-splicing, rna, rna-seq, splicing. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous"}}, "target": "rnasplice", "target_idx": 4}
{"id": "samplesheet_arch_riboseq_profiling_1_2", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness", "pipeline": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,bam": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "field_constraint_bai_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_3", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_preseq_lcextrap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software for predicting library complexity and genome coverage in high-throughput sequencing (tools: preseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsites": null, "polypolish/polish": null, "preseq/lcextrap": null, "bam_qc_rnaseq": null, "nonpareil/nonpareilcurvesr": null}}, "target": "preseq/lcextrap", "target_idx": 2}
{"id": "mod_multiqcsav_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregate results from bioinformatics analyses across many samples into a single report, with support for multiqc_sav plugin (tools: multiqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"multiqcsav": "Aggregate results from bioinformatics analyses across many samples into a single report, with support for mult", "cooler/digest": "Generate fragment-delimited genomic bins", "multiqc": "Aggregate results from bioinformatics analyses across many samples into a single report", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "hasheddrops": "Generating cell hashing calls from a matrix of count data."}}, "target": "multiqcsav", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_4_2", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Nanopore sequencing run with sample to barcode assignment and flowcell type?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "resource_bwa_index_4", "category": "resource_profiling", "state": {"process": "BWA_INDEX", "tool": "bwa/index", "description": "Create BWA index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_INDEX (Create BWA index for reference genome) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_high", "target_idx": 1}
{"id": "resource_annotsv_annotsv_3", "category": "resource_profiling", "state": {"process": "ANNOTSV_ANNOTSV", "tool": "annotsv/annotsv", "description": "Annotation and Ranking of Structural Variation"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_ANNOTSV (Annotation and Ranking of Structural Variation) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_rbt_vcfsplit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool for splitting VCF/BCF files into N equal chunks, including BND support (tools: rust-bio-tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "gridss_annotate": "Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmaske", "rbt_vcfsplit": "A tool for splitting VCF/BCF files into N equal chunks, including BND support", "bam_stats_mirna_mirtop": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 ", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "rbt_vcfsplit", "target_idx": 2}
{"id": "mod_gatk4_svannotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds predicted functional consequence, gene overlap, and noncoding element overlap annotations to SV VCF from GATK-SV pipeline. Input files are an SV VCF, a GTF file containing primary or canonical transcripts, and a BED file containing noncoding elements. Output file is an annotated SV VCF. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_svannotate": "Adds predicted functional consequence, gene overlap, and noncoding element overlap annotations to SV VCF from ", "bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "anarcii": "A language model for antigen receptor numbering", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "octopusv_correct": "Standardize a caller VCF into OctopuSV SVCF format."}}, "target": "gatk4_svannotate", "target_idx": 0}
{"id": "mod_mash_dist_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate Mash distances between reference and query sequences (tools: mash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpdists": "Pairwise SNP distance matrix from a FASTA sequence alignment", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "mash/dist": "Calculate Mash distances between reference and query sequences", "ariba/run": "Query input FASTQs against Ariba formatted databases", "freyja/variants": "call variant and sequencing depth information of the variant"}}, "target": "mash/dist", "target_idx": 2}
{"id": "mod_spotiflow_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Spotiflow, accurate and efficient spot detection with stereographic flow. (tools: spotiflow)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "ngscheckmate_vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "baysor_run": "Bayesian segmentation of spatial transcriptomics data.", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope"}}, "target": "spotiflow", "target_idx": 0}
{"id": "mod_bamtofastq10x_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Long Ranger back to FASTQ files that can be used as inputs to re-run analysis (tools: bamtofastq10x)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": null, "bamtofastq10x": null, "gatk4spark/baserecalibrator": null, "bamaligncleaner": null, "somalier/ancestry": null}}, "target": "bamtofastq10x", "target_idx": 1}
{"id": "mod_vg_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: vg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"helitronscanner_draw": "HelitronScanner draw tool for Helitron transposons in genomes", "bcftools_index": "Index VCF tools", "biscuit_index": "Indexes a reference genome for use with Biscuit", "vg_index": "write your description here", "localcdsearch_annotate": "A command-line tool for local protein domain annotation using NCBI's Conserved Domain Database (CDD)"}}, "target": "vg_index", "target_idx": 3}
{"id": "mod_bedtools_maskfasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: masks sequences in a FASTA file based on intervals defined in a feature file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sigprofiler": null, "bamutil_clipoverlap": null, "agat_convertbed2gff": null, "annotsv_annotsv": null, "bedtools_maskfasta": null}}, "target": "bedtools_maskfasta", "target_idx": 4}
{"id": "resource_autocycler_combine_1", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMBINE", "tool": "autocycler/combine", "description": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMBINE (Merge resolved cluster assemblies into final consensus outputs with Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_dynamic_resource_allocation_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_3", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_detaxizer_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/detaxizer. Description: A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/detaxizer.", "criteria": {"sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,seq_data,pbi,start_from": null, "sample,fastq_1,fastq_2,rundir,tags": null}}, "target": "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1", "target_idx": 0}
{"id": "field_constraint_fastq_2_1_13", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null, "type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "mod_biomformat_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HDF5) formats are supported (tools: biomformat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "agat_convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "snpsift_annmem": "Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-opt", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD"}}, "target": "biomformat_convert", "target_idx": 4}
{"id": "mod_ribocode_prepare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare the annotation files for RiboCode ORF calling (tools: ribocode)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode/metaplots": "Set up RiboCode ORF calling with metaplots", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "gatk4/splitintervals": "Split intervals into sub-interval files.", "ribocode/ribocode": "Call ORFs with RiboCode from Ribo-Seq data", "ribocode/prepare": "Prepare the annotation files for RiboCode ORF calling"}}, "target": "ribocode/prepare", "target_idx": 4}
{"id": "resource_agat_spaddintrons_4", "category": "resource_profiling", "state": {"process": "AGAT_SPADDINTRONS", "tool": "agat/spaddintrons", "description": "Add intron features to gtf/gff file without intron features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPADDINTRONS (Add intron features to gtf/gff file without intron features.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_seqkit_fq2fa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert FASTQ to FASTA format (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/extractoverlappingfragments": null, "adapterremovalfixprefix": null, "haplogrep2/classify": null, "art/illumina": null, "seqkit/fq2fa": null}}, "target": "seqkit/fq2fa", "target_idx": 4}
{"id": "schema_std_createpanelrefs_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createpanelrefs", "assay": "createpanelrefs pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/createpanelrefs (Generate Panel of Normals, models or other similar reference)?", "criteria": {"id,fasta,query": null, "sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "fasta,assembly,ncbi,gff,fastq": null}}, "target": "sample,bam,bai,cram,crai", "target_idx": 1}
{"id": "mod_custom_matrixfilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: filter a matrix based on a minimum value and numbers of samples that must pass. (tools: matrixfilter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "custom_matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass.", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "deeptools_plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "mm2plus_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences"}}, "target": "custom_matrixfilter", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_7_2", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "resource_blobtk_plot_3", "category": "resource_profiling", "state": {"process": "BLOBTK_PLOT", "tool": "blobtk/plot", "description": "Creates differing styles of blobplots depending on provided arguments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_PLOT (Creates differing styles of blobplots depending on provided arguments.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_fastq_subsample_fq_salmon_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subsample fastq (tools: fastq_subsample_fq_salmon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/run": "Query input FASTQs against Ariba formatted databases", "fastq_subsample_fq_salmon": "Subsample fastq", "ariba/getref": "Download and prepare database for Ariba analysis", "bedgraph_bedclip_bedgraphtobigwig": "Convert bedgraph to bigwig with clip", "gatk4/variantstotable": "Extract fields from a VCF file to a tab-delimited table"}}, "target": "fastq_subsample_fq_salmon", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_2_14", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_phyloplace_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.. Topics: evolution, evolutionary-tree, phylogenetic-placement, phylogenetics, sequence-classification, taxonomy-assignment. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phyloplace": null, "variantbenchmarking": null, "diaproteomics": null, "pairgenomealign": null, "mag": null, "seqinspector": null, "metatdenovo": null, "atacseq": null}}, "target": "phyloplace", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_7_2", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "NANOPLOT", "library_inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_25", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_4_3", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "template": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions?", "criteria": {"sample,raw_file,condition": null, "sample,peptides_tsv": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents))", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents).", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_spring_compress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, efficient, lossless compression of FASTQ files. (tools: spring)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse2/phase": "Tool for imputation and phasing from vcf file or directly from bam files.", "presto/filterseq": "Filter reads by quality score.", "spring/compress": "Fast, efficient, lossless compression of FASTQ files.", "ariba/getref": "Download and prepare database for Ariba analysis", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads"}}, "target": "spring/compress", "target_idx": 2}
{"id": "resource_biscuit_qc_2", "category": "resource_profiling", "state": {"process": "BISCUIT_QC", "tool": "biscuit/qc", "description": "Perform basic quality control on a BAM file generated with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_QC (Perform basic quality control on a BAM file generated with Biscuit) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_0_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,fastq_1": null, "sample,rrna_fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "pipe_all101_createpanelrefs_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Generate Panel of Normals, models or other similar references from lots of samples. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralmetagenome": null, "viralintegration": null, "createpanelrefs": null, "genomeqc": null, "denovotranscript": null}}, "target": "createpanelrefs", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_15", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "assay_type": "RNA gene fusion detection (Arriba, STAR-Fusion)", "data_format": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fusion_bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "noul_retry_errorstrategy_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_4_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads for immunoprecipitation and input chromatin?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "mod_hamronization_summarize_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to summarize and combine all hAMRonization reports into a single file (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ataqv/mkarv": "mkarv function of a corresponding ataqv tool", "dshbio/filtergff3": "Filter features in gzipped GFF3 format", "hamronization/amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "hamronization/rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification.", "hamronization/summarize": "Tool to summarize and combine all hAMRonization reports into a single file"}}, "target": "hamronization/summarize", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_1_7", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_llamacpppython_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Python wrapper for running locally-hosted LLM with llama.cpp (tools: llama-cpp-python)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stringtie/merge": "Merges the annotation gtf file and the stringtie output gtf files", "huggingface/download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "llamacpppython/run": "Python wrapper for running locally-hosted LLM with llama.cpp", "controlfreec/freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "isoseq/refine": "Remove polyA tail and artificial concatemers"}}, "target": "llamacpppython/run", "target_idx": 2}
{"id": "subworkflow_pkg_cache_download_ensemblvep_snpeff_1", "category": "subworkflow_packaging", "state": {"subworkflow": "CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "snpeff/download"], "description": "downlad annotation cache for snpeff and ensemblvep"}, "question": {"type": "choice", "instructions": "How should CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF (ensemblvep/download, snpeff/download) be structured in DSL2?", "criteria": {"Local subworkflow CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF": null, "Leave them out": null, "Use nf-core subworkflow cache_download_ensemblvep_snpeff": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow cache_download_ensemblvep_snpeff", "target_idx": 2}
{"id": "mod_rapidnj_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a Newick format phylogeny from a multiple sequence alignment using a Neighbour-Joining algorithm. Capable of bacterial genome size alignments. (tools: rapidnj)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa/generateevents": "Generates alternative splicing events from a GTF file using SUPPA.", "rapidnj": "Produces a Newick format phylogeny from a multiple sequence alignment using a Neighbour-Joining algorithm. Cap", "cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm", "sentieon/wgsmetrics": "Collects whole genome quality metrics from a bam file", "epang/place": "phylogenetic placement of query sequences in a reference tree"}}, "target": "rapidnj", "target_idx": 1}
{"id": "mod_baysor_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bayesian segmentation of spatial transcriptomics data. (tools: baysor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ilastik_pixelclassification": null, "bcftools_csq": null, "kraken2_add": null, "baysor_run": null, "cellpose": null}}, "target": "baysor_run", "target_idx": 3}
{"id": "resource_biohansel_5", "category": "resource_profiling", "state": {"process": "BIOHANSEL", "tool": "biohansel", "description": "Use k-mers to rapidly subtype S. enterica genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOHANSEL (Use k-mers to rapidly subtype S. enterica genomes) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_crabz_decompress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decompress files with crabz (tools: crabz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crabz/decompress": null, "xz/decompress": null, "unzip": null, "pbtk/pbindex": null, "traitar/pfamget": null}}, "target": "crabz/decompress", "target_idx": 0}
{"id": "mod_homer_pos2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converting from HOMER peak to BED file formats (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer_pos2bed": null, "idr": null, "entrezdirect_esummary": null, "fqtk": null, "homer_annotatepeaks": null}}, "target": "homer_pos2bed", "target_idx": 0}
{"id": "mod_hlala_preparegraph_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pre-compute the graph index structure. (tools: hlala)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_bwa": "Align reads to a reference genome using bwa then sort with samtools", "hlala/preparegraph": "Pre-compute the graph index structure.", "hlala/typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "arcashla/extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "metaeuk/easypredict": "Annotation of eukaryotic metagenomes using MetaEuk"}}, "target": "hlala/preparegraph", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_4_3", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "template": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering?", "criteria": {"sample,fastq_1,fastq_2,environment": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 0}
{"id": "mod_bwameth_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs indexing of c2t converted reference genome (tools: bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_index_bismark_bwameth": null, "bwameth/index": null, "panacus/histgrowth": null, "seqtk/sample": null, "parabricks/fq2bammeth": null}}, "target": "bwameth/index", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Longitudinal cancer monitoring across multiple timepoints)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bismark_methylationextractor_4", "category": "resource_profiling", "state": {"process": "BISMARK_METHYLATIONEXTRACTOR", "tool": "bismark/methylationextractor", "description": "Extracts methylation information for individual cytosines from alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_METHYLATIONEXTRACTOR (Extracts methylation information for individual cytosines from alignments.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq with strandedness", "data_format": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_cooler_zoomify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a multi-resolution cooler file by coarsening (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec_assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "cooler_zoomify": "Generate a multi-resolution cooler file by coarsening", "pairtools_dedup": "Find and remove PCR/optical duplicates", "cooler_balance": "Run matrix balancing on a cool file", "cooltools_insulation": "Calculate the diamond insulation scores and call insulating boundaries"}}, "target": "cooler_zoomify", "target_idx": 1}
{"id": "mod_jasminesv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Jointly Accurate Sv Merging with Intersample Network Edges (tools: jasminesv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_split": "Find split or spliced alignments in a MAF file", "gatk_unifiedgenotyper": "SNP and Indel variant caller on a per-locus basis", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "jasminesv": "Jointly Accurate Sv Merging with Intersample Network Edges", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient "}}, "target": "jasminesv", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_13", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_2", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_30", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_funcprofiler_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/funcprofiler. Description: Read-based functional profiling of microbiome sequencing data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/funcprofiler.", "criteria": {"sample,fastq_1,fastq_2,barcode_details": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 3}
{"id": "pipe_all101_fastqrepair_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for corruption analysis? Specific context: A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, and settles reads that became disordered. Topics: corruption, data-cleaning, data-recovery, fastq, fastq-corrupted, fastq-format. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a"}}, "target": "fastqrepair", "target_idx": 4}
{"id": "schema_std_tfactivity_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/tfactivity. Description: Bioinformatics pipeline that makes use of expression and open chromatin data to identify differentially active transcription factors across conditions..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/tfactivity.", "criteria": {"sample_id,idat_red,idat_green,group": null, "sample,nuclear_image,spot_table,membrane_image": null, "family_id,sample,file_path,hpo_terms,sex": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "sample,condition,assay,peak_file,footprinting", "target_idx": 3}
{"id": "mod_odgi_layout_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and id-compacted. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/head": "Subset FASTA/FASTQ files to some number of sequences", "odgi/layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "odgi/stats": "Metrics describing a variation graph and its path relationship.", "mirtop/gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations", "odgi/unchop": "Merge unitigs into a single node preserving the node order."}}, "target": "odgi/layout", "target_idx": 1}
{"id": "core_tool_minimap2_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Long-read mapping of Oxford Nanopore and PacBio HiFi sequencing reads against human and microbial reference assemblies.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"minimap2": "Versatile pairwise aligner for long reads, spliced transcripts, and assemblies", "subread": "Alignment tool", "star": "RNA aligner", "bowtie2": "Short read aligner", "bwa_mem": "DNA aligner"}}, "target": "minimap2", "target_idx": 0}
{"id": "core_tool_quast_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Evaluate, compare, and compute quality metrics (N50, L50, misassemblies, completeness) for draft genome assemblies against reference genomes.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"multiqc": null, "checkm": null, "mummer": null, "quast": null, "busco": null}}, "target": "quast", "target_idx": 3}
{"id": "schema_std_airrflow_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/airrflow", "description": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/airrflow?", "criteria": {"sample_id,subject_id,species,pcr_target_locus,tissue": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,fastq_1,fastq_2,library_id,lane": null}}, "target": "sample_id,subject_id,species,pcr_target_locus,tissue", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/bacass) for Hybrid bacterial assembly combining short Illumina and long Nanopore reads. Input files: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_pcangsd_inbreeding_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate per-sample inbreeding coefficients from genotype likelihoods (tools: pcangsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pcangsd/inbreeding": "Estimate per-sample inbreeding coefficients from genotype likelihoods", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "krakenuniq/build": "Download and build (custom) KrakenUniq databases", "rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome"}}, "target": "pcangsd/inbreeding", "target_idx": 0}
{"id": "mod_skani_search_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Memory-efficient ANI database queries with skani. (tools: skani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "skani/search": "Memory-efficient ANI database queries with skani.", "varlociraptor/filterfdr": "Filter Varlociraptor variant calls using FDR control.", "survivor/bedpetovcf": "Converts a bedpe file to a VCF file (beta version)", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "skani/search", "target_idx": 1}
{"id": "mod_conifer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate confidence scores from Kraken2 output (tools: conifer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whatshap/haplotag": "Tag reads by haplotype", "catpack/download": "Downloads the required files for either Nr or GTDB for building into a CAT database", "conifer": "Calculate confidence scores from Kraken2 output", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "kaiju/kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database"}}, "target": "conifer", "target_idx": 2}
{"id": "noul_process_conditional_execution_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_35", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_angsd_realsfs_5", "category": "resource_profiling", "state": {"process": "ANGSD_REALSFS", "tool": "angsd/realsfs", "description": "Estimate site frequency spectrum from site allele frequencies"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_REALSFS (Estimate site frequency spectrum from site allele frequencies) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_mgikit_demultiplex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex MGI fastq files (tools: mgikit demultiplex)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "president": "Calculate pairwise nucleotide identity with respect to a reference sequence", "doubletdetection": "Doublet detection in single-cell RNA-seq data", "mgikit_demultiplex": "Demultiplex MGI fastq files", "bcl2fastq": "Demultiplex Illumina BCL files"}}, "target": "mgikit_demultiplex", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_28", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_ganon_classify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classify FASTQ files against ganon database (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon/classify": "Classify FASTQ files against ganon database", "imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op", "custom/summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "ganon/table": "Generate a multi-sample report file from the output of ganon report runs"}}, "target": "ganon/classify", "target_idx": 0}
{"id": "mod_cellrangerarc_mkgtf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build a filtered gtf needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkgtf command. (tools: cellrangerarc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "varscan/processsomatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "cellrangerarc/mkgtf": "Module to build a filtered gtf needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkgtf ", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "odgi/build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1."}}, "target": "cellrangerarc/mkgtf", "target_idx": 2}
{"id": "resource_art_illumina_3", "category": "resource_profiling", "state": {"process": "ART_ILLUMINA", "tool": "art/illumina", "description": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ART_ILLUMINA (Simulation tool to generate synthetic Illumina next-generation sequencing reads) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_vcf_annotate_snpeff_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_SNPEFF", "modules": ["snpeff", "snpeff/snpeff", "htslib/bgziptabix"], "description": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_SNPEFF (snpeff, snpeff/snpeff, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow VCF_ANNOTATE_SNPEFF": null, "Use nf-core subworkflow vcf_annotate_snpeff": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_annotate_snpeff", "target_idx": 2}
{"id": "mod_gffcompare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare, merge, annotate and estimate accuracy of generated gtf files (tools: gffcompare)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gffcompare": "Compare, merge, annotate and estimate accuracy of generated gtf files", "opt/track": "track aligns query probe sequences to any target transcriptome", "xeniumranger/rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "busco/generateplot": "BUSCO plot generation tool", "ribotricer/prepareorfs": "Accurate detection of short and long active ORFs using Ribo-seq data"}}, "target": "gffcompare", "target_idx": 0}
{"id": "mod_rastair_methylkit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parses rastair call output and converts it into a MethylKit-compatible format. (tools: rastair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_hisat2": "Align reads to a reference genome using hisat2 then sort with samtools", "bismark_align": "Performs alignment of BS-Seq reads using bismark", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "rastair_methylkit": "Parses rastair call output and converts it into a MethylKit-compatible format.", "raw2ometiff": "write your description here"}}, "target": "rastair_methylkit", "target_idx": 3}
{"id": "mod_purgedups_splitfa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split fasta file by 'N's to aid in self alignment for duplicate purging (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fmhfunprofiler": null, "purgedups_splitfa": null, "quast": null, "bedtools_split": null, "atlas_splitmerge": null}}, "target": "purgedups_splitfa", "target_idx": 1}
{"id": "mod_varscan_somatic_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, and copy number variations in both somatic and germline samples. It is particularly useful for analyzing tumor/normal sample pairs. (tools: varscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_stats_mirna_mirtop": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 ", "varscan_somatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "strobealign": "Align short reads using dynamic seed size with strobemers", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "bcftools_consensus": "Compresses VCF files"}}, "target": "varscan_somatic", "target_idx": 1}
{"id": "resource_bracken_bracken_2", "category": "resource_profiling", "state": {"process": "BRACKEN_BRACKEN", "tool": "bracken/bracken", "description": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BRACKEN (Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_metaboigniter_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metaboigniter", "assay": "metaboigniter pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/metaboigniter (Pre-processing of mass spectrometry-based metabolomics data )?", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "patient,vcf,tbi,dataset,tumour_sample": null, "sample,type,level,msfile": null}}, "target": "sample,type,level,msfile", "target_idx": 3}
{"id": "field_constraint_status_1_8", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "format: file-path": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_meryl_histogram_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A genomic k-mer counter (and sequence utility) with nice features. (tools: meryl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"localcdsearch/download": "A command-line tool for downloading databases for local protein domain annotation using NCBI's Conserved Domai", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "meryl/histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "ganon/report": "Generate a ganon report file from the output of ganon classify", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D"}}, "target": "meryl/histogram", "target_idx": 2}
{"id": "field_constraint_status_3_2", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "format: file-path": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_custom_matrixfilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: filter a matrix based on a minimum value and numbers of samples that must pass. (tools: matrixfilter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqsero2": "Salmonella serotype prediction from reads and assemblies", "truvari/segment": "Normalization of SVs into disjointed genomic regions", "deeptools/plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "custom/matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass.", "deeptools/computematrix": "calculates scores per genome regions for other deeptools plotting utilities"}}, "target": "custom/matrixfilter", "target_idx": 3}
{"id": "mod_infernal_cmsearch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search covariance models against a sequence database (tools: infernal)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"infernal_cmsearch": "Search covariance models against a sequence database", "ribodetector": "Accurate and rapid RiboRNA sequences Detector based on deep learning", "barrnap": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files", "affy_justrma": "Read CEL files into an ExpressionSet and generate a matrix", "numorph_intensity": "performs shading correction and intensity normalization between tile stacks"}}, "target": "infernal_cmsearch", "target_idx": 0}
{"id": "schema_std_rnasplice_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnasplice. Description: rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnasplice.", "criteria": {"sample,fastq_1,fastq_2,strandedness,condition": null, "sample,fastq_1,fastq_2,barcode_details": null, "id,test_vcf,test_regions,caller,subsample": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,fastq_1,fastq_2,strandedness,condition", "target_idx": 0}
{"id": "resource_bigscape_bigscape_4", "category": "resource_profiling", "state": {"process": "BIGSCAPE_BIGSCAPE", "tool": "bigscape/bigscape", "description": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSCAPE_BIGSCAPE (BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clust) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_samtools_splitheader_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract header lines from a SAM/BAM/CRAM file into separate files depending on type (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_view": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF", "samtools_convert": "convert and then index CRAM -> BAM or BAM -> CRAM file", "samtools_splitheader": "Extract header lines from a SAM/BAM/CRAM file into separate files depending on type", "nanomonsv_get": "Call somatic structural variants with nanomonsv get using tumor/control\nparse outputs and a reference genome.", "hapibd": "The hap-ibd program detects identity-by-descent (IBD) segments and homozygosity-by-descent (HBD) segments in p"}}, "target": "samtools_splitheader", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_0_0", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,cram": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "mod_entrezdirect_esummary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries an NCBI database using Unique Identifier(s) (tools: entrezdirect)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paftools_sam2paf": null, "fcs_fcsgx": null, "goat_taxonsearch": null, "entrezdirect_esummary": null, "proteus_readproteingroups": null}}, "target": "entrezdirect_esummary", "target_idx": 3}
{"id": "mod_affy_justrma_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read CEL files into an ExpressionSet and generate a matrix (tools: affy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"localcdsearch_download": null, "affy_justrma": null, "oarfish_readmode": null, "propr_propd": null, "rsem_calculateexpression": null}}, "target": "affy_justrma", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_47", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_3", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_1", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/dualrnaseq", "assay_type": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "data_format": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen?", "criteria": {"sample,fastq_1": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "pipe_all101_hgtseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline to investigate horizontal gene transfer from NGS data. Topics: bwa-mem, bwa-mem2, fastqc, genomics-visualization, ggbio, horizontal-gene-transfer. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralintegration": null, "ampliseq": null, "hgtseq": null, "sarek": null, "metapep": null, "taxprofiler": null, "stableexpression": null, "lsmquant": null, "seqsubmit": null, "airrflow": null}}, "target": "hgtseq", "target_idx": 2}
{"id": "mod_ssuissero_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotype prediction of Streptococcus suis assemblies (tools: ssuissero)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromograph": null, "amrfinderplus/run": null, "abricate/summary": null, "localcdsearch/download": null, "ssuissero": null}}, "target": "ssuissero", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_0_21", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "field_constraint_bai_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: 16S rRNA / ITS microbiome amplicon profiling)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 16S rRNA / ITS microbiome amplicon profiling with entry step FASTQC.", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_4", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_mmseqs_contig_taxonomy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assign taxonomy to contigs using the MMseqs2 workflow. (tools: mmseqs_contig_taxonomy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_sort_stats_samtools": null, "bracken/combinebrackenoutputs": null, "skani/triangle": null, "mmseqs_contig_taxonomy": null, "bracken/bracken": null}}, "target": "mmseqs_contig_taxonomy", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_45", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "schema_std_chipseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/chipseq", "description": "ChIP-seq peak-calling, QC and differential analysis pipeline.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/chipseq?", "criteria": {"sample,vcf,tbi": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,fastq_1,fastq_2,library_id,lane": null, "sample,fastq_1,fastq_2,replicate,antibody": null}}, "target": "sample,fastq_1,fastq_2,replicate,antibody", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_2_0", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 2}
{"id": "schema_std_readsimulator_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/readsimulator. Description: A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/readsimulator.", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "sample,fastq_1,fastq_2,group": null, "sample,seed": null, "sample,group,path,ref,method": null}}, "target": "sample,seed", "target_idx": 2}
{"id": "resource_ariba_run_5", "category": "resource_profiling", "state": {"process": "ARIBA_RUN", "tool": "ariba/run", "description": "Query input FASTQs against Ariba formatted databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_RUN (Query input FASTQs against Ariba formatted databases) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gedi_price_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm (tools: gedi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gedi_price": null, "plastid_psite": null, "plastid_metagenegenerate": null, "scimap_mcmicro": null, "iqtree": null}}, "target": "gedi_price", "target_idx": 0}
{"id": "mod_simpleaf_quant_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: simpleaf is a program to simplify and customize the running and configuration of single-cell processing with alevin-fry. (tools: simpleaf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcquant": null, "simpleaf_quant": null, "fastq_trim_fastp_fastqc": null, "oarfish_alignmentmode": null, "fasta_build_add_kraken2": null}}, "target": "simpleaf_quant", "target_idx": 1}
{"id": "mod_genmap_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: create index file for genmap (tools: genmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmap_index": "create index file for genmap", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "bcftools_index": "Index VCF tools", "openms_idscoreswitcher": "Switches between different scores of peptide or protein hits in identification data"}}, "target": "genmap_index", "target_idx": 0}
{"id": "mod_krona_ktimportkrona_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect multiple krona reports into a single html file (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"drep_compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "malt_run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "krona_ktimportkrona": "Collect multiple krona reports into a single html file", "blobtk_plot": "Creates differing styles of blobplots depending on provided arguments.", "deeptools_plotfingerprint": "plots cumulative reads coverages by BAM file"}}, "target": "krona_ktimportkrona", "target_idx": 2}
{"id": "mod_gatk4_revertsam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reverts SAM or BAM files to a previous state. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscreen_buildfromindex": "Build fastq screen config file from bowtie index files", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4_revertsam": "Reverts SAM or BAM files to a previous state.", "fastq_download_prefetch_fasterqdump_sratools": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA).", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables"}}, "target": "gatk4_revertsam", "target_idx": 2}
{"id": "resource_biscuit_align_4", "category": "resource_profiling", "state": {"process": "BISCUIT_ALIGN", "tool": "biscuit/align", "description": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_ALIGN (Aligns single- or paired-end reads from bisulfite-converted libraries to a refer) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_3_0", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_biobambam_bammerge_0", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMERGE", "tool": "biobambam/bammerge", "description": "Merge a list of sorted bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMERGE (Merge a list of sorted bam files) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_0_3", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,image": null, "sample,bam": null, "sample,fastq_1,fastq_2,image,slide,area": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 3}
{"id": "pipe_all101_proteinannotator_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Generation of sequence-level annotations for amino acid sequences. Topics: annotation, proteomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bamtofastq": null, "nanostring": null, "proteinfamilies": null, "taxprofiler": null, "metatdenovo": null, "funcscan": null, "phyloplace": null, "proteinannotator": null}}, "target": "proteinannotator", "target_idx": 7}
{"id": "mod_find_unpigz_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module for decompressing a large number of gzipped files, getting around the UNIX terminal argument limit (tools: find)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect/xtract": "Queries an NCBI database using an UID", "cat/cat": "A module for concatenation of gzipped or uncompressed files", "custom/tabulartogseachip": "Make a GSEA class file (.chip) from tabular inputs", "find/unpigz": "A module for decompressing a large number of gzipped files, getting around the UNIX terminal argument limit", "crabz/compress": "Compress files with crabz"}}, "target": "find/unpigz", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_1_2", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "schema_std_sopa_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sopa", "assay": "sopa pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/sopa (Nextflow version of Sopa - spatial omics pipeline and analys)?", "criteria": {"sample,id,data_path,fastq_dir,cytaimage": null, "sample_id,bam,vcf,library_id,lane": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,id,data_path,fastq_dir,cytaimage", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_5_5", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Visium spatial transcriptomics with histology image.", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "pipe_all101_demo_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos.. Topics: demo, minimal-example, training, tutorial. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]"}}, "target": "demo", "target_idx": 3}
{"id": "mod_octopusv_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot structural variant statistics using octopusv stat output (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqwish_induce": "Induce a variation graph in GFA format from alignments in PAF format", "octopusv_plot": "Plot structural variant statistics using octopusv stat output", "crabz_decompress": "Decompress files with crabz", "bismark_summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "custom_collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op"}}, "target": "octopusv_plot", "target_idx": 1}
{"id": "mod_quilt_quilt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: QUILT is an R and C++ program for rapid genotype imputation from low-coverage sequence using a large reference panel. (tools: quilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode_ribocode": "Call ORFs with RiboCode from Ribo-Seq data", "glimpse_ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information.", "quilt_quilt": "QUILT is an R and C++ program for rapid genotype imputation from low-coverage sequence using a large reference", "gappa_examinegraft": "Grafts query sequences from phylogenetic placement on the reference tree", "glimpse_chunk": "Defines chunks where to run imputation"}}, "target": "quilt_quilt", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_47", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_presto_filterseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter reads by quality score. (tools: presto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastx/collapser": "Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts)", "presto/filterseq": "Filter reads by quality score.", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "roary": "Calculate pan-genome from annotated bacterial assemblies in GFF3 format", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "presto/filterseq", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_5_2", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery", "pipeline": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnafusion, determine the input samplesheet column structure for: RNA gene fusion detection (Arriba, STAR-Fusion).", "criteria": {"sample,fusion_bed": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "resource_bamtools_split_1", "category": "resource_profiling", "state": {"process": "BAMTOOLS_SPLIT", "tool": "bamtools/split", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_SPLIT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_pairgenomealign_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pairgenomealign", "description": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pairgenomealign?", "criteria": {"id,test_vcf,test_regions,caller,subsample": null, "sample,fasta": null, "sample,fasta,protein,gbk,gff": null, "sample,id,data_path,fastq_dir,cytaimage": null}}, "target": "sample,fasta", "target_idx": 1}
{"id": "resource_ampcombi2_parsetables_5", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_PARSETABLES", "tool": "ampcombi2/parsetables", "description": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_PARSETABLES (A submodule that parses and standardizes the results from various antimicrobial ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_4_1", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs?", "criteria": {"sample,otu_table": null, "sample,fasta": null, "sample,primer_fwd,primer_rev": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_canvas_germline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPedigree-WGS mode. Although named SmallPedigree-WGS, this\nmode is recommended for single germline samples as well as small pedigrees.\nThe module accepts aligned reads (BAM), germline SNV calls, and sex-specific ploidy\ninformation, and outputs a VCF with copy number status across the genome together\nwith a coverage-and-variant-frequency file used for downstream segmentation. (tools: canvas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions.", "canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "cellrangeratac_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkfastq com", "samtools_markdup": "mark duplicate alignments in a coordinate sorted file", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples)."}}, "target": "canvas_germline", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_49", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_samtools_quickcheck_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly check that input files appear to be intact. Checks that beginning of the file contains a valid header (all formats) containing at least one target sequence and then seeks to the end of the file and checks that an end-of-file (EOF) is present and intact (BAM and CRAM only). Alignment records are not checked. The quickcheck module returns a non-zero EXIT_CODE if any input files don't have a valid header or are missing an EOF block. Otherwise EXIT_CODE is zero. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stacks/refmap": "ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available.", "fusionreport/download": "Build DB for fusionreport", "seqfu/check": "Evaluates the integrity of DNA FASTQ files", "samtools/quickcheck": "Quickly check that input files appear to be intact. Checks that beginning of the file contains a valid header ", "bioawk": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats."}}, "target": "samtools/quickcheck", "target_idx": 3}
{"id": "field_constraint_sample_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "format: file-path": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "resource_agat_spextractsequences_2", "category": "resource_profiling", "state": {"process": "AGAT_SPEXTRACTSEQUENCES", "tool": "agat/spextractsequences", "description": "This script extracts sequences in fasta format according to features described\nin a gff file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPEXTRACTSEQUENCES (This script extracts sequences in fasta format according to features described\ni) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_1_32", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_atlasgeneannotationmanipulation_gtf2featureannotation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate tables of feature metadata from GTF files (tools: atlasgeneannotationmanipulation)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "vcf_phase_shapeit5": "Subworkflow to phase a reference panel VCF file using SHAPEIT5.\nThe panel is first chunked by chromosome by gl", "odgi_stats": "Metrics describing a variation graph and its path relationship.", "agat_spaddintrons": "Add intron features to gtf/gff file without intron features."}}, "target": "atlasgeneannotationmanipulation_gtf2featureannotation", "target_idx": 0}
{"id": "mod_blast_blastp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast/blastp": null, "repeatmodeler/repeatmodeler": null, "bamtools/stats": null, "abritamr/run": null, "amrfinderplus/update": null}}, "target": "blast/blastp", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_48", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_gunc_mergecheckm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merging of CheckM and GUNC results in one summary table (tools: gunc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwameth_index": null, "checkm_lineagewf": null, "pairtools_dedup": null, "gunc_mergecheckm": null, "checkm_qa": null}}, "target": "gunc_mergecheckm", "target_idx": 3}
{"id": "mod_hmmer_eslsfetchindex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel miniapp bundled with the HMMER\npackage (esl-sfetch --index). The resulting index lets esl-sfetch\nretrieve sequences from the file in constant time. This module is the\nindexing half of a pair: hmmer/eslsfetchindex builds the SSI index,\nhmmer/eslsfetch consumes it (or an equivalent one) to fetch sequences\nor subsequences. (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie", "hmmer/eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi", "fastk/histex": "A fast K-mer counter for high-fidelity shotgun datasets", "hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment", "pcne": "Estimates plasmid copy number from assembled genome"}}, "target": "hmmer/eslsfetchindex", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_bamcmp_bwa_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BAMCMP_BWA", "modules": ["bamcmp", "bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better to the first genome, then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BAMCMP_BWA (bamcmp, bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_BAMCMP_BWA": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_bamcmp_bwa": null}}, "target": "Use nf-core subworkflow fastq_align_bamcmp_bwa", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_extract_kraken_krakentools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS", "modules": ["kraken2/kraken2", "krakentools/extractkrakenreads"], "description": "Extract classified Kraken2 reads by taxonomic id"}, "question": {"type": "choice", "instructions": "How should FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS (kraken2/kraken2, krakentools/extractkrakenreads) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_extract_kraken_krakentools": null, "Leave them out": null, "Local subworkflow FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_extract_kraken_krakentools", "target_idx": 0}
{"id": "core_tool_fastqc_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Quality control metric evaluation including per-base sequence quality scores, GC content distributions, and k-mer overrepresentation for raw FASTQ data.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"nanoplot": null, "fastqc": null, "qualimap": null, "falco": null, "multiqc": null}}, "target": "fastqc", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_2_5", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fasta": null, "sample,raw_file,condition": null, "sample,mzml": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "mod_shinyngs_app_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: build and deploy Shiny apps for interactively mining differential abundance data (tools: shinyngs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"limma_differential": null, "propr_propd": null, "shinyngs_app": null, "eklipse": null, "hmmer_hmmlogo": null}}, "target": "shinyngs_app", "target_idx": 2}
{"id": "mod_sequenzautils_bam2seqz_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sequenza-utils bam2seqz process BAM and Wiggle files to produce a seqz file (tools: sequenzautils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequenzautils/bam2seqz": "Sequenza-utils bam2seqz process BAM and Wiggle files to produce a seqz file", "cnvkit/access": "Calculate the sequence-accessible coordinates in chromosomes from the given reference genome, output as a BED ", "wittyer": "A large variant benchmarking tool analogous to hap.py for small variants.", "transdecoder/predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "ascat": "copy number profiles of tumour cells."}}, "target": "sequenzautils/bam2seqz", "target_idx": 0}
{"id": "resource_adapterremovalfixprefix_2", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVALFIXPREFIX", "tool": "adapterremovalfixprefix", "description": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with DeDup."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVALFIXPREFIX (Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names a) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_6_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_octopusv_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge and harmonize structural variant calls from multiple samples. (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"octopusv_merge": "Merge and harmonize structural variant calls from multiple samples.", "rtgtools_cnveval": "The cnveval tool of RTG tools. It is used to evaluate called CNV regions for agreement with a baseline CNV set", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "caddsv_run": "Score structural variants with CADD-SV."}}, "target": "octopusv_merge", "target_idx": 0}
{"id": "resource_agat_spstatistics_5", "category": "resource_profiling", "state": {"process": "AGAT_SPSTATISTICS", "tool": "agat/spstatistics", "description": "Provides different type of statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPSTATISTICS (Provides different type of statistics in text format from a GFF/GTF annotation f) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_biscuit_vcf2bed_1", "category": "resource_profiling", "state": {"process": "BISCUIT_VCF2BED", "tool": "biscuit/vcf2bed", "description": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_VCF2BED (Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compl) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_drep_dereplicate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome (tools: drep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "msisensorpro_msisomatic": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "drep_dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome", "openms_idscoreswitcher": "Switches between different scores of peptide or protein hits in identification data"}}, "target": "drep_dereplicate", "target_idx": 3}
{"id": "mod_upd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simple software to call UPD regions from germline exome/wgs trios. (tools: upd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngsbits_updhunter": "UPD detection from trio variant data.", "proovframe_map": "frame-shift correction for long read (meta)genomics - maps proteins to reads", "upd": "Simple software to call UPD regions from germline exome/wgs trios.", "stecfinder": "Serotype STEC samples from paired-end reads or assemblies", "ssuissero": "Serotype prediction of Streptococcus suis assemblies"}}, "target": "upd", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_1_2", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "resource_atlas_call_2", "category": "resource_profiling", "state": {"process": "ATLAS_CALL", "tool": "atlas/call", "description": "generate VCF file from a BAM file using various calling methods"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_CALL (generate VCF file from a BAM file using various calling methods) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_ucsc_bedclip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove lines from bed file that refer to off-chromosome locations. (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_collectreadcounts": null, "vardictjava": null, "bedops_convert2bed": null, "annotsv_annotsv": null, "ucsc_bedclip": null}}, "target": "ucsc_bedclip", "target_idx": 4}
{"id": "mod_csvtk_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits CSV/TSV into multiple files according to column values (tools: csvtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"narfmap/hashtable": "Create DRAGEN hashtable for reference genome", "dshbio/filterbed": "Filter features in gzipped BED format", "bcftools/pluginsplit": "Split VCF by sample, creating single- or multi-sample VCFs.", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "csvtk/split": "Splits CSV/TSV into multiple files according to column values"}}, "target": "csvtk/split", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wes_pe_4_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from Agilent/Twist exome target capture?", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_17", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_gatk4_printreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Print reads in the SAM/BAM/CRAM file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "gatk4/filterintervals": "Filters intervals based on annotations and/or count statistics.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "gatk4/printreads": "Print reads in the SAM/BAM/CRAM file"}}, "target": "gatk4/printreads", "target_idx": 4}
{"id": "samplesheet_arch_bulk_small_rna_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/smrnaseq", "assay_type": "Small RNA / miRNA sequencing", "data_format": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Small RNA / miRNA sequencing with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "noul_undeclared_process_file_inputs_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_samtools_fasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a SAM/BAM/CRAM file to FASTA (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_fasta": "Converts a SAM/BAM/CRAM file to FASTA", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "bwa_index": "Create BWA index for reference genome", "bamclipper": "This module is used to clip primer sequences from your alignments.", "porechop_porechop": "Adapter removal and demultiplexing of Oxford Nanopore reads"}}, "target": "samtools_fasta", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_3", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_all101_diaproteomics_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Automated quantitative analysis of DIA proteomics mass spectrometry measurements.. Topics: data-independent-proteomics, dia-proteomics, openms, proteomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": null, "seqsubmit": null, "mag": null, "isoseq": null, "mhcquant": null, "pangenome": null, "crisprseq": null, "diaproteomics": null, "atacseq": null, "multiplesequencealign": null}}, "target": "diaproteomics", "target_idx": 7}
{"id": "mod_mirtop_export_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package (tools: mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop_stats": "mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category.", "rseqc_innerdistance": "Calculate inner distance between read pairs.", "bam_markduplicates_picard": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats", "mirdeep2_mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs.", "mirtop_export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package"}}, "target": "mirtop_export", "target_idx": 4}
{"id": "schema_std_alleleexpression_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/alleleexpression. Description: Alleleexpression is a nf-core pipeline for allele-specific expression (ASE) analysis using STAR-WASP for alignment, UMI-tools for deduplication, and phaser for haplotype phasing and ASE detection..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/alleleexpression.", "criteria": {"sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2,replicate,control": null, "sample,fastq_1,fastq_2,vcf": null, "fastq_1,fastq_2,group,replicate,control": null}}, "target": "sample,fastq_1,fastq_2,vcf", "target_idx": 2}
{"id": "intent_build_pipeline_11", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "build_pipeline": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "resource_bwafastalign_index_3", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_INDEX", "tool": "bwafastalign/index", "description": "Create BWA-FASTALIGN index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_INDEX (Create BWA-FASTALIGN index for reference genome) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_high", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_6_5", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/genomeassembler --input samplesheet.csv (Assay: Long-read Pacific Biosciences HiFi sequencing)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_regenie_step1_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi", "regenie/splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "regenie/step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions", "seacr/callpeak": "Call peaks using SEACR on sequenced reads in bedgraph format"}}, "target": "regenie/step1", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_36", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_sentieon_coveragemetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accelerated implementation of the GATK DepthOfCoverage tool. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cmseq/polymut": null, "pmdtools/filter": null, "cnvpytor/histogram": null, "sentieon/coveragemetrics": null, "bbmap/pileup": null}}, "target": "sentieon/coveragemetrics", "target_idx": 3}
{"id": "field_constraint_strandedness_0_11", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "subworkflow_pkg_mmseqs_fasta_cluster_2", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_FASTA_CLUSTER", "modules": ["mmseqs/createdb", "mmseqs/cluster", "mmseqs/linclust", "mmseqs/createtsv"], "description": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file."}, "question": {"type": "choice", "instructions": "How should MMSEQS_FASTA_CLUSTER (mmseqs/createdb, mmseqs/cluster, mmseqs/linclust, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Local subworkflow MMSEQS_FASTA_CLUSTER": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow mmseqs_fasta_cluster": null}}, "target": "Use nf-core subworkflow mmseqs_fasta_cluster", "target_idx": 3}
{"id": "core_tool_gatk_haplotypecaller_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Germline SNP and Indel variant calling via local de novo haplotype assembly across active genomic regions.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"deepvariant": null, "gatk_haplotypecaller": null, "strelka2": null, "freebayes": null, "mutect2": null}}, "target": "gatk_haplotypecaller", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_5_2", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Downstream functional annotation of pre-called VCF files.", "criteria": {"sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic cancer variant calling with tumor-normal pairs", "data_format": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic cancer variant calling with tumor-normal pairs with entry step BWA_MEM.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_fastq_2_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "mod_gatk4_calculatecontamination_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummaries. Output to be used with filtermutectcalls. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/blastx": "Queries a DIAMOND database using blastx mode", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4/calculatecontamination": "Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummari", "antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables"}}, "target": "gatk4/calculatecontamination", "target_idx": 2}
{"id": "pipe_all101_sopa_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Nextflow version of Sopa - spatial omics pipeline and analysis. Topics: segmentation, spatial-omics, spatial-proteomics, spatial-transcriptomics, spatialdata. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"references": null, "pairgenomealign": null, "multiplesequencealign": null, "genomeassembler": null, "methylseq": null, "sopa": null, "proteinannotator": null, "callingcards": null}}, "target": "sopa", "target_idx": 5}
{"id": "qc_adapt_pe_illumina_fastqc_0_37", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "field_constraint_phenotype_0_4", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "resource_bedtools_shift_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHIFT", "tool": "bedtools/shift", "description": "Shifts each feature by specific number of bases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHIFT (Shifts each feature by specific number of bases) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_epigenomics_hic_5_4", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/hic, determine the input samplesheet column structure for: Hi-C chromosome conformation capture mapping.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_seqtk_subseq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select only sequences that match the filtering condition (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqtk_subseq": null, "fastq_trim_fastp_fastqc": null, "hifiadapterfilt_hifiadapterfilt": null, "ngsbits_updhunter": null, "filtlong": null}}, "target": "seqtk_subseq", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Metagenomic MAG assembly with comparative groups)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "mod_samtools_fixmate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Samtools fixmate is a tool that can fill in information (insert size, cigar, mapq) about paired end reads onto the corresponding other read. Also has options to remove secondary/unmapped alignments and recalculate whether reads are proper pairs. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rustqc": "All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, an", "samtools_fixmate": "Samtools fixmate is a tool that can fill in information (insert size, cigar, mapq) about paired end reads onto", "genmap_map": "create mappability files for a genome", "samtools_bedcov": "reports coverage over regions in a supplied BED file", "bwamem2_index": "Create BWA-mem2 index for reference genome"}}, "target": "samtools_fixmate", "target_idx": 1}
{"id": "mod_poolsnp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PoolSNP is a heuristic SNP caller, which uses an MPILEUP file and a reference genome in FASTA format as inputs. (tools: poolsnp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequencetools_pileupcaller": null, "sushie": null, "stacks_refmap": null, "poolsnp": null, "shinyngs_staticexploratory": null}}, "target": "poolsnp", "target_idx": 3}
{"id": "resource_agat_spfilterbyorfsize_1", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERBYORFSIZE", "tool": "agat/spfilterbyorfsize", "description": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF passing the test, the other contains the rest. By default the test is \"> 100\" that means all gene models that have ORF longer than 100 Amino acids, will pass the test."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERBYORFSIZE (The script reads a gff annotation file, and create two output files, one contain) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_glimpse2_ligate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks that are ligated into chromosome-wide files maintaining the phasing. (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_impute_glimpse": null, "fargene": null, "fgbio_collectduplexseqmetrics": null, "shapeit5_ligate": null, "glimpse2_ligate": null}}, "target": "glimpse2_ligate", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_5_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_kallisto_quant_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes equivalence classes for reads and quantifies abundances (tools: kallisto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kallistobustools_ref": null, "kallisto_quant": null, "kallisto_index": null, "autocycler_resolve": null, "hifitrimmer_processblast": null}}, "target": "kallisto_quant", "target_idx": 1}
{"id": "mod_bcftools_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index VCF tools (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/index": "Index VCF tools", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome", "bcftools/annotate": "Add or remove annotations.", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "bcftools/index", "target_idx": 0}
{"id": "noul_channel_filter_operator_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_6_5", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns are standard for Downstream functional annotation of pre-called VCF files input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,bed": null, "sample,vcf,tbi": null}}, "target": "sample,vcf,tbi", "target_idx": 3}
{"id": "resource_biobambam_bamsormadup_4", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMSORMADUP", "tool": "biobambam/bamsormadup", "description": "Parallel sorting and duplicate marking"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMSORMADUP (Parallel sorting and duplicate marking) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for POSITIONSOFINT (custom/positionsofint).", "criteria": {"Use nf-core subworkflow positionsofint": null, "Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 1}
{"id": "intent_build_pipeline_6", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "build_pipeline", "target_idx": 3}
{"id": "mod_strdust_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tandem repeat genotyper for long reads (tools: STRdust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strdust": "Tandem repeat genotyper for long reads", "trtools/mergestr": "MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file.", "trtools/dumpstr": "DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a fi", "fastani": "Alignment-free computation of Average Nucleotide Identity (ANI)", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity"}}, "target": "strdust", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_4_4", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted CRAM alignments with companion CRAI indexes?", "criteria": {"sample,bam,bai": null, "sample,cram,crai": null, "sample,cram": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_4_3", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end tiled viral amplicon FASTQs per clinical swab sample?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/hic --input samplesheet.csv (Assay: Hi-C chromosome conformation capture mapping)", "question": {"type": "choice", "instructions": "Which columns are standard for Hi-C chromosome conformation capture mapping input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_gather_bcftools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_GATHER_BCFTOOLS", "modules": ["bcftools/sort", "bcftools/concat", "htslib/bgziptabix"], "description": "Concatenate several VCF files using bcftools concat."}, "question": {"type": "choice", "instructions": "How should VCF_GATHER_BCFTOOLS (bcftools/sort, bcftools/concat, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_gather_bcftools": null, "Leave them out": null, "Local subworkflow VCF_GATHER_BCFTOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_gather_bcftools", "target_idx": 0}
{"id": "mod_fgumi_zipper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Zip an unmapped UMI BAM together with its aligned BAM using fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi", "fgumi_zipper": "Zip an unmapped UMI BAM together with its aligned BAM using fgumi", "merqury_hapmers": "A script to generate hap-mer dbs for trios", "fgbio_callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag.", "ragtag_patch": "Homology-based assembly patching: Make continuous joins and fill gaps in 'target.fa' using sequences from 'que"}}, "target": "fgumi_zipper", "target_idx": 1}
{"id": "noul_executor_support_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_fastme_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Distance-based phylogeny with FastME (tools: fastme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon_indexdiff": "Subtract minimizers in deacon index (or fasta file) from another index (A - B)", "genescopefk": "A derivative of GenomeScope2.0 modified to work with FastK", "fastme": "Distance-based phylogeny with FastME", "virusrecom": "Information-theory-based method for recombination detection of viral lineages using weighted information conte", "iqtree": "Produces a Newick format phylogeny from a multiple sequence alignment using the maximum likelihood algorithm. "}}, "target": "fastme", "target_idx": 2}
{"id": "mod_diann_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary analysis, empirical library assembly, individual analysis, and final quantification (tools: diann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/cluster": null, "freyja/variants": null, "diamond/deepclust": null, "bcftools/reheader": null, "diann": null}}, "target": "diann", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_2_20", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "local_subworkflow_preparereports_2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPAREREPORTS (custom/preparereports, multiqc).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow preparereports": null, "Local subworkflow PREPAREREPORTS": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_0_1", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,fastq_1": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 2}
{"id": "mod_staphopiasccmec_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts Staphylococcus aureus SCCmec type based on primers. (tools: staphopiasccmec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification.", "bbmap/pileup": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file.", "hamronization/fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "gatk/realignertargetcreator": "Generates a list of locations that should be considered for local realignment prior genotyping.", "staphopiasccmec": "Predicts Staphylococcus aureus SCCmec type based on primers."}}, "target": "staphopiasccmec", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_0_17", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_36", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_finaletoolkit_mds_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Comnpute the Motif Diversity Score using normalized Shannon entropy\n(Jiang et al., 2020). (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit/mds": null, "coptr/extract": null, "finaletoolkit/endmotifs": null, "backsub": null, "agat/spfilterfeaturefromkilllist": null}}, "target": "finaletoolkit/mds", "target_idx": 0}
{"id": "mod_molkartgarage_clahe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Contrast-limited adjusted histogram equalization (CLAHE) on single-channel tif images. (tools: molkartgarage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"molkartgarage/clahe": "Contrast-limited adjusted histogram equalization (CLAHE) on single-channel tif images.", "custom/orfmerge": "Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `cus", "vcf_annotate_ensemblvep": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file", "bioformats2raw": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible ", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "molkartgarage/clahe", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_taxonomic_profile_metaphlan_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TAXONOMIC_PROFILE_METAPHLAN", "modules": ["metaphlan/makedb", "metaphlan/metaphlan", "metaphlan/mergemetaphlantables"], "description": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn"}, "question": {"type": "choice", "instructions": "How should FASTQ_TAXONOMIC_PROFILE_METAPHLAN (metaphlan/makedb, metaphlan/metaphlan, metaphlan/mergemetaphlantables) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_taxonomic_profile_metaphlan": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_TAXONOMIC_PROFILE_METAPHLAN": null}}, "target": "Use nf-core subworkflow fastq_taxonomic_profile_metaphlan", "target_idx": 0}
{"id": "pipe_all101_viralmetagenome_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for epidemiology. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]"}}, "target": "viralmetagenome", "target_idx": 4}
{"id": "pipe_all101_demo_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos.. Topics: demo, minimal-example, training, tutorial. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training"}}, "target": "demo", "target_idx": 7}
{"id": "schema_std_seqinspector_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/seqinspector", "description": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput. ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/seqinspector?", "criteria": {"sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,seed": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,fastq_2,rundir,tags", "target_idx": 0}
{"id": "mod_bakta_baktadbdownload_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads BAKTA database from Zenodo (tools: bakta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pharokka_pharokka": "Functional annotation of phages", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "svdb_build": "Build a structural variant database", "freyja_variants": "call variant and sequencing depth information of the variant", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "bakta_baktadbdownload", "target_idx": 1}
{"id": "mod_vt_decompose_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: decomposes multiallelic variants into biallelic in a VCF file. (tools: vt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "vt_normalize": "normalizes variants in a VCF file", "glimpse2_concordance": "Program to compute the genotyping error rate at the sample or marker level.", "gatk4_postprocessgermlinecnvcalls": "Postprocesses the output of GermlineCNVCaller and generates VCFs and denoised copy ratios", "vt_decompose": "decomposes multiallelic variants into biallelic in a VCF file."}}, "target": "vt_decompose", "target_idx": 4}
{"id": "resource_biscuit_align_3", "category": "resource_profiling", "state": {"process": "BISCUIT_ALIGN", "tool": "biscuit/align", "description": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_ALIGN (Aligns single- or paired-end reads from bisulfite-converted libraries to a refer) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_coverm_genome_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate read coverage per-genome (tools: coverm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"damageprofiler": "A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage", "coptr/extract": "Computes the coverage map along the reference genome", "dupblaster": "Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline ", "coverm/contig": "Map reads to contigs and estimate coverage", "coverm/genome": "Calculate read coverage per-genome"}}, "target": "coverm/genome", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq with strandedness. Input files: Paired-end FASTQ reads with library strandedness.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_fastq_align_bamcmp_bwa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better to the first genome, then sort with samtools (tools: fastq_align_bamcmp_bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "scanpy/scrublet": "Detect doublets in single-cell RNA-seq data using Scrublet via Scanpy", "fastq_align_bamcmp_bwa": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better", "xeniumranger/importsegmentation": "The xeniumranger importsegmentation module runs `xeniumranger import-segmentation`\nto recompute Xenium Onboard", "atlas/splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "fastq_align_bamcmp_bwa", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_2_5", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "subworkflow_pkg_bed_scatter_bedtools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BED_SCATTER_BEDTOOLS", "modules": ["bedtools/split"], "description": "Scatters inputted BED files by the amount specified."}, "question": {"type": "choice", "instructions": "How should BED_SCATTER_BEDTOOLS (bedtools/split) be structured in DSL2?", "criteria": {"Local subworkflow BED_SCATTER_BEDTOOLS": null, "Use nf-core subworkflow bed_scatter_bedtools": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bed_scatter_bedtools", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_4_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs?", "criteria": {"sample,bam": null, "sample,cpg,methylation": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_13", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "schema_std_drop_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/drop. Description: Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/drop.", "criteria": {"sample,id,data_path,fastq_dir,cytaimage": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,seq_data,pbi,start_from": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE", "target_idx": 1}
{"id": "noul_channel_collect_operator_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_bai_0_6", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_12", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_15", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_salsa2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SALSA, A tool to scaffold long read assemblies with HiC (tools: salsa2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": null, "salsa2": null, "abricate/summary": null, "mm2plus/index": null, "pmdtools/filter": null}}, "target": "salsa2", "target_idx": 1}
{"id": "resource_agat_spextractsequences_1", "category": "resource_profiling", "state": {"process": "AGAT_SPEXTRACTSEQUENCES", "tool": "agat/spextractsequences", "description": "This script extracts sequences in fasta format according to features described\nin a gff file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPEXTRACTSEQUENCES (This script extracts sequences in fasta format according to features described\ni) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_slamseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for differential-expression. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "metapep": "From metagenomes to epitopes and beyond"}}, "target": "slamseq", "target_idx": 2}
{"id": "subworkflow_pkg_bam_docounts_contamination_angsd_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DOCOUNTS_CONTAMINATION_ANGSD", "modules": ["angsd/docounts", "angsd/contamination"], "description": "Calculate contamination of the X-chromosome with ANGSD"}, "question": {"type": "choice", "instructions": "How should BAM_DOCOUNTS_CONTAMINATION_ANGSD (angsd/docounts, angsd/contamination) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_docounts_contamination_angsd": null, "Local subworkflow BAM_DOCOUNTS_CONTAMINATION_ANGSD": null}}, "target": "Use nf-core subworkflow bam_docounts_contamination_angsd", "target_idx": 2}
{"id": "noul_dynamic_resource_allocation_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "local_subworkflow_variantsofint_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should this step (custom/variantsofint) be packaged: Variant filtering and clinical annotation aggregation?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow variantsofint": null, "Local subworkflow VARIANTSOFINT": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 3}
{"id": "mod_rtgtools_vcfeval_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The VCFeval tool of RTG tools. It is used to evaluate called variants for agreement with a baseline variant set (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rtgtools_bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "controlfreec_freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "holodeck_methylate": "Generate a methylation-annotated VCF from a reference genome with holodeck", "gatk4_sitedepthtobaf": "EXPERIMENTAL TOOL! Convert SiteDepth to BafEvidence", "rtgtools_vcfeval": "The VCFeval tool of RTG tools. It is used to evaluate called variants for agreement with a baseline variant se"}}, "target": "rtgtools_vcfeval", "target_idx": 4}
{"id": "mod_snpeff_snpeff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genetic variant annotation and functional effect prediction toolbox (tools: snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariateremlldms": null, "gubbins": null, "snpeff_snpeff": null, "agat_spflagshortintrons": null, "agat_spfilterbyorfsize": null}}, "target": "snpeff_snpeff", "target_idx": 2}
{"id": "noul_modular_subworkflow_composition_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_mmseqs_createtsv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a tsv file from a query and a target database as well as the result database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_createtsv": "Create a tsv file from a query and a target database as well as the result database", "custom_orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "mmseqs_easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2", "malt_run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h"}}, "target": "mmseqs_createtsv", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_18", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_5_4", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/bacass, determine the input samplesheet column structure for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads.", "criteria": {"sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_2_5", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "subworkflow_pkg_mmseqs_contig_taxonomy_3", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_CONTIG_TAXONOMY", "modules": ["mmseqs/databases", "mmseqs/createdb", "mmseqs/taxonomy", "mmseqs/createtsv"], "description": "Assign taxonomy to contigs using the MMseqs2 workflow."}, "question": {"type": "choice", "instructions": "How should MMSEQS_CONTIG_TAXONOMY (mmseqs/databases, mmseqs/createdb, mmseqs/taxonomy, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Use nf-core subworkflow mmseqs_contig_taxonomy": null, "Leave them out": null, "Local subworkflow MMSEQS_CONTIG_TAXONOMY": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow mmseqs_contig_taxonomy", "target_idx": 0}
{"id": "schema_std_epitopeprediction_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/epitopeprediction", "assay": "epitopeprediction pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/epitopeprediction (A bioinformatics best-practice analysis pipeline for epitope)?", "criteria": {"id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,alleles,mhc_class,filename": null, "sample,tools,file,index": null}}, "target": "sample,alleles,mhc_class,filename", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Visium spatial transcriptomics with histology image. Input files: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic cancer variant calling with tumor-normal pairs", "data_format": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_mcmicro_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data.. Topics: bioformats, image-analysis, image-processing, microscopy, multiplexed-imaging, ome-tiff. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnasplice": null, "mcmicro": null, "scrnaseq": null, "cutandrun": null, "reportho": null}}, "target": "mcmicro", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_vclust_prefilter_align_cluster_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER", "modules": ["vclust/prefilter", "vclust/align", "vclust/cluster"], "description": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter"}, "question": {"type": "choice", "instructions": "How should FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER (vclust/prefilter, vclust/align, vclust/cluster) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster": null, "Local subworkflow FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_41", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wes_pe_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Paired-end Whole Exome Sequencing (WES) target capture", "data_format": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_32", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "pipe_all101_ribomsqc_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for ribomsqc analysis? Specific context: QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]"}}, "target": "ribomsqc", "target_idx": 2}
{"id": "mod_salsa2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SALSA, A tool to scaffold long read assemblies with HiC (tools: salsa2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "abacas": "Contiguate draft genome assembly", "holodeck_eval": "Evaluate alignment accuracy of holodeck-simulated reads", "salsa2": "SALSA, A tool to scaffold long read assemblies with HiC", "leviosam2_lift": "Converting aligned short and long reads records from one reference to another"}}, "target": "salsa2", "target_idx": 3}
{"id": "mod_fastq_align_bwaaln_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed BAM files (tools: fastq_align_bwaaln)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_view": "filter/convert SAM/BAM/CRAM file", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "fastq_align_bwaaln": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed ", "concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign."}}, "target": "fastq_align_bwaaln", "target_idx": 2}
{"id": "local_subworkflow_daisribosome_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should DAISRIBOSOME (dais) be built?", "criteria": {"Use nf-core subworkflow daisribosome": null, "Keep the modules in the main workflow": null, "Local subworkflow DAISRIBOSOME": null, "Leave them out": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_1_4", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_localcdsearch_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A command-line tool for local protein domain annotation using NCBI's Conserved Domain Database (CDD) (tools: localcdsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"localcdsearch/annotate": null, "oarfish/readmode": null, "localcdsearch/download": null, "checkv/downloaddatabase": null, "blast/blastp": null}}, "target": "localcdsearch/annotate", "target_idx": 0}
{"id": "subworkflow_pkg_bam_impute_quilt_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_QUILT", "modules": ["gawk", "quilt/quilt", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using QUILT software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_QUILT (gawk, quilt/quilt, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Local subworkflow BAM_IMPUTE_QUILT": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_impute_quilt": null}}, "target": "Use nf-core subworkflow bam_impute_quilt", "target_idx": 3}
{"id": "mod_spaceranger_mkgtf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build a filtered GTF needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkgtf command. (tools: spaceranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie_build": "Create bowtie index for reference genome", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "ltrharvest": "Predicts LTR retrotransposons using the parallel version of GenomeTools gt-ltrharvest\nutility included in the ", "spaceranger_mkgtf": "Module to build a filtered GTF needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkgtf comman", "vcontact3_prepareddatabases": "Prepare and format databases for vCONTACT3 viral taxonomic analysis"}}, "target": "spaceranger_mkgtf", "target_idx": 3}
{"id": "mod_saltshaker_classify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mtDNA deletion and duplication classification downstream of mitosalt (tools: saltshaker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker/classify": "mtDNA deletion and duplication classification downstream of mitosalt", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "saltshaker/call": "mtDNA deletion and duplication calling downstream of mitosalt", "sentieon/tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.", "pirate": "Pangenome toolbox for bacterial genomes"}}, "target": "saltshaker/classify", "target_idx": 0}
{"id": "mod_hmtnote_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Human mitochondrial variants annotation using HmtVar. Contains .plk file with annotation, so can be run offline (tools: hmtnote)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"getorganelle_fromreads": "Assembles organelle genomes from genomic data", "eklipse": "tool for detection and quantification of large mtDNA rearrangements.", "minimap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "mmseqs_linclust": "Cluster sequences in linear time using MMSeqs2 linclust.", "hmtnote_annotate": "Human mitochondrial variants annotation using HmtVar. Contains .plk file with annotation, so can be run offlin"}}, "target": "hmtnote_annotate", "target_idx": 4}
{"id": "subworkflow_pkg_bam_dedup_umi_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_UMI", "modules": ["umitools/prepareforrsem", "samtools/sort", "bam_dedup_stats_samtools_umicollapse", "bam_dedup_stats_samtools_umitools", "bam_sort_stats_samtools"], "description": "BAM deduplication with UMI processing for both genome and transcriptome alignments"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_UMI (umitools/prepareforrsem, samtools/sort, bam_dedup_stats_samtools_umicollapse, bam_dedup_stats_samtools_umitools, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_DEDUP_UMI": null, "Use nf-core subworkflow bam_dedup_umi": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_dedup_umi", "target_idx": 2}
{"id": "pipe_core10_taxprofiler_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Multi-tool taxonomic classification and profiling across Kraken2, MetaPhlAn, Centrifuge, and mOTUs for shotgun metagenomic data.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)"}}, "target": "taxprofiler", "target_idx": 2}
{"id": "mod_agat_spflagshortintrons_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting the data to EBI.\n(Typical EBI error message: ********ERROR: Intron usually expected to be at least 10 nt long. Please check the accuracy) (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "kmcp_search": "Search sequences against database", "gamma_gamma": "Gene Allele Mutation Microbial Assessment", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "agat_spflagshortintrons", "target_idx": 1}
{"id": "mod_sourmash_pairwise_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/pairwise": null, "merquryfk/katcomp": null, "wipertools/fastqgather": null, "drep/dereplicate": null, "deeptools/multibamsummary": null}}, "target": "sourmash/pairwise", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Visium spatial transcriptomics with histology image. Input files: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,bam": null, "sample,fastq_1,image": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "pipe_all101_imcyto_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Image Mass Cytometry analysis pipeline. Topics: cytometry, image-analysis, image-processing, image-segmentation. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"imcyto": null, "createpanelrefs": null, "multiplesequencealign": null, "differentialabundance": null, "riboseq": null, "cageseq": null, "rnavar": null, "diaproteomics": null}}, "target": "imcyto", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pre-aligned BAM variant calling pipeline. Input files: Aligned BAM files.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_bracken_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2_BRACKEN", "modules": ["kraken2/add", "kraken2/build", "bracken/build"], "description": "KRAKEN2 and BRACKEN build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2_BRACKEN (kraken2/add, kraken2/build, bracken/build) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_BUILD_ADD_KRAKEN2_BRACKEN": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_build_add_kraken2_bracken": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2_bracken", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_14", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_channel_operator_map_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_deepbgc_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning. (tools: deepbgc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_makeblastdb": "Builds a BLAST database", "miniprot_index": "Provides fasta index required by miniprot alignment.", "deepbgc_download": "Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning.", "antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "datavzrd": "Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables."}}, "target": "deepbgc_download", "target_idx": 2}
{"id": "resource_bedtools_slop_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SLOP", "tool": "bedtools/slop", "description": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SLOP (Adds a specified number of bases in each direction (unique values may be specifi) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_deprecated_dsl1_set_keyword_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_pairtools_parse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find ligation junctions in .sam, make .pairs (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools/parse": "Find ligation junctions in .sam, make .pairs", "echtvar/anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "ferrohgvs/parse": "Parse and validate HGVS variant descriptions with ferro", "svdss/index": "Index a reference genome FASTA file using SVDSS (via ropebwt3), producing either an FMD or FMR index for use w", "circexplorer2/parse": "CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate."}}, "target": "pairtools/parse", "target_idx": 0}
{"id": "resource_artic_guppyplex_1", "category": "resource_profiling", "state": {"process": "ARTIC_GUPPYPLEX", "tool": "artic/guppyplex", "description": "Aggregates fastq files with demultiplexed reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_GUPPYPLEX (Aggregates fastq files with demultiplexed reads) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_15", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_rclone_checksum_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Check files in a destination path against a checksum SUM file (tools: rclone)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kleborate": "Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species", "pairtools/flip": "Flip pairs to get an upper-triangular matrix", "md5sum": "Create MD5 (128-bit) checksums", "rclone/checksum": "Check files in a destination path against a checksum SUM file", "rclone/copy": "Copy files or directories between local and/or remote storage using Rclone"}}, "target": "rclone/checksum", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/riboseq) for Ribosome profiling (Ribo-seq) footprint sequencing. Input files: Single-end ribosome protected RNA fragments (RPFs) with strandedness.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,cdna_fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "noul_include_modular_process_syntax_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_bedtools_sort_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SORT", "tool": "bedtools/sort", "description": "Sorts a feature file by chromosome and other criteria."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SORT (Sorts a feature file by chromosome and other criteria.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_medium", "target_idx": 2}
{"id": "noul_named_output_channel_access_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral amplicon sequencing with primers", "data_format": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_24", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_1_2", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification", "pipeline": "nf-core/hic"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hi-C chromosome conformation capture mapping?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_biscuit_epiread_0", "category": "resource_profiling", "state": {"process": "BISCUIT_EPIREAD", "tool": "biscuit/epiread", "description": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_EPIREAD (Summarizes read-level methylation (and optionally SNV) information from a\nBiscui) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_5_5", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "template": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnafusion, determine the input samplesheet column structure for: RNA gene fusion detection (Arriba, STAR-Fusion).", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_pints_caller_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Main caller script for peak calling (tools: pints)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macs3_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "pints_caller": "Main caller script for peak calling", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "genrich": "Peak-calling for ChIP-seq and ATAC-seq enrichment experiments", "scds": "Module to use scds for doublet scoring"}}, "target": "pints_caller", "target_idx": 1}
{"id": "mod_saltshaker_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mtDNA deletion and duplication calling downstream of mitosalt (tools: saltshaker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eklipse": "tool for detection and quantification of large mtDNA rearrangements.", "saltshaker/classify": "mtDNA deletion and duplication classification downstream of mitosalt", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file", "saltshaker/call": "mtDNA deletion and duplication calling downstream of mitosalt"}}, "target": "saltshaker/call", "target_idx": 4}
{"id": "samplesheet_arch_pediatric_trio_somatic_5_2", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents).", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_impute_glimpse_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_GLIMPSE", "modules": ["glimpse/chunk", "glimpse/phase", "glimpse/ligate", "bcftools/index"], "description": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_GLIMPSE (glimpse/chunk, glimpse/phase, glimpse/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow VCF_IMPUTE_GLIMPSE": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_impute_glimpse": null}}, "target": "Use nf-core subworkflow vcf_impute_glimpse", "target_idx": 3}
{"id": "resource_ale_5", "category": "resource_profiling", "state": {"process": "ALE", "tool": "ale", "description": "ALE: assembly likelihood estimator."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALE (ALE: assembly likelihood estimator.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_miniprot_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: miniprot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "odgi_sort": "Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm.", "miniprot_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "atlas_splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "miniprot_align", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "data_format": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "field_constraint_fastq_1_1_2", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "resource_antismash_antismashlite_2", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITE", "tool": "antismash/antismashlite", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITE (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pre-aligned BAM variant calling pipeline", "data_format": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Aligned BAM files?", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Single-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_0_45", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_ilastik_multicut_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. (tools: ilastik)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "ichorcna_createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "rpbp_selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s", "ilastik_multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells"}}, "target": "ilastik_multicut", "target_idx": 4}
{"id": "mod_caddsv_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score structural variants with CADD-SV. (tools: caddsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "viennarna/rnafold": "Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary str", "caddsv/run": "Score structural variants with CADD-SV.", "gatk4/printsvevidence": "WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end an", "plastid/makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-"}}, "target": "caddsv/run", "target_idx": 2}
{"id": "local_subworkflow_nextclade_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should NEXTCLADE (nextclade/run) be built?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow NEXTCLADE": null, "Leave them out": null, "Use nf-core subworkflow nextclade": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 1}
{"id": "schema_std_methylseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "description": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/methylseq?", "criteria": {"sample,fastq_1,fastq_2,genome": null, "family_id,sample,file_path,hpo_terms,sex": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "sample,fastq_1,fastq_2,replicate,control": null}}, "target": "sample,fastq_1,fastq_2,genome", "target_idx": 0}
{"id": "resource_busco_download_2", "category": "resource_profiling", "state": {"process": "BUSCO_DOWNLOAD", "tool": "busco/download", "description": "Download database for BUSCO"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_DOWNLOAD (Download database for BUSCO) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_include_modular_process_syntax_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_module_metadata_propagation_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_bam_split_by_region_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split the reads in the input bam by specified genomic region. (tools: bam_split_by_region)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/split": null, "bam_split_by_region": null, "tcoffee/consensus": null, "parabricks/dbsnp": null, "bamtools/split": null}}, "target": "bam_split_by_region", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_0_3", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "template": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_3_0", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multiplexed Oxford Nanopore run with barcode demultiplexing with entry step NANOPLOT.", "criteria": {"sample,bam": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "mod_homer_annotatepeaks_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate peaks with HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strvctvre_strvctvre": null, "hifiadapterfilt_downloaddb": null, "homer_annotatepeaks": null, "annosine": null, "homer_findpeaks": null}}, "target": "homer_annotatepeaks", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_47", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_gatk4_filtervarianttranches_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply tranche filtering (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4/filtervarianttranches": "Apply tranche filtering", "fgbio/callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "fastq_index_filter_deacon": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon"}}, "target": "gatk4/filtervarianttranches", "target_idx": 1}
{"id": "mod_picard_splitsambynumberofreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits a SAM/BAM/CRAM file to multiple files. This tool splits the input query-grouped SAM/BAM/CRAM file into multiple files while maintaining the sort order. This can be used to split a large unmapped input in order to parallelize alignment. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_splitsambynumberofreads": "Splits a SAM/BAM/CRAM file to multiple files. This tool splits the input query-grouped SAM/BAM/CRAM file into ", "sylph_profile": "Sylph profile command for taxonoming profiling", "bedtools_split": "Split BED files into several smaller BED files", "quartonotebook": "Render a Quarto notebook, including parametrization.", "bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "picard_splitsambynumberofreads", "target_idx": 0}
{"id": "mod_seqtk_trim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim low quality bases from FastQ files (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqtk_trim": "Trim low quality bases from FastQ files", "ariba_getref": "Download and prepare database for Ariba analysis", "parsesdrf_convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration ", "svim_alignment": "Structural variant detection from long-read sequencing alignments using SVIM.", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "seqtk_trim", "target_idx": 0}
{"id": "mod_popscle_demuxlet_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing and external genotyping data for each sample is available. (tools: popscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU", "mobsuite_recon": "A tool to reconstruct plasmids in bacterial assemblies", "popscle_demuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "ciri2": "Circular RNA identification based on multiple seed matching"}}, "target": "popscle_demuxlet", "target_idx": 3}
{"id": "mod_samtools_idxstats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reports alignment summary statistics for a BAM/CRAM/SAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_idxstats": null, "bamtools_stats": null, "seqfu_check": null, "hhsuite_hhsearch": null, "ltrretriever_lai": null}}, "target": "samtools_idxstats", "target_idx": 0}
{"id": "field_constraint_bai_0_14", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "intent_debug_error_4", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq. Input files: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_vrhyme_vrhyme_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Binning virus genomes from metagenomes (tools: vrhyme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vrhyme_vrhyme": "Binning virus genomes from metagenomes", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "pcangsd_inbreeding": "Estimate per-sample inbreeding coefficients from genotype likelihoods", "deeparg_predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "concoct_concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile"}}, "target": "vrhyme_vrhyme", "target_idx": 0}
{"id": "schema_std_createtaxdb_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createtaxdb", "description": "Parallelised and automated construction of metagenomic classifier databases of different tools", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/createtaxdb?", "criteria": {"id,taxid,fasta_dna,fasta_aa": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "id,taxid,fasta_dna,fasta_aa", "target_idx": 0}
{"id": "mod_openms_idmassaccuracy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates a distribution of the mass error from given mass spectra and IDs. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms/idmassaccuracy": "Calculates a distribution of the mass error from given mass spectra and IDs.", "openms/filefilter": "Filters peptide/protein identification results by different criteria.", "gemmi/cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "last/postmask": "Post-alignment masking", "openms/decoydatabase": "Create a decoy peptide database from a standard FASTA database."}}, "target": "openms/idmassaccuracy", "target_idx": 0}
{"id": "resource_bbmap_repair_1", "category": "resource_profiling", "state": {"process": "BBMAP_REPAIR", "tool": "bbmap/repair", "description": "Re-pairs reads that became disordered or had some mates eliminated."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_REPAIR (Re-pairs reads that became disordered or had some mates eliminated.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "core_tool_interproscan_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Scan protein and nucleotide sequences against multiple member databases to identify structural domains, functional sites, and protein families.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"diamond": null, "blastp": null, "hmmer": null, "eggnog": null, "interproscan": null}}, "target": "interproscan", "target_idx": 4}
{"id": "mod_svtk_standardize_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert SV calls to a standardized format. (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_dedup_bwameth": null, "portcullis/full": null, "svtk/rdtest2vcf": null, "annotsv/installannotations": null, "svtk/standardize": null}}, "target": "svtk/standardize", "target_idx": 4}
{"id": "mod_crabs_import_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In-house generated or curated data can be imported into CRABS. (tools: crabs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nextclade/run": "SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation)", "fastqutils/info": "Performs quality control of FASTQ files", "crabs/import": "In-house generated or curated data can be imported into CRABS.", "samtools/ampliconclip": "Clips read alignments where they match BED file defined regions", "seqkit/translate": "Translate DNA/RNA to protein sequence"}}, "target": "crabs/import", "target_idx": 2}
{"id": "mod_ciri2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Circular RNA identification based on multiple seed matching (tools: ciri2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ciri2": "Circular RNA identification based on multiple seed matching", "segemehl_align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection", "segemehl_index": "Generate genome indices for segemehl align", "deeptools_computematrix": "calculates scores per genome regions for other deeptools plotting utilities", "catpack_contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins)."}}, "target": "ciri2", "target_idx": 0}
{"id": "mod_plink_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subset plink bfiles with a text file of variant identifiers (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools/extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "plink/extract": "Subset plink bfiles with a text file of variant identifiers", "iphop/predict": "Predict phage host using iPHoP", "force/cube": "Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spat", "picard/extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at"}}, "target": "plink/extract", "target_idx": 1}
{"id": "mod_msisensorpro_baseline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msisensor-pro/pro tumor-only MSI detection. (tools: msisensorpro)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro_msisomatic": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "controlfreec_assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "msisensorpro_baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "emu_abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads.", "vembrane_sort": "Sort VCF/BCF files by custom Python expressions for variant prioritization"}}, "target": "msisensorpro_baseline", "target_idx": 2}
{"id": "resource_affy_justrma_0", "category": "resource_profiling", "state": {"process": "AFFY_JUSTRMA", "tool": "affy/justrma", "description": "Read CEL files into an ExpressionSet and generate a matrix"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AFFY_JUSTRMA (Read CEL files into an ExpressionSet and generate a matrix) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_variantprioritization_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for variantprioritization analysis? Specific context: Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR).. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]"}}, "target": "variantprioritization", "target_idx": 0}
{"id": "noul_multiple_script_sections_invalid_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_vrhyme_extractunbinned_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracting sequences that were unbinnned by vRhyme into a FASTA file (tools: vrhyme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd_soapsnpcalibration": null, "vrhyme_extractunbinned": null, "vrhyme_vrhyme": null, "deeptools_multibamsummary": null, "vt_decomposeblocksub": null}}, "target": "vrhyme_extractunbinned", "target_idx": 1}
{"id": "mod_crabz_compress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compress files with crabz (tools: crabz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_bgzip": null, "gfatools_stat": null, "crabz_compress": null, "foldcomp_decompress": null, "integronfinder": null}}, "target": "crabz_compress", "target_idx": 2}
{"id": "mod_fgbio_groupreadsbyumi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template, and then templates are sorted by the 5’ mapping positions\nof the reads from the template, used from earliest mapping position to latest.\nReads that have the same end positions are then sub-grouped by UMI sequence.\n(!) Note: the MQ tag is required on reads with mapped mates (!)\nThis can be added using samblaster with the optional argument --addMateTags. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kled": null, "fgbio/zipperbams": null, "repeatmasker/repeatmasker": null, "fgbio/copyumifromreadname": null, "fgbio/groupreadsbyumi": null}}, "target": "fgbio/groupreadsbyumi", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_qc_stats_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_STATS", "modules": ["fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp"], "description": "Generate statistics for short read sequencing data using multiple tools"}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_STATS (fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_QC_STATS": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_qc_stats": null}}, "target": "Use nf-core subworkflow fastq_qc_stats", "target_idx": 3}
{"id": "mod_bbmap_repair_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Re-pairs reads that became disordered or had some mates eliminated. (tools: repair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani_search": "Memory-efficient ANI database queries with skani.", "metamaps_mapdirectly": "Maps long reads to a metamaps database", "bbmap_repair": "Re-pairs reads that became disordered or had some mates eliminated.", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "ariba_run": "Query input FASTQs against Ariba formatted databases"}}, "target": "bbmap_repair", "target_idx": 2}
{"id": "resource_bcftools_roh_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROH", "tool": "bcftools/roh", "description": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROH (A program for detecting runs of homo/autozygosity. Only bi-allelic sites are con) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_4_3", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_channel_mix_operator_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_parabricks_fq2bam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated alignment, sorting, BQSR calculation, and duplicate marking. Note this nf-core module requires files to be copied into the working directory and not symlinked. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"goleft_indexsplit": "Quickly generate evenly sized (by amount of data) regions across a number of bam/cram files", "parabricks_fq2bam": "NVIDIA Clara Parabricks GPU-accelerated alignment, sorting, BQSR calculation, and duplicate marking. Note this", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "ribowaltz": "Calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap"}}, "target": "parabricks_fq2bam", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_0", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bamclipper_4", "category": "resource_profiling", "state": {"process": "BAMCLIPPER", "tool": "bamclipper", "description": "This module is used to clip primer sequences from your alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCLIPPER (This module is used to clip primer sequences from your alignments.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "intent_build_pipeline_14", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "build_pipeline", "target_idx": 2}
{"id": "noul_named_output_channel_access_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_3_2", "category": "samplesheet_schema", "state": {"technology": "Variant Annotation", "workflow_entry": "ENSEMBLVEP", "library_inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Downstream functional annotation of pre-called VCF files with entry step ENSEMBLVEP.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf,tbi": null}}, "target": "sample,vcf,tbi", "target_idx": 3}
{"id": "mod_samtools_ampliconclip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clips read alignments where they match BED file defined regions (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"minia": "Minia is a short-read assembler based on a de Bruijn graph", "crabs/insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR.", "samtools/ampliconclip": "Clips read alignments where they match BED file defined regions", "artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "longphase/haplotag": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi"}}, "target": "samtools/ampliconclip", "target_idx": 2}
{"id": "mod_pridepy_downloadfile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download a single file from the PRIDE Archive by name using pridepy. (tools: pridepy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "pridepy_downloadfile": "Download a single file from the PRIDE Archive by name using pridepy.", "annotsv_installannotations": "Install the AnnotSV annotations", "foldmason_msa2lddtreport": "Renders a visualization report using foldmason", "fastq_align_hisat2": "Align reads to a reference genome using hisat2 then sort with samtools"}}, "target": "pridepy_downloadfile", "target_idx": 1}
{"id": "intent_prepare_data_9", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "ask_question": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_1_3", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"sample,fastq_1": null, "patient,sample,status,bam,bai": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_bai_1_9", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "mod_gridss_extractoverlappingfragments_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for targeted GRIDSS structural variant calling. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss_extractoverlappingfragments": null, "gridss_generateponbedpe": null, "odgi_view": null, "gridss_gridss": null, "telescope_assign": null}}, "target": "gridss_extractoverlappingfragments", "target_idx": 0}
{"id": "resource_alignoth_4", "category": "resource_profiling", "state": {"process": "ALIGNOTH", "tool": "alignoth", "description": "Creating alignment plots from bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALIGNOTH (Creating alignment plots from bam files) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_diann_insilicolibrarygeneration_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN software for data-independent acquisition (DIA) proteomics data processing.\nOutput materials should include attribution: \"Generated using DIA-NN\". (tools: diann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_mpileup": "Compresses VCF files", "diann_insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "vardictjava": "The Java port of the VarDict variant caller", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "dia_proteomics_analysis": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,\npreliminary analysis, emp"}}, "target": "diann_insilicolibrarygeneration", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_4_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "BWA_MEM", "library_inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs for patient tumor and germline normal tissue?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_windowmasker_mkcounts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program to generate frequency counts of repetitive units. (tools: windowmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"windowmasker_mkcounts": "A program to generate frequency counts of repetitive units.", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "chromap_chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "kleborate": "Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species"}}, "target": "windowmasker_mkcounts", "target_idx": 0}
{"id": "mod_octopusv_stat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarize structural variant statistics from octopusv SVCF files (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"octopusv_svcf2bed": "Converts octopusv SVCF files to the standard BED format", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "ivar_trim": "Trim primer sequences rom a BAM file with iVar", "octopusv_plot": "Plot structural variant statistics using octopusv stat output", "octopusv_stat": "Summarize structural variant statistics from octopusv SVCF files"}}, "target": "octopusv_stat", "target_idx": 4}
{"id": "mod_fastqdl_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download FASTQ files from SRA or ENA repositories. (tools: fastqdl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aria2": "CLI Download utility", "vg_deconstruct": "Deconstruct snarls present in a variation graph in GFA format to variants in VCF format", "sniffles": "structural-variant calling with sniffles", "caalm_downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "fastqdl": "Download FASTQ files from SRA or ENA repositories."}}, "target": "fastqdl", "target_idx": 4}
{"id": "mod_blobtk_depth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a bed file containing the depth of data at intervals of an aligned bam. (tools: blobtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pear": "PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger.", "bamclipper": "This module is used to clip primer sequences from your alignments.", "blobtk/depth": "Creates a bed file containing the depth of data at intervals of an aligned bam.", "svtk/countsvtypes": "Count the instances of each SVTYPE observed in each sample in a VCF.", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "blobtk/depth", "target_idx": 2}
{"id": "mod_mcroni_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analysis of mcr-1 gene (mobilized colistin resistance) for sequence variation (tools: mcroni)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "holodeck_methylate": "Generate a methylation-annotated VCF from a reference genome with holodeck", "mcroni": "Analysis of mcr-1 gene (mobilized colistin resistance) for sequence variation", "tbprofiler_profile": "A tool to detect resistance and lineages of M. tuberculosis genomes", "vcontact3_prepareddatabases": "Prepare and format databases for vCONTACT3 viral taxonomic analysis"}}, "target": "mcroni", "target_idx": 2}
{"id": "mod_parabricks_rnafq2bam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool is the equivalent of fq2bam for RNA-Seq samples, receiving inputs in FASTQ format, performing alignment with the splice-aware STAR algorithm, optionally marking of duplicate reads, and outputting an aligned BAM file ready for variant and fusion calling. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/rnafq2bam": null, "sentieon/wgsmetrics": null, "spaceranger/mkref": null, "bamaligncleaner": null, "ampcombi2/parsetables": null}}, "target": "parabricks/rnafq2bam", "target_idx": 0}
{"id": "resource_any2fasta_3", "category": "resource_profiling", "state": {"process": "ANY2FASTA", "tool": "any2fasta", "description": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input files may be gzip, bzip2, zip, or zstd compressed."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANY2FASTA (Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_status_1_7", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "pipe_all101_nascent_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Nascent Transcription Processing Pipeline. Topics: gro-seq, nascent, pro-seq, rna, transcription, tss. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nascent": null, "pacvar": null, "demultiplex": null, "proteogenomicsdb": null, "proteinfold": null, "multiplesequencealign": null, "hadge": null, "oncoanalyser": null}}, "target": "nascent", "target_idx": 0}
{"id": "noul_container_environment_specification_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_channel_mix_operator_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_sex_0_14", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "noul_channel_operator_map_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_varlociraptor_callvariants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlociraptor preprocessing (tools: varlociraptor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastk/fastk": null, "varlociraptor/callvariants": null, "freyja/boot": null, "delly/call": null, "merquryfk/katgc": null}}, "target": "varlociraptor/callvariants", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_4_1", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs for patient tumor and germline normal tissue?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_4_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering?", "criteria": {"sample,rrna_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 2}
{"id": "schema_std_mag_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay": "mag pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/mag (Assembly and binning of metagenomes)?", "criteria": {"gene_name,alignment,tree,suite,tool": null, "id,raw_file": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,fastq_1,fastq_2,bam,seq_type": null}}, "target": "sample,run,group,short_reads_1,short_reads_2", "target_idx": 2}
{"id": "resource_bcftools_plotvcfstats_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLOTVCFSTATS", "tool": "bcftools/plotvcfstats", "description": "Plots the output of bcftools stats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLOTVCFSTATS (Plots the output of bcftools stats) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_homer_makeucscfile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a UCSC bed graph with the HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)", "fastqe": "fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data.", "homer_findpeaks": "Find peaks with HOMER suite", "homer_makeucscfile": "Create a UCSC bed graph with the HOMER suite", "untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives"}}, "target": "homer_makeucscfile", "target_idx": 3}
{"id": "resource_bcftools_reheader_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_REHEADER", "tool": "bcftools/reheader", "description": "Reheader a VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_REHEADER (Reheader a VCF file) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_meryl_unionsum_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A genomic k-mer counter (and sequence utility) with nice features. (tools: meryl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkv_endtoend": "Assess the quality of metagenome-assembled viral genomes.", "fastk_histex": "A fast K-mer counter for high-fidelity shotgun datasets", "bigslice_bigslice": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenB", "fastk_fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "meryl_unionsum": "A genomic k-mer counter (and sequence utility) with nice features."}}, "target": "meryl_unionsum", "target_idx": 4}
{"id": "mod_vembrane_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort VCF/BCF files by custom Python expressions for variant prioritization (tools: vembrane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_liftovervcf": "Lifts over a VCF file from one reference build to another.", "vembrane_sort": "Sort VCF/BCF files by custom Python expressions for variant prioritization", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "gapseq_find": "Predict metabolic pathways from genomic data using gapseq"}}, "target": "vembrane_sort", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_0_3", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "template": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_22", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_confusing_combine_with_mix_semantics_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_3", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "noul_channel_collect_operator_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_ngscheckmate_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_NGSCHECKMATE", "modules": ["ngscheckmate/fastq", "ngscheckmate/vafncm"], "description": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs."}, "question": {"type": "choice", "instructions": "How should FASTQ_NGSCHECKMATE (ngscheckmate/fastq, ngscheckmate/vafncm) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_NGSCHECKMATE": null, "Use nf-core subworkflow fastq_ngscheckmate": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_ngscheckmate", "target_idx": 2}
{"id": "mod_fasta_vclust_prefilter_align_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter\nof candidate sequence pairs with `vclust prefilter`, 2) compute pairwise\nalignments and similarity metrics with `vclust align`, and 3) generate\nthreshold-based clusters with `vclust cluster`. (tools: fasta_vclust_prefilter_align_cluster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "deepmased/features": "DeepMAsED features subcommand: extracts alignment-based features from BAM and assembly FASTA for each contig, ", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "panacus/histgrowth": "Calculates a coverage histogram from a GFA file and constructs a growth table from this as either a TSV or HTM", "fasta_vclust_prefilter_align_cluster": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter\nof candidate sequence pairs with `v"}}, "target": "fasta_vclust_prefilter_align_cluster", "target_idx": 4}
{"id": "noul_named_output_channel_access_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_sourmash_gather_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search a metagenome sourmash signature against one or many reference databases and return the minimum set of genomes that contain the k-mers in the metagenome. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cobiontid_kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written", "sourmash_gather": "Search a metagenome sourmash signature against one or many reference databases and return the minimum set of g", "tidk_explore": "`tidk explore` attempts to find the simple telomeric repeat unit in the genome provided.\nIt will report this r", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity", "mmseqs_createtsv": "Create a tsv file from a query and a target database as well as the result database"}}, "target": "sourmash_gather", "target_idx": 1}
{"id": "noul_retry_errorstrategy_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_biscuit_bsconv_0", "category": "resource_profiling", "state": {"process": "BISCUIT_BSCONV", "tool": "biscuit/bsconv", "description": "Summarize and/or filter reads based on bisulfite conversion rate"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BSCONV (Summarize and/or filter reads based on bisulfite conversion rate) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_47", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_modular_subworkflow_composition_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_confusing_combine_with_mix_semantics_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_gatk4_reblockgvcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Condenses homRef blocks in a single-sample GVCF (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4_reblockgvcf": "Condenses homRef blocks in a single-sample GVCF", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment", "catpack_summarise": "Summarises results from CAT/BAT/RAT classification steps"}}, "target": "gatk4_reblockgvcf", "target_idx": 1}
{"id": "noul_subworkflow_structural_blocks_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fgumi_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters consensus reads generated by simplex or duplex consensus calling.\nThis is a high-performance replacement for fgbio FilterConsensusReads. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae/trim": null, "fgbio/zipperbams": null, "fastme": null, "agat/sqstatbasic": null, "fgumi/filter": null}}, "target": "fgumi/filter", "target_idx": 4}
{"id": "mod_deeptmhmm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A Deep Learning Model for Transmembrane Topology Prediction and Classification (tools: deeptmhmm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rsem/preparereference": null, "blast/blastp": null, "deeptmhmm": null, "circexplorer2/annotate": null, "caalm/caalm": null}}, "target": "deeptmhmm", "target_idx": 2}
{"id": "resource_aardvark_merge_1", "category": "resource_profiling", "state": {"process": "AARDVARK_MERGE", "tool": "aardvark/merge", "description": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_MERGE (A tool to evaluate and merge multiple variant calls into a consensus VCF.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_sentieon_dnamodelapply_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: modifies the input VCF file by adding the MLrejected FILTER to the variants (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "wisecondorx/convert": "Convert and filter aligned reads to .npz", "bam_impute_quilt": "Subworkflow to impute BAM files using QUILT software.\nVariants location to impute are obtain through the tsv f", "sentieon/dnamodelapply": "modifies the input VCF file by adding the MLrejected FILTER to the variants", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "sentieon/dnamodelapply", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_6_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns are standard for CAGE-seq 5-prime capped transcript end sequencing input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,tss_bed": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "noul_undeclared_process_file_inputs_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_qualimap_bamqccram_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment data (tools: qualimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "qualimap_bamqccram": "Evaluate alignment data", "sortmerna": "Local sequence alignment tool for filtering, mapping and clustering.", "windowmasker_mkcounts": "A program to generate frequency counts of repetitive units.", "busco_generateplot": "BUSCO plot generation tool"}}, "target": "qualimap_bamqccram", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_smartseq_plate_based_1_4", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,matrix": null, "plate,sample,bam": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_biscuit_biscuitblaster_2", "category": "resource_profiling", "state": {"process": "BISCUIT_BISCUITBLASTER", "tool": "biscuit/biscuitblaster", "description": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BISCUITBLASTER (A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM f) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_32", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_1_5", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,matrix": null, "sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "schema_std_methylarray_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylarray", "description": "Process methylation data from Illumina arrays. Pre-processing, quality checks, confounder check and DMPs (differentially methylated positions) and DMRs (differentially methylated regions). Optionally estimates cell type composition and adjusts data for it.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/methylarray?", "criteria": {"sample_id,idat_red,idat_green,group": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample_id,idat_red,idat_green,group", "target_idx": 0}
{"id": "mod_sam2lca_analyze_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calling lowest common ancestors from multi-mapped reads in SAM/BAM/CRAM files (tools: sam2lca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "sam2lca_analyze": "Calling lowest common ancestors from multi-mapped reads in SAM/BAM/CRAM files", "abundance_differential_filter": "A subworkflow for filtering differential abundance results", "haplogrep2_classify": "classification into haplogroups"}}, "target": "sam2lca_analyze", "target_idx": 2}
{"id": "mod_htseq_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: count how many reads map to each feature (tools: htseq/count)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc/count": null, "htseq/count": null, "vembrane/sort": null, "amulety/antiberta2": null, "fastk/fastk": null}}, "target": "htseq/count", "target_idx": 1}
{"id": "mod_pharmcat_reporter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescribing recommendations for clinical decision support. (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon/report": "Generate a ganon report file from the output of ganon classify", "ucsc/bigwigaverageoverbed": "compute average score of bigwig over bed file", "pharmcat/reporter": "The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescri", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "hmmcopy/readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows"}}, "target": "pharmcat/reporter", "target_idx": 2}
{"id": "schema_std_rnasplice_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnasplice", "assay": "rnasplice pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnasplice (rnasplice is a bioinformatics pipeline for RNA-seq alternati)?", "criteria": {"sample,seed": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "id,raw_file": null}}, "target": "sample,fastq_1,fastq_2,strandedness,condition", "target_idx": 1}
{"id": "mod_seqcluster_collapse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file. (tools: seqcluster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqcluster_collapse": null, "cdhit_cdhit": null, "staphscan": null, "isoseq_cluster": null, "homer_annotatepeaks": null}}, "target": "seqcluster_collapse", "target_idx": 0}
{"id": "noul_include_modular_process_syntax_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_nanoseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Nanopore demultiplexing, QC and alignment pipeline. Topics: alignment, demultiplexing, nanopore, qc. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nascent": null, "slamseq": null, "seqsubmit": null, "ampliseq": null, "pixelator": null, "cutandrun": null, "isoseq": null, "nanoseq": null}}, "target": "nanoseq", "target_idx": 7}
{"id": "samplesheet_arch_ont_metagenome_single_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Long-read Oxford Nanopore environmental metagenomic sequencing)", "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Oxford Nanopore environmental metagenomic sequencing input samplesheet?", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_learnmsa_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align sequences using learnMSA (tools: learnmsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"learnmsa/align": "Align sequences using learnMSA", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "falco": "Run falco on sequenced reads", "seqcluster/collapse": "Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file.", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins"}}, "target": "learnmsa/align", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_1_2", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,unite_fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_ariba_getref_3", "category": "resource_profiling", "state": {"process": "ARIBA_GETREF", "tool": "ariba/getref", "description": "Download and prepare database for Ariba analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_GETREF (Download and prepare database for Ariba analysis) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_bam_1_11", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "mod_hapibd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The hap-ibd program detects identity-by-descent (IBD) segments and homozygosity-by-descent (HBD) segments in phased genotype data. The hap-ibd program can analyze data sets with hundreds of thousands of samples. (tools: hapibd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_clustermetrics": null, "duphold": null, "hapibd": null, "bedtools_map": null, "bam_telomere_estimation": null}}, "target": "hapibd", "target_idx": 2}
{"id": "pipe_core10_chipseq_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Mapping transcription factor occupancy across the genome using cross-linked chromatin immunoprecipitation followed by sequencing.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)"}}, "target": "chipseq", "target_idx": 0}
{"id": "resource_abritamr_run_4", "category": "resource_profiling", "state": {"process": "ABRITAMR_RUN", "tool": "abritamr/run", "description": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRITAMR_RUN (A NATA accredited tool for reporting the presence of antimicrobial resistance ge) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_amulety_translate_5", "category": "resource_profiling", "state": {"process": "AMULETY_TRANSLATE", "tool": "amulety/translate", "description": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_TRANSLATE (A module to translate BCR and TCR nucleotide sequences into amino acid sequences) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_verifybamid_verifybamid2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure high quality sequence reads and reliable downstream analysis. (tools: verifybamid2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem3_index": "Create bwa-mem3 index for reference genome", "verifybamid_verifybamid2": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "bedgraph_bedclip_bedgraphtobigwig": "Convert bedgraph to bigwig with clip", "authentict_deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries"}}, "target": "verifybamid_verifybamid2", "target_idx": 1}
{"id": "resource_antismash_antismash_5", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASH", "tool": "antismash/antismash", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASH (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_ganon_buildcustom_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build ganon database using custom reference sequences. (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon/report": "Generate a ganon report file from the output of ganon classify", "fastq_qc_trim_filter_setstrandedness": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files,", "elprep/split": "Split bam file into manageable chunks", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "ganon/buildcustom", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_39", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "field_constraint_fastq_1_1_0", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "mod_custom_tabulartogseachip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make a GSEA class file (.chip) from tabular inputs (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bcftools_convert": "Converts certain output formats to VCF", "custom_tabulartogseachip": "Make a GSEA class file (.chip) from tabular inputs", "bam_qc_picard": "Produces comprehensive statistics from BAM file", "custom_tabulartogseagct": "Convert a TSV or CSV with features by row and observations by column to a GCT format file as consumed by GSEA"}}, "target": "custom_tabulartogseachip", "target_idx": 2}
{"id": "mod_sgdemux_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex bgzip'd fastq files (tools: sgdemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/happy": "Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row", "gappa/examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "fqtk": "Demultiplex fastq files", "bcl2fastq": "Demultiplex Illumina BCL files", "sgdemux": "Demultiplex bgzip'd fastq files"}}, "target": "sgdemux", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_0_17", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_artic_guppyplex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregates fastq files with demultiplexed reads (tools: artic)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files.", "artic/minion": "Run the alignment/variant-call/consensus logic of the artic pipeline", "cleanifier/index": "Builds a Cuckoo filter or Cuckoo hash table index from reference sequences (FASTA/FASTQ) for fast contaminatio", "artic/guppyplex": "Aggregates fastq files with demultiplexed reads", "artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}}, "target": "artic/guppyplex", "target_idx": 3}
{"id": "mod_cnvkit_target_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transform bait intervals into targets more suitable for CNVkit. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromap/chromap": null, "cnvkit/target": null, "fastcov": null, "cnvkit/export": null, "cnvkit/coverage": null}}, "target": "cnvkit/target", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_28", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_4_3", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "mod_paraclu_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Paraclu finds clusters in data attached to sequences. (tools: paraclu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"falint": "A fasta linter/validator", "paraclu": "Paraclu finds clusters in data attached to sequences.", "gapseq/draft": "Create draft metabolic model from pathway and transporter predictions", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "csvtk/sort": "Sort  CSV (or TSV) tables"}}, "target": "paraclu", "target_idx": 1}
{"id": "mod_biscuit_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit. (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trimgalore": "A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith e", "biscuit/biscuitblaster": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit", "biscuit/align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "biscuit/epiread": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compl", "slimfastq": "Fast, efficient, lossless compression of FASTQ files."}}, "target": "biscuit/align", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_23", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_bbmap_pileup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hlala/preparegraph": "Pre-compute the graph index structure.", "vcf2maf": "vcf2maf", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "bbmap/pileup": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file."}}, "target": "bbmap/pileup", "target_idx": 4}
{"id": "noul_channel_join_operator_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_45", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_adapterremovalfixprefix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with DeDup. (tools: adapterremovalfixprefix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "spaceranger_mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "ucsc_bedtobigbed": "Convert file from bed to bigBed format"}}, "target": "adapterremovalfixprefix", "target_idx": 0}
{"id": "mod_deepvariant_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: (DEPRECATED - see main.nf) DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/flank": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file.", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools/consensus": "Compresses VCF files", "deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "vcfexpress": "Filter a VCF/BCF and optionally print by template expression. If no template is given the output will be VCF/B"}}, "target": "deepvariant", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_6", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_38", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_5_2", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Multiplexed Oxford Nanopore run with barcode demultiplexing.", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "mod_pridepy_fetchsdrf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fetch an SDRF file from the PRIDE Archive for a given project accession. (tools: pridepy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust", "pridepy/fetchsdrf": "Fetch an SDRF file from the PRIDE Archive for a given project accession.", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline", "rsem/preparereference": "Prepare a reference genome for RSEM", "diamond/linclust": "Fast protein sequence clustering using a greedy incremental approach"}}, "target": "pridepy/fetchsdrf", "target_idx": 1}
{"id": "mod_trust4_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run TRUST4 on RNA-seq data (tools: trust4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety_balmpaired": null, "trust4": null, "samtools_reheader": null, "amulety_embed": null, "metaspace_download": null}}, "target": "trust4", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_41", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_scrna_10x_v3_3_2", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "mod_trimgalore_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith extra functionality for RRBS data (tools: trimgalore)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "trimgalore": "A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith e", "flash": "Perform merging of mate paired-end sequencing reads", "trgt_plot": "Visualize tandem repeats genotyped by TRGT", "chromap_chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap."}}, "target": "trimgalore", "target_idx": 1}
{"id": "mod_gatk4_cleansam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped reads (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paraclu": null, "bamaligncleaner": null, "evigene/tr2aacds": null, "last/lastal": null, "gatk4/cleansam": null}}, "target": "gatk4/cleansam", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_decontaminate_deacon_hostile_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DECONTAMINATE_DEACON_HOSTILE", "modules": ["hostile/fetch", "hostile/clean", "deacon/index", "deacon/filter", "fastq_fetch_clean_hostile", "fastq_index_filter_deacon"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile"}, "question": {"type": "choice", "instructions": "How should FASTQ_DECONTAMINATE_DEACON_HOSTILE (hostile/fetch, hostile/clean, deacon/index, deacon/filter, fastq_fetch_clean_hostile, fastq_index_filter_deacon) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_decontaminate_deacon_hostile": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_DECONTAMINATE_DEACON_HOSTILE": null}}, "target": "Use nf-core subworkflow fastq_decontaminate_deacon_hostile", "target_idx": 0}
{"id": "mod_fgumi_simplexmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi", "cooler_merge": "Merge multiple coolers with identical axes", "fgumi_dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "octopusv_svcf2bed": "Converts octopusv SVCF files to the standard BED format", "fgumi_simplexmetrics": "Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data"}}, "target": "fgumi_simplexmetrics", "target_idx": 4}
{"id": "pipe_all101_smrnaseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for small-rna analysis? Specific context: A small-RNA sequencing analysis pipeline. Topics: small-rna, smrna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]"}}, "target": "smrnaseq", "target_idx": 5}
{"id": "subworkflow_pkg_bam_qc_rnaseq_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_RNASEQ", "modules": ["preseq/lcextrap", "qualimap/rnaseq", "dupradar", "subread/featurecounts", "custom/multiqccustombiotype", "samtools/sort", "bam_rseqc"], "description": "Run post-alignment QC tools on RNA-seq BAM files including library complexity"}, "question": {"type": "choice", "instructions": "How should BAM_QC_RNASEQ (preseq/lcextrap, qualimap/rnaseq, dupradar, subread/featurecounts, custom/multiqccustombiotype, samtools/sort, bam_rseqc) be structured in DSL2?", "criteria": {"Local subworkflow BAM_QC_RNASEQ": null, "Leave them out": null, "Use nf-core subworkflow bam_qc_rnaseq": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_qc_rnaseq", "target_idx": 2}
{"id": "local_subworkflow_daisribosome_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should this step (dais) be packaged: Custom ribosomal frameshift translation analysis?", "criteria": {"Use nf-core subworkflow daisribosome": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow DAISRIBOSOME": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 3}
{"id": "mod_deepbgc_pipeline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepBGC detects BGCs in bacterial and fungal genomes using deep learning. (tools: deepbgc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "hamronization/summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "deepbgc/pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "bedtools/complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}}, "target": "deepbgc/pipeline", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_5_3", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_bai_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "mod_hmmer_eslsfetch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. The esl-sfetch utility is an Easel\nminiapp bundled with the HMMER package. This module only fetches: the SSI\nindex must be produced beforehand by the sibling module\n`hmmer/eslsfetchindex`. The keyfile is used to fetch the named sequences\n(-f), or, with ext.args = '-C', parsed as a subsequence coordinate file\n(-Cf) to extract and rename subsequences. (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_eslalimask": "Mask multiple sequence alignments", "ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro", "samtools_cramsize": "List CRAM Content-ID and Data-Series sizes", "hmmer_eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "hmmer_eslsfetch": "Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. T"}}, "target": "hmmer_eslsfetch", "target_idx": 4}
{"id": "mod_multivcfanalyzer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SNP table generator from GATK UnifiedGenotyper with functionality geared for aDNA (tools: multivcfanalyzer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvpytor/partition": "Calculate segmentation for specified bin size (multiple bin sizes separate by space)", "multivcfanalyzer": "SNP table generator from GATK UnifiedGenotyper with functionality geared for aDNA", "atlas/call": "generate VCF file from a BAM file using various calling methods", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "multivcfanalyzer", "target_idx": 1}
{"id": "pipe_core10_taxprofiler_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Shotgun metagenomic profiling combining multiple taxonomic classifiers into harmonized multi-sample reports.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": null, "eager": null, "rnaseq": null, "sarek": null, "chipseq": null, "mag": null, "ampliseq": null, "scrnaseq": null, "viralrecon": null, "atacseq": null}}, "target": "taxprofiler", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_4_3", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "template": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_8_1", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "mod_fgbio_filterconsensusreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDuplexConsensusReads. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_groupreadsbyumi": null, "xz_compress": null, "graphmap2_align": null, "fgbio_callduplexconsensusreads": null, "fgbio_filterconsensusreads": null}}, "target": "fgbio_filterconsensusreads", "target_idx": 4}
{"id": "samplesheet_arch_metatranscriptome_denovo_6_0", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns are standard for Environmental community metatranscriptomics de novo assembly input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1,fastq_2": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "mod_memote_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run memote test suite and collect results as JSON (tools: memote)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"carveme/carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "memote/run": "Run memote test suite and collect results as JSON", "ldak/thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "gapseq/fill": "Perform gap filling on draft metabolic model", "salmon/index": "Create index for salmon"}}, "target": "memote/run", "target_idx": 1}
{"id": "subworkflow_pkg_homer_groseq_1", "category": "subworkflow_packaging", "state": {"subworkflow": "HOMER_GROSEQ", "modules": ["unzip", "homer/maketagdirectory", "homer/makeucscfile", "homer/findpeaks", "homer/pos2bed"], "description": "Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.ucsd.edu/homer/ngs/groseq/groseq.html)."}, "question": {"type": "choice", "instructions": "How should HOMER_GROSEQ (unzip, homer/maketagdirectory, homer/makeucscfile, homer/findpeaks, homer/pos2bed) be structured in DSL2?", "criteria": {"Use nf-core subworkflow homer_groseq": null, "Local subworkflow HOMER_GROSEQ": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow homer_groseq", "target_idx": 0}
{"id": "mod_cdhit_cdhit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster protein sequences using sequence similarity (tools: cdhit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cdhit_cdhit": "Cluster protein sequences using sequence similarity", "artic_minion": "Run the alignment/variant-call/consensus logic of the artic pipeline", "seqtk_subseq": "Select only sequences that match the filtering condition", "paraclu": "Paraclu finds clusters in data attached to sequences.", "cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity"}}, "target": "cdhit_cdhit", "target_idx": 0}
{"id": "field_constraint_expected_cells_3_9", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "resource_bedtools_split_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SPLIT", "tool": "bedtools/split", "description": "Split BED files into several smaller BED files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SPLIT (Split BED files into several smaller BED files) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_autocycler_trim_2", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_TRIM", "tool": "autocycler/trim", "description": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_TRIM (Trim cluster assembly graphs to remove unsupported segments prior to resolution.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_fastq_qc_trim_filter_setstrandedness_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files, preparing them for downstream analysis. (tools: fastq_qc_trim_filter_setstrandedness)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"estsfs": "estimation of the unfolded site frequency spectrum", "ariba_getref": "Download and prepare database for Ariba analysis", "kraken2_kraken2": "Classifies metagenomic sequence data", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "fastq_qc_trim_filter_setstrandedness": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files,"}}, "target": "fastq_qc_trim_filter_setstrandedness", "target_idx": 4}
{"id": "mod_meningotype_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotyping of Neisseria meningitidis assemblies (tools: meningotype)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"starfusion/build": "Download STAR-fusion genome resource required to run STAR-Fusion caller", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "meningotype": "Serotyping of Neisseria meningitidis assemblies", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "vsearch/sintax": "Taxonomic classification using the sintax algorithm."}}, "target": "meningotype", "target_idx": 2}
{"id": "schema_std_metaboigniter_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/metaboigniter. Description: Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/metaboigniter.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,seq_data,pbi,start_from": null, "sample,type,level,msfile": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null}}, "target": "sample,type,level,msfile", "target_idx": 2}
{"id": "local_subworkflow_daisribosome_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should DAISRIBOSOME (dais) be built?", "criteria": {"Local subworkflow DAISRIBOSOME": null, "Use nf-core subworkflow daisribosome": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 0}
{"id": "pipe_all101_genomeqc_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Compare the quality of multiple genomes, along with their annotations.. Topics: genome-assembly-evaluation, genomics, phylogenetic-trees, quality-control. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti"}}, "target": "genomeqc", "target_idx": 5}
{"id": "samplesheet_arch_bulk_wes_pe_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Paired-end Whole Exome Sequencing (WES) target capture. Input files: Paired-end FASTQs from Agilent/Twist exome target capture.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Whole Exome Sequencing (WES) target capture with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_3_1", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "template": "nf-core/eager"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment with entry step FASTQC.", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_3_0", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 16S rRNA / ITS microbiome amplicon profiling with entry step FASTQC.", "criteria": {"sample,fasta": null, "sample,otu_table": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bamaligncleaner_4", "category": "resource_profiling", "state": {"process": "BAMALIGNCLEANER", "tool": "bamaligncleaner", "description": "removes unused references from header of sorted BAM/CRAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMALIGNCLEANER (removes unused references from header of sorted BAM/CRAM files.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedtools_coverage_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COVERAGE", "tool": "bedtools/coverage", "description": "computes both the depth and breadth of coverage of features in file B on the features in file A"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COVERAGE (computes both the depth and breadth of coverage of features in file B on the fea) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_deepmased_features_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepMAsED features subcommand: extracts alignment-based features from BAM and assembly FASTA for each contig, producing feature tables used as input for DeepMAsED predict. (tools: deepmased)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "metamdbg/asm": "Metagenome assembler for long-read sequences (HiFi and ONT).", "vsearch/sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).", "deepmased/features": "DeepMAsED features subcommand: extracts alignment-based features from BAM and assembly FASTA for each contig, "}}, "target": "deepmased/features", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_1_40", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "intent_debug_error_5", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "ask_question": null, "prepare_data": null}}, "target": "debug_error", "target_idx": 1}
{"id": "noul_channel_collect_operator_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_traitar_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Traitar3 - predict microbial phenotypes from genomic sequences using protein families (tools: traitar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngmaster": null, "gfaffix": null, "traitar/pfamget": null, "traitar/run": null, "deeparg/predict": null}}, "target": "traitar/run", "target_idx": 3}
{"id": "mod_minibwa_map_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align fastq reads to a fasta reference using minibwa (tools: minibwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_train": null, "bbmap_index": null, "popscle_freemuxlet": null, "bbmap_bbsplit": null, "minibwa_map": null}}, "target": "minibwa_map", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_0_48", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_1_2", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "intent_prepare_data_19", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "prepare_data": null, "build_pipeline": null, "ask_question": null}}, "target": "prepare_data", "target_idx": 1}
{"id": "mod_picard_sortvcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts vcf files (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler/merge": "Merge multiple coolers with identical axes", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "picard/sortvcf": "Sorts vcf files", "diamond/cluster": "calculate clusters of highly similar sequences", "crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs"}}, "target": "picard/sortvcf", "target_idx": 2}
{"id": "field_constraint_bai_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "field_constraint_bai_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "schema_std_rnadnavar_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnadnavar", "description": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnadnavar?", "criteria": {"fasta,assembly,ncbi,gff,fastq": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 2}
{"id": "mod_catpack_summarise_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarises results from CAT/BAT/RAT classification steps (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gtdbtk_classifywf": null, "catpack_summarise": null, "upp_align": null, "riker_multi": null, "catpack_bins": null}}, "target": "catpack_summarise", "target_idx": 1}
{"id": "mod_riker_multi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run multiple riker collectors in a single BAM pass using riker multi. Specify\ntools via ext.args (e.g. '--tools alignment basic isize'). The wgs, gcbias, and\nerror tools require a reference FASTA; the hybcap tool requires baits and targets. (tools: riker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond_makedb": "Builds a DIAMOND database", "bam_rseqc": "Subworkflow to run multiple commands in the RSeqC package", "bamclipper": "This module is used to clip primer sequences from your alignments.", "riker_multi": "Run multiple riker collectors in a single BAM pass using riker multi. Specify\ntools via ext.args (e.g. '--tool", "atlas_splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "riker_multi", "target_idx": 3}
{"id": "mod_angsd_docounts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates base frequency statistics across reference positions from BAM. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd/docounts": "Calculates base frequency statistics across reference positions from BAM.", "allelecounter": "Generates a count of coverage of alleles", "angsd/dosaf": "Estimate site allele frequencies from BAM files.", "angsd/contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome.", "vcf_annotate_ensemblvep": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file"}}, "target": "angsd/docounts", "target_idx": 0}
{"id": "mod_islandpath_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genomic island prediction in bacterial and archaeal genomes (tools: islandpath)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metabuli_build": "Builds a database for classification with metabuli from FASTA files and a taxonomy", "islandpath": "Genomic island prediction in bacterial and archaeal genomes", "gangstr": "GangSTR is a tool for genome-wide profiling tandem repeats from short reads.", "rundbcan_easysubstrate": "Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzyme", "rundbcan_easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ"}}, "target": "islandpath", "target_idx": 1}
{"id": "mod_picard_setnmmdanduqtags_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool takes in a coordinate-sorted SAM or BAM and calculatesthe NM, MD, and UQ tags by comparing with the reference. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_setnmmdanduqtags": "This tool takes in a coordinate-sorted SAM or BAM and calculatesthe NM, MD, and UQ tags by comparing with the ", "igv_js": "igv.js is an embeddable interactive genome visualization component", "instrain_profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "picard_setnmmdanduqtags", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_32", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_baysor_segfree_0", "category": "resource_profiling", "state": {"process": "BAYSOR_SEGFREE", "tool": "baysor/segfree", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_SEGFREE (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_repeatmodeler_repeatmodeler_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs de novo transposable element (TE) family identification with RepeatModeler (tools: repeatmodeler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"repeatmodeler_repeatmodeler": "Performs de novo transposable element (TE) family identification with RepeatModeler", "topas_gencons": "Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage presen", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "quantmsutils_mzmlstatistics": "Generate statistics from mzML files using quantms-utils", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "repeatmodeler_repeatmodeler", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bigscape_bigscape_3", "category": "resource_profiling", "state": {"process": "BIGSCAPE_BIGSCAPE", "tool": "bigscape/bigscape", "description": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSCAPE_BIGSCAPE (BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clust) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_2_0", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_gatk4_haplotypecaller_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call germline SNPs and indels via local re-assembly of haplotypes (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety_esm2": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety.", "gatk4_haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "bwa_index": "Create BWA index for reference genome", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "gatk4_haplotypecaller", "target_idx": 1}
{"id": "resource_bamreadcount_3", "category": "resource_profiling", "state": {"process": "BAMREADCOUNT", "tool": "bamreadcount", "description": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMREADCOUNT (bam-readcount is a utility that runs on a BAM or CRAM file and generates low-lev) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bases2fastq_4", "category": "resource_profiling", "state": {"process": "BASES2FASTQ", "tool": "bases2fastq", "description": "Demultiplex Element Biosciences bases files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASES2FASTQ (Demultiplex Element Biosciences bases files) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "local_subworkflow_irma_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should IRMA (irma) be built?", "criteria": {"Local subworkflow IRMA": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow irma": null}}, "target": "Local subworkflow IRMA", "target_idx": 0}
{"id": "resource_ataqv_mkarv_5", "category": "resource_profiling", "state": {"process": "ATAQV_MKARV", "tool": "ataqv/mkarv", "description": "mkarv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_MKARV (mkarv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_krakentools_extractkrakenreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract reads classified at any user-specified taxonomy IDs. (tools: krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/build": "Extends a Kraken2 database to be compatible with Bracken", "krakentools/extractkrakenreads": "Extract reads classified at any user-specified taxonomy IDs.", "gatk4/mergemutectstats": "Merges mutect2 stats generated on different intervals/regions", "kraken2/build": "Builds Kraken2 database", "biohansel": "Use k-mers to rapidly subtype S. enterica genomes"}}, "target": "krakentools/extractkrakenreads", "target_idx": 1}
{"id": "mod_metaphlan_makedb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build MetaPhlAn database for taxonomic profiling. (tools: metaphlan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "concoct_concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "bbmap_bbmerge": "Merging overlapping paired reads into a single read.", "metaphlan_makedb": "Build MetaPhlAn database for taxonomic profiling.", "bcftools_index": "Index VCF tools"}}, "target": "metaphlan_makedb", "target_idx": 3}
{"id": "field_constraint_status_1_13", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "mod_truvari_consistency_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Over multiple vcfs, calculate their intersection/consistency. (tools: truvari)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"savana/cna": "Copy-number aberration calling with SAVANA for long-read tumour/normal alignments.", "dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "seqtk/cutn": "Generates a BED file containing genomic locations of lengths of N.", "caddsv/get": "Download CADD-SV annotation resources or SegmentNT model files.", "truvari/consistency": "Over multiple vcfs, calculate their intersection/consistency."}}, "target": "truvari/consistency", "target_idx": 4}
{"id": "pipe_all101_spatialaxe_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for 10x-genomics. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]"}}, "target": "spatialaxe", "target_idx": 6}
{"id": "samplesheet_arch_prealigned_cram_indexed_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Genome analysis from reference-compressed CRAM files. Input files: Coordinate-sorted CRAM alignments with companion CRAI indexes.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Genome analysis from reference-compressed CRAM files.", "criteria": {"sample,cram": null, "sample,bam,bai": null, "sample,vcf": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "resource_bamtofastq10x_1", "category": "resource_profiling", "state": {"process": "BAMTOFASTQ10X", "tool": "bamtofastq10x", "description": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Long Ranger back to FASTQ files that can be used as inputs to re-run analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOFASTQ10X (Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bcftools_filter_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_FILTER", "tool": "bcftools/filter", "description": "Filters VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_FILTER (Filters VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_vardictjava_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Java port of the VarDict variant caller (tools: vardictjava)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"force/tileextent": null, "bcftools/call": null, "atlas/call": null, "bedops/convert2bed": null, "vardictjava": null}}, "target": "vardictjava", "target_idx": 4}
{"id": "samplesheet_arch_ampliseq_its_fungal_0_3", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Long-read Oxford Nanopore environmental metagenomic sequencing)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "resource_bcftools_roh_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROH", "tool": "bcftools/roh", "description": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROH (A program for detecting runs of homo/autozygosity. Only bi-allelic sites are con) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_metamaps_mapdirectly_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Maps long reads to a metamaps database (tools: metamaps)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamaps_mapdirectly": "Maps long reads to a metamaps database", "catpack_reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "mosdepth": "Calculates genome-wide sequencing coverage.", "catpack_bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "hisat2_extractsplicesites": "Extracts splicing sites from a gtf files"}}, "target": "metamaps_mapdirectly", "target_idx": 0}
{"id": "mod_bcftools_pluginscatter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split VCF by chunks or regions, creating multiple VCFs. (tools: pluginscatter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss_extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "bcftools_pluginscatter": "Split VCF by chunks or regions, creating multiple VCFs.", "gatk4_mergevcfs": "Merges several vcf files", "picard_scatterintervalsbyns": "Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into inte"}}, "target": "bcftools_pluginscatter", "target_idx": 2}
{"id": "schema_std_genomeassembler_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "description": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/genomeassembler?", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "sample,group,ref_fasta,ref_gff,use_ref", "target_idx": 3}
{"id": "mod_khmer_normalizebymedian_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module that calls normalize-by-median.py from khmer. The module can take a mix of paired end (interleaved) and single end reads. If both types are provided, only a single file with single ends is possible. (tools: khmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA", "khmer/uniquekmers": "In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more", "khmer/normalizebymedian": "Module that calls normalize-by-median.py from khmer. The module can take a mix of paired end (interleaved) and", "khmer/trimlowabund": "Removes low abundance k-mers from FASTA/FASTQ files", "bbmap/bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously"}}, "target": "khmer/normalizebymedian", "target_idx": 2}
{"id": "mod_bam_vcf_impute_glimpse2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow\ntakes VCF files, phased reference panel, and genetic maps to perform imputation\nand outputs phased and imputed VCF files.\nMeta map of all channels, except ch_input, will be used to perform joint operations.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: bam_vcf_impute_glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools/stats": "Calculate pairs statistics", "bam_vcf_impute_glimpse2": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow\ntakes VCF files, phased ref", "tidk/plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "glimpse2/concordance": "Program to compute the genotyping error rate at the sample or marker level.", "glimpse/phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods"}}, "target": "bam_vcf_impute_glimpse2", "target_idx": 1}
{"id": "mod_sourcepredict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classifies and predicts the origin of metagenomic samples (tools: sourcepredict)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourcepredict": null, "biomformat/convert": null, "argnorm": null, "vcf_impute_beagle5": null, "plink2/vcf": null}}, "target": "sourcepredict", "target_idx": 0}
{"id": "mod_endorspy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: endorS.py calculates endogenous DNA from samtools flagstat files and print to screen (tools: endorspy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen", "sylph/profile": "Sylph profile command for taxonoming profiling", "leehom": "Bayesian reconstruction of ancient DNA fragments", "malt/build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "hmmer/hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile"}}, "target": "endorspy", "target_idx": 0}
{"id": "mod_sratools_fasterqdump_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA). (tools: sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sratools_fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA).", "salmon_index": "Create index for salmon", "fastqutils_info": "Performs quality control of FASTQ files", "genomad_endtoend": "Identify mobile genetic elements present in genomic assemblies", "artic_aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}}, "target": "sratools_fasterqdump", "target_idx": 0}
{"id": "intent_prepare_data_22", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "prepare_data", "target_idx": 2}
{"id": "resource_bio2zarr_vcf2zarrconvert_4", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARRCONVERT", "tool": "bio2zarr/vcf2zarrconvert", "description": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARRCONVERT (Convert VCF data to the VCF Zarr specification reliably, in parallel or distribu) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_regenie_runl0_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run one REGENIE step 1 level-0 job from a split master file (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"admixture": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datas", "resfinder/run": "ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteri", "regenie/runl0": "Run one REGENIE step 1 level-0 job from a split master file", "pbsv/discover": "pbsv - PacBio structural variant (SV) signature discovery tool", "regenie/step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions"}}, "target": "regenie/runl0", "target_idx": 2}
{"id": "mod_gatk4_modelsegments_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts copy number ratios (and optonally allelic counts) to copy number segments (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_denoisereadcounts": "Denoises read counts to produce denoised copy ratios", "anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "krona_kronadb": "KronaTools Update Taxonomy downloads a taxonomy database", "gatk4_modelsegments": "Converts copy number ratios (and optonally allelic counts) to copy number segments", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "gatk4_modelsegments", "target_idx": 3}
{"id": "noul_channel_mix_operator_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_filter_bcftools_ensemblvep_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_FILTER_BCFTOOLS_ENSEMBLVEP", "modules": ["bcftools/view", "ensemblvep/filtervep", "htslib/bgziptabix"], "description": "Filter VCF file with bcftools and filter_vep"}, "question": {"type": "choice", "instructions": "How should VCF_FILTER_BCFTOOLS_ENSEMBLVEP (bcftools/view, ensemblvep/filtervep, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Local subworkflow VCF_FILTER_BCFTOOLS_ENSEMBLVEP": null, "Leave them out": null, "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep", "target_idx": 2}
{"id": "resource_annosine_1", "category": "resource_profiling", "state": {"process": "ANNOSINE", "tool": "annosine", "description": "Accelerating de novo SINE annotation in plant and animal genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOSINE (Accelerating de novo SINE annotation in plant and animal genomes) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_21", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_all101_mhcquant_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Identify and quantify MHC eluted peptides from mass spectrometry raw data. Topics: dda, immunopeptidomics, mass-spectrometry, mhc, openms, peptides. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous"}}, "target": "mhcquant", "target_idx": 2}
{"id": "mod_gridss_generateponbedpe_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss_call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment", "gridss_extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "gridss_generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "deeptools_bigwigcompare": "Compare two bigWig files based on the number of mapped reads", "oarfish_alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje"}}, "target": "gridss_generateponbedpe", "target_idx": 2}
{"id": "schema_std_tfactivity_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tfactivity", "description": "Bioinformatics pipeline that makes use of expression and open chromatin data to identify differentially active transcription factors across conditions.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/tfactivity?", "criteria": {"sample_id,bam,vcf,library_id,lane": null, "sample,condition,assay,peak_file,footprinting": null, "sample,seed": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "sample,condition,assay,peak_file,footprinting", "target_idx": 1}
{"id": "mod_bcftools_isec_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply set operations to VCF files (tools: isec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/isec": null, "mmseqs_fasta_cluster": null, "parabricks/genotypegvcf": null, "aardvark/compare": null, "bcftools/consensus": null}}, "target": "bcftools/isec", "target_idx": 0}
{"id": "intent_build_pipeline_4", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "build_pipeline", "target_idx": 2}
{"id": "pipe_all101_rnafusion_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze RNA-seq analysis pipeline for detection of gene-fusions. Topics: fusion, fusion-genes, gene-fusion, rna, rna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data."}}, "target": "rnafusion", "target_idx": 1}
{"id": "pipe_all101_isoseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for isoseq analysis? Specific context: Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences and produce a bed annotation.. Topics: isoseq, isoseq-3, rna, tama, ultra. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]"}}, "target": "isoseq", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_27", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_24", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_process_conditional_execution_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_chromograph_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Chromograph is a python package to create PNG images from genetics data such as BED and WIG files. (tools: chromograph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files.", "hifitrimmer/processblast": "Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrima", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "cooler/balance": "Run matrix balancing on a cool file"}}, "target": "chromograph", "target_idx": 0}
{"id": "pipe_all101_methylong_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Extract methylation calls from long reads (ONT/ PacBio). Topics: dna-methylation, fiber-seq, long-read, ont, pacbio. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeassembler": null, "hicar": null, "scnanoseq": null, "methylong": null, "eager": null, "proteogenomicsdb": null, "circdna": null, "chipseq": null, "createpanelrefs": null, "spatialaxe": null}}, "target": "methylong", "target_idx": 3}
{"id": "noul_workflow_completion_lifecycle_hook_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_minimap2_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides fasta index required by minimap2 alignment. (tools: minimap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamreadcount": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencin", "minimap2/index": "Provides fasta index required by minimap2 alignment.", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "bam_impute_quilt": "Subworkflow to impute BAM files using QUILT software.\nVariants location to impute are obtain through the tsv f", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}}, "target": "minimap2/index", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_bwa_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWA", "modules": ["bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bwa then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWA (bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_bwa": null, "Local subworkflow FASTQ_ALIGN_BWA": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_bwa", "target_idx": 0}
{"id": "mod_bases2fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Element Biosciences bases files (tools: bases2fastq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_telomere_estimation": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter", "bases2fastq": "Demultiplex Element Biosciences bases files", "manta_germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "fqtk": "Demultiplex fastq files"}}, "target": "bases2fastq", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Long-read Oxford Nanopore environmental metagenomic sequencing", "data_format": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Oxford Nanopore environmental metagenomic sequencing with entry step NANOPLOT.", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "mod_csvtk_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort  CSV (or TSV) tables (tools: csvtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vrhyme_extractunbinned": "Extracting sequences that were unbinnned by vRhyme into a FASTA file", "csvtk_sort": "Sort  CSV (or TSV) tables", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "elprep_filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "pairtools_restrict": "Assign restriction fragments to pairs"}}, "target": "csvtk_sort", "target_idx": 1}
{"id": "mod_atlas_splitmerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: split single end read groups by length and merge paired end reads (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio_splitbed": "Split features in gzipped BED format", "irescue": "Quantification of transposable elements expression in scRNA-seq", "finaletoolkit_endmotifs": "Measure the frequency of 5' k-mer end motifs.", "csvtk_split": "Splits CSV/TSV into multiple files according to column values", "atlas_splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "atlas_splitmerge", "target_idx": 4}
{"id": "resource_biobambam_bammerge_3", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMERGE", "tool": "biobambam/bammerge", "description": "Merge a list of sorted bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMERGE (Merge a list of sorted bam files) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_deseq2_differential_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: runs a differential expression analysis with DESeq2 (tools: deseq2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"limma_differential": "runs a differential expression analysis with Limma", "deseq2_differential": "runs a differential expression analysis with DESeq2", "propr_propd": "Perform differential proportionality analysis", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "pairtools_merge": "Merge multiple pairs/pairsam files"}}, "target": "deseq2_differential", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_39", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_khmer_trimlowabund_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes low abundance k-mers from FASTA/FASTQ files (tools: khmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco/plot": null, "gapseq/doall": null, "busco/download": null, "khmer/trimlowabund": null, "clippy": null}}, "target": "khmer/trimlowabund", "target_idx": 3}
{"id": "mod_memote_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run memote test suite and collect results as JSON (tools: memote)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pycoqc": "write your description here", "memote_run": "Run memote test suite and collect results as JSON", "gapseq_fill": "Perform gap filling on draft metabolic model", "carveme_carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "rtgtools_rocplot": "Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI is"}}, "target": "memote_run", "target_idx": 1}
{"id": "subworkflow_pkg_bam_tumor_only_somatic_variant_calling_gatk_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a single tumor sample using mutect2 tumor only mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Local subworkflow BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk", "target_idx": 2}
{"id": "schema_std_ribomsqc_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ribomsqc", "description": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/ribomsqc?", "criteria": {"sample,fastq_1,fastq_2,replicate,antibody": null, "id,raw_file": null, "sample,bam,pbi,fail,repeat_id": null, "patient,sample,vcf,status,cna": null}}, "target": "id,raw_file", "target_idx": 1}
{"id": "pipe_all101_methylseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair. Topics: bisulfite-sequencing, dna-methylation, em-seq, epigenome, epigenomics, methyl-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"atacseq": null, "smrnaseq": null, "methylseq": null, "proteinfamilies": null, "rnasplice": null, "viralrecon": null, "dualrnaseq": null, "diaproteomics": null, "pacvar": null, "cutandrun": null}}, "target": "methylseq", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq with entry step FASTQC.", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null, "sample,well,fastq": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_amulety_translate_3", "category": "resource_profiling", "state": {"process": "AMULETY_TRANSLATE", "tool": "amulety/translate", "description": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_TRANSLATE (A module to translate BCR and TCR nucleotide sequences into amino acid sequences) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_angsd_contamination_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "bwamem3_index": "Create bwa-mem3 index for reference genome", "angsd_contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome.", "angsd_docounts": "Calculates base frequency statistics across reference positions from BAM."}}, "target": "angsd_contamination", "target_idx": 3}
{"id": "pipe_all101_scrnaseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for 10x-genomics analysis? Specific context: Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection. Topics: 10x-genomics, 10xgenomics, alevin, bustools, cellranger, kallisto. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "seqsubmit": "nf-core pipeline for data submission to ENA", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "scrnaseq", "target_idx": 7}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "assay_type": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "data_format": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 1}
{"id": "subworkflow_pkg_bam_applybqsr_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_APPLYBQSR", "modules": ["gatk4/applybqsr", "samtools/merge"], "description": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using"}, "question": {"type": "choice", "instructions": "How should BAM_APPLYBQSR (gatk4/applybqsr, samtools/merge) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_APPLYBQSR": null, "Use nf-core subworkflow bam_applybqsr": null}}, "target": "Use nf-core subworkflow bam_applybqsr", "target_idx": 3}
{"id": "schema_std_methylarray_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylarray", "description": "Process methylation data from Illumina arrays. Pre-processing, quality checks, confounder check and DMPs (differentially methylated positions) and DMRs (differentially methylated regions). Optionally estimates cell type composition and adjusts data for it.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/methylarray?", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample_id,idat_red,idat_green,group": null, "id,fasta": null}}, "target": "sample_id,idat_red,idat_green,group", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_3_2", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_blat_0", "category": "resource_profiling", "state": {"process": "BLAT", "tool": "blat", "description": "Queries a sequence subject"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAT (Queries a sequence subject) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_channel_mix_operator_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_arcane_filter_5", "category": "resource_profiling", "state": {"process": "ARCANE_FILTER", "tool": "arcane/filter", "description": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCANE_FILTER (Filter GTF annotations and genome sequence for alignment-free single-cell RNA-se) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_scrna_multiome_0_1", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "mod_ngmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merging paired-end reads and removing sequencing adapters. (tools: ngmerge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr/normalize": null, "ngmerge": null, "pypgx/preparedepthofcoverage": null, "segemehl/index": null, "bedtools/sort": null}}, "target": "ngmerge", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_8", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_16", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_7_2", "category": "samplesheet_schema", "state": {"technology": "Spatial Transcriptomics", "workflow_entry": "FASTQC", "library_inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,image": null, "sample,image": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "resource_aardvark_compare_3", "category": "resource_profiling", "state": {"process": "AARDVARK_COMPARE", "tool": "aardvark/compare", "description": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_COMPARE (A tool to evaluate variant calling performance by comparing a query VCF against ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_5_4", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/dualrnaseq, determine the input samplesheet column structure for: Dual RNA-seq simultaneous host and pathogen transcriptomics.", "criteria": {"sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 1}
{"id": "mod_xeniumranger_relabel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xeniumranger_importsegmentation": "The xeniumranger importsegmentation module runs `xeniumranger import-segmentation`\nto recompute Xenium Onboard", "pairtools_dedup": "Find and remove PCR/optical duplicates", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "xeniumranger_relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts.", "svtk_vcf2bed": "Converts VCFs containing structural variants to BED format"}}, "target": "xeniumranger_relabel", "target_idx": 3}
{"id": "noul_subworkflow_structural_blocks_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_0_1", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,status,bam,bai": null, "sample,bam,bai": null, "patient,sample,bam": null, "sample,vcf": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "resource_biscuit_qc_3", "category": "resource_profiling", "state": {"process": "BISCUIT_QC", "tool": "biscuit/qc", "description": "Perform basic quality control on a BAM file generated with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_QC (Perform basic quality control on a BAM file generated with Biscuit) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_syri_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements. (tools: syri)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "syri": "Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearran", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "quant_tximport_summarizedexperiment": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedEx", "hmmer_hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile"}}, "target": "syri", "target_idx": 1}
{"id": "mod_fgbio_callduplexconsensusreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same double-stranded source molecule. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_printreads": "Print reads in the SAM/BAM/CRAM file", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "vcf_annotate_ensemblvep": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file", "fgbio_groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub"}}, "target": "fgbio_callduplexconsensusreads", "target_idx": 4}
{"id": "samplesheet_arch_spatial_xenium_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Xenium in situ subcellular spatial RNA transcriptomics. Input files: Xenium output bundle with transcripts CSV, cell polygons, and morphology images.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "resource_antismash_antismashlite_1", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITE", "tool": "antismash/antismashlite", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITE (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_last_dotplot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Makes a dotplot (Oxford Grid) of pair-wise sequence alignments (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_lastdb": "Prepare sequences for subsequent alignment with lastal.", "seqtk_cutn": "Generates a BED file containing genomic locations of lengths of N.", "last_lastal": "Aligns query sequences to target sequences indexed with lastdb", "parsnp": "Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection.", "last_dotplot": "Makes a dotplot (Oxford Grid) of pair-wise sequence alignments"}}, "target": "last_dotplot", "target_idx": 4}
{"id": "noul_executor_support_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Multiplexed Oxford Nanopore run with barcode demultiplexing)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multiplexed Oxford Nanopore run with barcode demultiplexing with entry step NANOPLOT.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "mod_tmb_pytmb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool. (tools: tmb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"taxonkit_name2taxid": "Convert taxon names to TaxIds", "openms_idscoreswitcher": "Switches between different scores of peptide or protein hits in identification data", "genometester4_glistmaker": "Create and count k-mer lists from nucelotide sequences.", "tmb_pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "refsolver_score": "Score a query sequence dictionary against a reference using ref-solver"}}, "target": "tmb_pytmb", "target_idx": 3}
{"id": "mod_viber_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multisample subclonal deconvolution of cancer genome sequencing data. (tools: viber)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mobster": "Subclonal deconvolution of cancer genome sequencing data.", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq", "gtdbtk/gtdbtoncbimajorityvote": "Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy", "pypgx/preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "viber": "Multisample subclonal deconvolution of cancer genome sequencing data."}}, "target": "viber", "target_idx": 4}
{"id": "field_constraint_expected_cells_2_4", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"enum: [auto, single, paired]": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_4_2", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs?", "criteria": {"sample,otu_table": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_37", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_tabix_bgziptabix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix index (tools: tabix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_epistasis": "Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others.", "fastq_subsample_fq_salmon": "Subsample fastq", "samtools_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "fasta_bgzip_index_dict_samtools": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA f", "tabix_bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde"}}, "target": "tabix_bgziptabix", "target_idx": 4}
{"id": "samplesheet_arch_metatranscriptome_denovo_0_3", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "template": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 2}
{"id": "mod_gatk4_bedtointervallist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates an interval list from a bed file and a reference dict (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_fetch_clean_hostile": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "gatk4_bedtointervallist": "Creates an interval list from a bed file and a reference dict", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "biscuit_align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit."}}, "target": "gatk4_bedtointervallist", "target_idx": 2}
{"id": "mod_rclone_copy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy files or directories between local and/or remote storage using Rclone (tools: rclone)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone/check": "Check that files in source and destination paths match", "muscle5/super5": "Muscle is a program for creating multiple alignments of amino acid or nucleotide sequences. This particular mo", "rclone/copy": "Copy files or directories between local and/or remote storage using Rclone", "rclone/checksum": "Check files in a destination path against a checksum SUM file", "checkm2/predict": "CheckM2 bin quality prediction"}}, "target": "rclone/copy", "target_idx": 2}
{"id": "local_subworkflow_prepontreads_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPONTREADS (porechop, nanoplot).", "criteria": {"Use nf-core subworkflow prepontreads": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPONTREADS": null, "Leave them out": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 2}
{"id": "mod_coptr_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexes a directory of fasta files for use with CoPTR (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_create_umi_consensus_fgbio": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads\nconvert them to unmapped B", "coptr_estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "coptr_index": "Indexes a directory of fasta files for use with CoPTR", "mitohifi_mitohifi": "A python workflow that assembles mitogenomes from Pacbio HiFi reads"}}, "target": "coptr_index", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_4_1", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,bam": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "subworkflow_pkg_cache_download_ensemblvep_snpeff_0", "category": "subworkflow_packaging", "state": {"subworkflow": "CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "snpeff/download"], "description": "downlad annotation cache for snpeff and ensemblvep"}, "question": {"type": "choice", "instructions": "How should CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF (ensemblvep/download, snpeff/download) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow cache_download_ensemblvep_snpeff": null}}, "target": "Use nf-core subworkflow cache_download_ensemblvep_snpeff", "target_idx": 3}
{"id": "field_constraint_bai_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_44", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "schema_std_eager_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "description": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/eager?", "criteria": {"sample,fastq_1,fastq_2,fasta,run_accession": null, "id,test_vcf,test_regions,caller,subsample": null, "sample_id,bam,vcf,library_id,lane": null, "id,fasta": null}}, "target": "sample_id,bam,vcf,library_id,lane", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_29", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_40", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic tumor-normal calling from pre-aligned BAM files. Input files: Coordinate-sorted BAMs with index for tumor and normal samples.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "sample,vcf": null, "patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "resource_annotsv_installannotations_2", "category": "resource_profiling", "state": {"process": "ANNOTSV_INSTALLANNOTATIONS", "tool": "annotsv/installannotations", "description": "Install the AnnotSV annotations"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_INSTALLANNOTATIONS (Install the AnnotSV annotations) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_biscuit_index_2", "category": "resource_profiling", "state": {"process": "BISCUIT_INDEX", "tool": "biscuit/index", "description": "Indexes a reference genome for use with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_INDEX (Indexes a reference genome for use with Biscuit) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_kraken2_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds Kraken2 database (tools: kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "emboss/revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "kraken2/build": "Builds Kraken2 database", "gridss/extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken."}}, "target": "kraken2/build", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_36", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_mashmap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mashmap is an approximate long read or contig mapper based on Jaccard similarity (tools: mashmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigslice/bigslice": null, "krakenuniq/download": null, "biscuit/bsconv": null, "mashmap": null, "mirdeep2/mapper": null}}, "target": "mashmap", "target_idx": 3}
{"id": "mod_soupx_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.\n\nThe filtered counts are preprocessed with Seurat (LogNormalize, PCA, kNN graph, clustering) to\nprovide cluster assignments to SoupX, which then estimates per-cluster contamination and adjusts\ncounts. The adjusted counts are written to the output H5AD as an `ambient` layer. (tools: soupx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "anndata/barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "soupx": "Estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.\n\nThe filtere", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file"}}, "target": "soupx", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_24", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_27", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_15", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "subworkflow_pkg_quant_tximport_summarizedexperiment_3", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT", "modules": ["custom/tx2gene", "tximeta/tximport", "summarizedexperiment/summarizedexperiment"], "description": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT (custom/tx2gene, tximeta/tximport, summarizedexperiment/summarizedexperiment) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow quant_tximport_summarizedexperiment": null, "Local subworkflow QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT": null, "Leave them out": null}}, "target": "Use nf-core subworkflow quant_tximport_summarizedexperiment", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq with strandedness. Input files: Paired-end FASTQ reads with library strandedness.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "field_constraint_strandedness_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_2_5", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "resource_atlas_pmd_2", "category": "resource_profiling", "state": {"process": "ATLAS_PMD", "tool": "atlas/pmd", "description": "Estimate the post-mortem damage patterns of DNA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_PMD (Estimate the post-mortem damage patterns of DNA) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_samshee_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to validate illumina® Sample Sheet v2 files. (tools: samshee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser/info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "eido/validate": "Validate samplesheet or PEP config against a schema", "parsesdrf/convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration ", "merquryfk/katgc": "A reimplemenation of KatGC to work with FastK databases", "samshee": "Module to validate illumina® Sample Sheet v2 files."}}, "target": "samshee", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_2_28", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_fastq_2_0_6", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "mod_authentict_deam2cont_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use deamination patterns to estimate contamination in single-stranded libraries (tools: authentict)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shasta": null, "proovframe_fix": null, "authentict_deam2cont": null, "damageprofiler": null, "pydamage_analyze": null}}, "target": "authentict_deam2cont", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_clean_fcs_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CLEAN_FCS", "modules": ["fcs/fcsadaptor", "fcsgx/rungx"], "description": "Foreign Contamination Screen (FCS) is a tool suite for identifying and removing contaminant sequences in genome assemblies"}, "question": {"type": "choice", "instructions": "How should FASTA_CLEAN_FCS (fcs/fcsadaptor, fcsgx/rungx) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_CLEAN_FCS": null, "Use nf-core subworkflow fasta_clean_fcs": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_clean_fcs", "target_idx": 1}
{"id": "pipe_all101_scrnaseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection. Topics: 10x-genomics, 10xgenomics, alevin, bustools, cellranger, kallisto. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v"}}, "target": "scrnaseq", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_5_5", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Xenium in situ subcellular spatial RNA transcriptomics.", "criteria": {"sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "mod_krakenuniq_preloadedkrakenuniq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classifies metagenomic sequence data using unique k-mer counts (tools: krakenuniq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scvitools_solo": null, "ganon_classify": null, "haplogrep3_classify": null, "krakenuniq_preloadedkrakenuniq": null, "eggnogmapper": null}}, "target": "krakenuniq_preloadedkrakenuniq", "target_idx": 3}
{"id": "mod_whamg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The wham suite consists of two programs, wham and whamg. wham, the original tool, is a very sensitive method with a high false discovery rate. The second program, whamg, is more accurate and better suited for general structural variant (SV) discovery. (tools: whamg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plotsr": "Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes.", "holodeck/mutate": "Generate a VCF of random mutations from a reference genome with holodeck", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "whamg": "The wham suite consists of two programs, wham and whamg. wham, the original tool, is a very sensitive method w", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "whamg", "target_idx": 3}
{"id": "mod_umitools_group_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Group reads based on their UMI and mapping coordinates (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_dedup_umi": "BAM deduplication with UMI processing for both genome and transcriptome alignments", "umitools/dedup": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "scvitools/solo": "Detect doublets in single-cell RNA-Seq data", "umitools/group": "Group reads based on their UMI and mapping coordinates", "svaba": "SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide "}}, "target": "umitools/group", "target_idx": 3}
{"id": "pipe_all101_multiplesequencealign_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": null, "hic": null, "smrnaseq": null, "chipseq": null, "ampliseq": null, "taxprofiler": null, "proteogenomicsdb": null, "spatialaxe": null, "coproid": null, "rangeland": null}}, "target": "multiplesequencealign", "target_idx": 0}
{"id": "field_constraint_phenotype_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [normal, tumor]": null, "type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "mod_qcat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplexer for Nanopore samples (tools: qcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bclconvert": "Demultiplex Illumina BCL files", "fqtk": "Demultiplex fastq files", "trgt_plot": "Visualize tandem repeats genotyped by TRGT", "qcat": "Demultiplexer for Nanopore samples", "samtools_import": "converts FASTQ files to unmapped SAM/BAM/CRAM"}}, "target": "qcat", "target_idx": 3}
{"id": "subworkflow_pkg_bedgraph_bedclip_bedgraphtobigwig_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG", "modules": ["ucsc/bedclip", "ucsc/bedgraphtobigwig"], "description": "Convert bedgraph to bigwig with clip"}, "question": {"type": "choice", "instructions": "How should BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG (ucsc/bedclip, ucsc/bedgraphtobigwig) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig": null, "Leave them out": null, "Local subworkflow BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig", "target_idx": 0}
{"id": "mod_finaletoolkit_fraglengthbins_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a binned fragment profile and a fragment distribution histogram (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bamsormadup": null, "deeparg_downloaddata": null, "duphold": null, "finaletoolkit_fraglengthbins": null, "paraphrase": null}}, "target": "finaletoolkit_fraglengthbins", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_3_0", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Standard Paired-end Whole Genome Sequencing (WGS) with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_gatk4_svcluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clusters structural variants based on coordinates, event type, and supporting algorithms (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/svcluster": "Clusters structural variants based on coordinates, event type, and supporting algorithms", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "stringtie/merge": "Merges the annotation gtf file and the stringtie output gtf files"}}, "target": "gatk4/svcluster", "target_idx": 0}
{"id": "mod_kraken2_kraken2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classifies metagenomic sequence data (tools: kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_vcf": "Import variant genetic data using plink2", "kraken2_kraken2": "Classifies metagenomic sequence data", "haplogrep3_classify": "classification into haplogroups", "haplogrep2_classify": "classification into haplogroups", "rpbp_selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s"}}, "target": "kraken2_kraken2", "target_idx": 1}
{"id": "mod_spatyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computational method for finding spa types. (tools: spatyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": null, "propr/logratio": null, "yte": null, "amrfinderplus/update": null, "spatyper": null}}, "target": "spatyper", "target_idx": 4}
{"id": "resource_amulety_esm2_3", "category": "resource_profiling", "state": {"process": "AMULETY_ESM2", "tool": "amulety/esm2", "description": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ESM2 (A module to create esm2 embeddings of antibody (BCR) amino acid sequences using ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "assay_type": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "data_format": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,bam": null, "sample,cpg,methylation": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_checkv_updatedatabase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct the database necessary for checkv's quality assessment (tools: checkv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm_lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "picard_meanqualitybycycle": "Collect metrics about the mean quality by cycle of a paired-end library.", "checkm2_predict": "CheckM2 bin quality prediction", "catpack_reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "checkv_updatedatabase": "Construct the database necessary for checkv's quality assessment"}}, "target": "checkv_updatedatabase", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_2", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_picard_cleansam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped reads (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "picard_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "hostile_clean": "Removes host reads from short- and long-read FASTQ sequencing files"}}, "target": "picard_cleansam", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_2_5", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 3}
{"id": "field_constraint_strandedness_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "resource_artic_guppyplex_0", "category": "resource_profiling", "state": {"process": "ARTIC_GUPPYPLEX", "tool": "artic/guppyplex", "description": "Aggregates fastq files with demultiplexed reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_GUPPYPLEX (Aggregates fastq files with demultiplexed reads) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bismark_genomepreparation_5", "category": "resource_profiling", "state": {"process": "BISMARK_GENOMEPREPARATION", "tool": "bismark/genomepreparation", "description": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_GENOMEPREPARATION (Converts a specified reference genome into two different bisulfite\nconverted ver) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gatk4_splitintervals_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split intervals into sub-interval files. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc/inferexperiment": "Infer strandedness from sequencing reads", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "gatk4/splitintervals": "Split intervals into sub-interval files.", "bedtools/getfasta": "extract sequences in a FASTA file based on intervals defined in a feature file.", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "gatk4/splitintervals", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_29", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_48", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bcftools_filter_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_FILTER", "tool": "bcftools/filter", "description": "Filters VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_FILTER (Filters VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_3_0", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Custom MIRA-NF Influenza / SC2 pipeline with entry step INPUT_CHECK.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_bbmap_bbmerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merging overlapping paired reads into a single read. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": null, "adapterremovalfixprefix": null, "bbmap_bbmerge": null, "checkv_updatedatabase": null, "foldseek_easysearch": null}}, "target": "bbmap_bbmerge", "target_idx": 2}
{"id": "mod_numorph_3dunet_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: 3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit. (tools: numorph_3dunet)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"numorph/3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "blobtk/plot": "Creates differing styles of blobplots depending on provided arguments.", "deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell", "gatk4/germlinecnvcaller": "Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPlo"}}, "target": "numorph/3dunet", "target_idx": 0}
{"id": "field_constraint_status_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "field_constraint_expected_cells_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "resource_angsd_soapsnpcalibration_5", "category": "resource_profiling", "state": {"process": "ANGSD_SOAPSNPCALIBRATION", "tool": "angsd/soapsnpcalibration", "description": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_SOAPSNPCALIBRATION (Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality mat) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_cnvkit_reference_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compile a coverage reference from the given files (normal samples). (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples).", "cnvkit_call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number", "viennarna_rnalfold": "calculate locally stable secondary structures of RNAs", "atlas_splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "cnvkit_reference", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_17", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_fgumi_fastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a BAM file to interleaved FASTQ format with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/fastq": "Convert a BAM file to interleaved FASTQ format with fgumi", "ascat": "copy number profiles of tumour cells.", "plink/exclude": "Exclude variant identifiers from plink bfiles", "ska/fasta": "Create genome sketch using split k-mers", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "fgumi/fastq", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_37", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "assay_type": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "data_format": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) input samplesheet?", "criteria": {"sample,cpg,methylation": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_strandedness_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "mod_ale_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ALE: assembly likelihood estimator. (tools: ale)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate_summary": null, "hostile_fetch": null, "ale": null, "cramino": null, "abra2": null}}, "target": "ale", "target_idx": 2}
{"id": "mod_propr_logratio_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transform the data matrix using centered logratio transformation (CLR) or additive logratio transformation (ALR) (tools: propr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr/propr": "Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coeff", "seqtk/seq": "Common transformation operations on FASTA or FASTQ files.", "cooltools/eigscis": "Perform eigen value decomposition on a cooler matrix to calculate compartment signal by finding the eigenvecto", "gridss/extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "propr/logratio": "Transform the data matrix using centered logratio transformation (CLR) or additive logratio transformation (AL"}}, "target": "propr/logratio", "target_idx": 4}
{"id": "resource_bigslice_bigslice_2", "category": "resource_profiling", "state": {"process": "BIGSLICE_BIGSLICE", "tool": "bigslice/bigslice", "description": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenBank format along with an HMM database and produces a SQLite database and FASTA outputs of predicted features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_BIGSLICE (A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nI) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/genomeassembler) for Long-read Pacific Biosciences HiFi sequencing. Input files: Single HiFi BAM or FastQ.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "field_constraint_bam_1_1", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_decontaminate_deacon_hostile_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DECONTAMINATE_DEACON_HOSTILE", "modules": ["hostile/fetch", "hostile/clean", "deacon/index", "deacon/filter", "fastq_fetch_clean_hostile", "fastq_index_filter_deacon"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile"}, "question": {"type": "choice", "instructions": "How should FASTQ_DECONTAMINATE_DEACON_HOSTILE (hostile/fetch, hostile/clean, deacon/index, deacon/filter, fastq_fetch_clean_hostile, fastq_index_filter_deacon) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_DECONTAMINATE_DEACON_HOSTILE": null, "Use nf-core subworkflow fastq_decontaminate_deacon_hostile": null}}, "target": "Use nf-core subworkflow fastq_decontaminate_deacon_hostile", "target_idx": 3}
{"id": "resource_antismash_antismashlitedownloaddatabases_2", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES", "tool": "antismash/antismashlitedownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_sample_0_0", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"enum: [0, 1]": null, "type: integer": null, "format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "mod_paragraph_idxdepth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determines the depth in a BAM/CRAM file (tools: paragraph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paragraph/idxdepth": "Determines the depth in a BAM/CRAM file", "sentieon/bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "bamclipper": "This module is used to clip primer sequences from your alignments.", "pychopper": "Identify, orient and trim nanopore cDNA reads", "ascat": "copy number profiles of tumour cells."}}, "target": "paragraph/idxdepth", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Trio exome/genome sequencing (Proband, Mother, Father))", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Trio exome/genome sequencing (Proband, Mother, Father) with entry step FASTQC.", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "core_tool_mutect2_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Somatic short variant detection (SNVs and small indels) comparing matched tumor and normal sequencing data with Bayesian somatic likelihood filtering.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"strelka2": "Fast somatic caller", "varscan2": "Somatic caller", "somaticsniper": "Somatic SNV caller", "vardict": "Variant caller", "mutect2": "Call somatic SNVs and indels via local assembly of haplotypes with tumor/normal comparison"}}, "target": "mutect2", "target_idx": 4}
{"id": "resource_biscuit_mergecg_1", "category": "resource_profiling", "state": {"process": "BISCUIT_MERGECG", "tool": "biscuit/mergecg", "description": "Merges methylation information for opposite-strand C's in a CpG context"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_MERGECG (Merges methylation information for opposite-strand C's in a CpG context) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_3_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Pacific Biosciences HiFi sequencing with entry step HIFIADAPTERFILT.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_workflow_completion_lifecycle_hook_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_3", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_authentict_deam2cont_3", "category": "resource_profiling", "state": {"process": "AUTHENTICT_DEAM2CONT", "tool": "authentict/deam2cont", "description": "Use deamination patterns to estimate contamination in single-stranded libraries"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTHENTICT_DEAM2CONT (Use deamination patterns to estimate contamination in single-stranded libraries) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_ichorcna_createpon_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, particularly for use in cell-free DNA. This module generates a panel of normals (tools: ichorcna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ichorcna/createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "sageproteomics/sage": "sage is a search software for proteomics data", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "ichorcna/run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti"}}, "target": "ichorcna/createpon", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_49", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "field_constraint_phenotype_1_14", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 1}
{"id": "mod_rrnatranscripts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ribosomal RNA extraction from a GTF file. (tools: rrnatranscripts)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": null, "fastq_remove_rrna": null, "rrnatranscripts": null, "homer_pos2bed": null, "gatk4_denoisereadcounts": null}}, "target": "rrnatranscripts", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_43", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_velocyto_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Velocyto is a library for the analysis of RNA velocity. velocyto.py CLI use\n`Path(resolve_path=True)` and breaks the nextflow logic of symbolic links.\nIf in the work dir velocyto find a file named EXACTLY `cellsorted_[ORIGINAL_BAM_NAME]`\nit will skip the samtools sort step.\nCellsorted bam file should be cell sorted with:\n```bash\n    samtools sort -t CB -O BAM -o cellsorted_input.bam input.bam\n```\nSee module test for an example with the SAMTOOLS_SORT nf-core module.\nConfig example to cellsort input bam using SAMTOOLS_SORT:\n```groovy\n    withName: SAMTOOLS_SORT {\n        ext.prefix = { \"cellsorted_${bam.baseName}\" }\n        ext.args = '-t CB -O BAM'\n    }\n```\nOptional mask must be passed with `ext.args` and option `--mask`\nThis is why I need to stage in the work dir 2 bam files (cellsorted and original).\nSee also [velocyto tutorial](https://velocyto.org/velocyto.py/tutorial/cli.html#notes-on-first-runtime-and-parallelization) (tools: velocyto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI", "bismark_report": "Collects bismark alignment reports", "cellranger_count": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expressi", "htseq_count": "count how many reads map to each feature", "velocyto": "Velocyto is a library for the analysis of RNA velocity. velocyto.py CLI use\n`Path(resolve_path=True)` and brea"}}, "target": "velocyto", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_2_0", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_20", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bcftools_stats_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_STATS", "tool": "bcftools/stats", "description": "Generates stats from VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_STATS (Generates stats from VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wes_pe_6_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Whole Exome Sequencing (WES) target capture input samplesheet?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_7_1", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_cache_download_ensemblvep_snpeff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: downlad annotation cache for snpeff and ensemblvep (tools: cache_download_ensemblvep_snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_annotation_cache": "Check the path to the annotation cache depending if local or on the cloud, or using annotation-cache itself", "snpeff_snpeff": "Genetic variant annotation and functional effect prediction toolbox", "hamronization_summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "cache_download_ensemblvep_snpeff": "downlad annotation cache for snpeff and ensemblvep", "ultraplex": "Ultraplex is an all-in-one software package for processing and demultiplexing fastq files."}}, "target": "cache_download_ensemblvep_snpeff", "target_idx": 3}
{"id": "mod_cooltools_insulation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the diamond insulation scores and call insulating boundaries (tools: cooltools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler/cload": "Create a cooler from genomic pairs and bins", "chromap/chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "cooltools/insulation": "Calculate the diamond insulation scores and call insulating boundaries", "sequenzautils/bam2seqz": "Sequenza-utils bam2seqz process BAM and Wiggle files to produce a seqz file", "doubletdetection": "Doublet detection in single-cell RNA-seq data"}}, "target": "cooltools/insulation", "target_idx": 2}
{"id": "mod_circexplorer2_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate circRNAs detected in the output from CIRCexplorer2 parse (tools: circexplorer2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms/psmfeatureextractor": "Computes extra features for each input PSM for use with Percolator rescoring.", "parabricks/rnafq2bam": "This tool is the equivalent of fq2bam for RNA-Seq samples, receiving inputs in FASTQ format, performing alignm", "fusioncatcher/build": "Build references for fusioncatcher", "quantmsutils/diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils", "circexplorer2/annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse"}}, "target": "circexplorer2/annotate", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_0_7", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_humann3_regroup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Regrouping genes to other functional categories (tools: humann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"humann3_humann": "Functional analysis of metagenome or metatranscriptome data", "pharokka_pharokka": "Functional annotation of phages", "humann3_regroup": "Regrouping genes to other functional categories", "rpbp_extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "bff": "Generating cell hashing calls from a matrix of count data."}}, "target": "humann3_regroup", "target_idx": 2}
{"id": "resource_bismark_coverage2cytosine_5", "category": "resource_profiling", "state": {"process": "BISMARK_COVERAGE2CYTOSINE", "tool": "bismark/coverage2cytosine", "description": "Relates methylation calls back to genomic cytosine contexts."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_COVERAGE2CYTOSINE (Relates methylation calls back to genomic cytosine contexts.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "core_tool_spades_metaspades_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? De novo assembler specifically optimized for complex microbial metagenomic mixtures, recovering contigs across unequal coverage depths.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"canu": null, "spades_metaspades": null, "unicycler": null, "flye": null, "megahit": null}}, "target": "spades_metaspades", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_13", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_slamdunk_map_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings. (tools: slamdunk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker_classify": "mtDNA deletion and duplication classification downstream of mitosalt", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "deseq2_differential": "runs a differential expression analysis with DESeq2", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "slamdunk_map": "Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings."}}, "target": "slamdunk_map", "target_idx": 4}
{"id": "mod_skesa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble microbial genomes from short-read FASTQ files into contigs in FASTA format using SKESA. (tools: skesa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": null, "abacas": null, "skesa": null, "merquryfk/katcomp": null, "sageproteomics/sage": null}}, "target": "skesa", "target_idx": 2}
{"id": "mod_umitools_group_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Group reads based on their UMI and mapping coordinates (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "umitools_extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "seqkit_seq": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "umitools_group": "Group reads based on their UMI and mapping coordinates", "fastk_fastk": "A fast K-mer counter for high-fidelity shotgun datasets"}}, "target": "umitools_group", "target_idx": 3}
{"id": "mod_fgumi_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts a SAM or BAM file. Several sort orders are available, including coordinate,\nqueryname, and template-coordinate. This is a high-performance replacement for fgbio SortBam. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam/bamsormadup": "Parallel sorting and duplicate marking", "sequenzautils/gcwiggle": "Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggl", "fgumi/sort": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate,\nqueryname, and template-coor", "last/mafswap": "Reorder alignments in a MAF file", "csvtk/sort": "Sort  CSV (or TSV) tables"}}, "target": "fgumi/sort", "target_idx": 2}
{"id": "pipe_all101_demo_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for demo analysis? Specific context: nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos.. Topics: demo, minimal-example, training, tutorial. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training"}}, "target": "demo", "target_idx": 7}
{"id": "mod_bedtools_complement_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "gatk4_createsomaticpanelofnormals": "Create a panel of normals constraining germline and artifactual sites for use with mutect2.", "bam_tumor_only_somatic_variant_calling_gatk": "Perform variant calling on a single tumor sample using mutect2 tumor only mode.\nRun the input bam file through", "bedtools_complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file.", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "bedtools_complement", "target_idx": 3}
{"id": "mod_mageck_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mageck count for functional genomics, reads are usually mapped to a specific sgRNA (tools: mageck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "mageck/count": "mageck count for functional genomics, reads are usually mapped to a specific sgRNA", "bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity", "cellranger/count": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expressi"}}, "target": "mageck/count", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic tumor-normal calling from pre-aligned BAM files. Input files: Coordinate-sorted BAMs with index for tumor and normal samples.", "question": {"type": "choice", "instructions": "Which columns are standard for Somatic tumor-normal calling from pre-aligned BAM files input samplesheet?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,vcf": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "local_subworkflow_checkirma_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should this step (custom/checkirma) be packaged: Custom validation of assembly output?", "criteria": {"Local subworkflow CHECKIRMA": null, "Use nf-core subworkflow checkirma": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_5_3", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: ATAC-seq chromatin accessibility with biological replicates.", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "field_constraint_expected_cells_0_8", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "mod_gecco_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomic and metagenomic data using Conditional Random Fields (CRFs). (tools: gecco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data", "plasmidid": "assembles bacterial plasmids", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "gecco/run": "GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomi", "antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt"}}, "target": "gecco/run", "target_idx": 3}
{"id": "resource_backsub_2", "category": "resource_profiling", "state": {"process": "BACKSUB", "tool": "backsub", "description": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACKSUB (Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_blast_blastp_4", "category": "resource_profiling", "state": {"process": "BLAST_BLASTP", "tool": "blast/blastp", "description": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTP (BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (prot) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_include_modular_process_syntax_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_deprecated_file_output_syntax_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_bam_1_10", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "field_constraint_bam_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "pipe_all101_dualrnaseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous RNA-seq.. Topics: dualrna-seq, host-pathogen, quantification, readmapping, rna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnaseq": null, "atacseq": null, "rnadnavar": null, "seqsubmit": null, "mnaseseq": null, "dualrnaseq": null, "scrnaseq": null, "bactmap": null}}, "target": "dualrnaseq", "target_idx": 5}
{"id": "resource_arriba_visualisation_4", "category": "resource_profiling", "state": {"process": "ARRIBA_VISUALISATION", "tool": "arriba/visualisation", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_VISUALISATION (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_blast_makeblastdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a BLAST database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_makeblastdb": "Builds a BLAST database", "humann3_regroup": "Regrouping genes to other functional categories", "checkm2_predict": "CheckM2 bin quality prediction", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "blast_makeblastdb", "target_idx": 0}
{"id": "mod_porechop_porechop_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adapter removal and demultiplexing of Oxford Nanopore reads (tools: porechop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shovill": null, "propr/propd": null, "hifiadapterfilt/downloaddb": null, "porechop/porechop": null, "artic/aligntrim": null}}, "target": "porechop/porechop", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_30", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "subworkflow_pkg_bam_telomere_estimation_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TELOMERE_ESTIMATION", "modules": ["telseq", "telogator2", "telomerehunter", "custom/summarisetelomereestimation"], "description": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter"}, "question": {"type": "choice", "instructions": "How should BAM_TELOMERE_ESTIMATION (telseq, telogator2, telomerehunter, custom/summarisetelomereestimation) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_TELOMERE_ESTIMATION": null, "Use nf-core subworkflow bam_telomere_estimation": null}}, "target": "Use nf-core subworkflow bam_telomere_estimation", "target_idx": 3}
{"id": "field_constraint_fastq_1_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "resource_anndata_barcodes_0", "category": "resource_profiling", "state": {"process": "ANNDATA_BARCODES", "tool": "anndata/barcodes", "description": "Module to subset AnnData object to cells with matching barcodes from the csv file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_BARCODES (Module to subset AnnData object to cells with matching barcodes from the csv fil) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Visium spatial transcriptomics with histology image)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "mod_umitools_prepareforrsem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make the output from umi_tools dedup or group compatible with RSEM (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "gatk4_germlinecnvcaller": "Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPlo", "custom_tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "umitools_prepareforrsem": "Make the output from umi_tools dedup or group compatible with RSEM", "umitools_group": "Group reads based on their UMI and mapping coordinates"}}, "target": "umitools_prepareforrsem", "target_idx": 3}
{"id": "schema_std_molkart_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/molkart", "assay": "molkart pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/molkart (A pipeline for processing Molecular Cartography data from Re)?", "criteria": {"sample,bundle,image": null, "patient,sample,vcf,status,cna": null, "sample,nuclear_image,spot_table,membrane_image": null, "id,taxid,fasta_dna,fasta_aa": null}}, "target": "sample,nuclear_image,spot_table,membrane_image", "target_idx": 2}
{"id": "mod_parabricks_mutectcaller_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated somatic variant calling, replicating GATK Mutect2. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_mutectcaller": null, "clair3": null, "bio2zarr_vcfpartition": null, "seq2hla": null, "graphtyper_genotype": null}}, "target": "parabricks_mutectcaller", "target_idx": 0}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_1_3", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,host_fasta": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "mod_quilt_quilt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: QUILT is an R and C++ program for rapid genotype imputation from low-coverage sequence using a large reference panel. (tools: quilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse/chunk": "Defines chunks where to run imputation", "seqwish/induce": "Induce a variation graph in GFA format from alignments in PAF format", "csvtk/sort": "Sort  CSV (or TSV) tables", "quilt/quilt": "QUILT is an R and C++ program for rapid genotype imputation from low-coverage sequence using a large reference", "glimpse/phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods"}}, "target": "quilt/quilt", "target_idx": 3}
{"id": "mod_cellrangerarc_mkfastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq command. (tools: cellrangerarc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma", "bowtie_build": "Create bowtie index for reference genome", "bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "hpsuissero": "Serotype prediction of Haemophilus parasuis assemblies", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap"}}, "target": "cellrangerarc_mkfastq", "target_idx": 0}
{"id": "mod_merquryfk_merquryfk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FastK based version of Merqury (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"meryl_count": "A genomic k-mer counter (and sequence utility) with nice features.", "merquryfk_hapmaker": "Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables", "grabix_check": "Checks if the input file is bgzip compressed or not", "gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever ", "merquryfk_merquryfk": "FastK based version of Merqury"}}, "target": "merquryfk_merquryfk", "target_idx": 4}
{"id": "pipe_all101_funcprofiler_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Read-based functional profiling of microbiome sequencing data. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": "Read-based functional profiling of microbiome sequencing data", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]"}}, "target": "funcprofiler", "target_idx": 0}
{"id": "mod_parsnp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection. (tools: parsnp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parsnp": "Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "alignoth": "Creating alignment plots from bam files", "wittyer": "A large variant benchmarking tool analogous to hap.py for small variants.", "fasta_index_methylseq": "Generate index files from reference fasta for bismark, bwameth and bwamem aligners"}}, "target": "parsnp", "target_idx": 0}
{"id": "mod_cellranger_mkfastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/renamesampleinvcf": "changes name of sample in the vcf file", "bowtie/build": "Create bowtie index for reference genome", "trinity": "Assembles a de novo transcriptome from RNAseq reads", "cellranger/mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command.", "biscuit/index": "Indexes a reference genome for use with Biscuit"}}, "target": "cellranger/mkfastq", "target_idx": 3}
{"id": "resource_ampcombi2_cluster_5", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_CLUSTER", "tool": "ampcombi2/cluster", "description": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete using MMseqs2 cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_CLUSTER (A submodule that clusters the merged AMP hits generated from ampcombi2/parsetabl) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_staphscan_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: staphscan is a tool to screen genome assemblies of Staphylococcus aureus (tools: staphscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kleborate": null, "staphscan": null, "sam2lca_analyze": null, "abricate_summary": null, "learnmsa_align": null}}, "target": "staphscan", "target_idx": 1}
{"id": "field_constraint_fastq_2_1_1", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_0_1", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_modular_subworkflow_composition_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_narfmap_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a reference using NARFMAP (tools: narfmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"narfmap/align": null, "shigeifinder": null, "busco/phylogenomics": null, "amps": null, "purecn/normaldb": null}}, "target": "narfmap/align", "target_idx": 0}
{"id": "mod_freyja_variants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: call variant and sequencing depth information of the variant (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja/variants": "call variant and sequencing depth information of the variant", "fastq_decontaminate_deacon_hostile": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile", "delly/call": "Call structural variants", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline", "freyja/demix": "specify the relative abundance of each known haplotype"}}, "target": "freyja/variants", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/diaproteomics) for Data-Independent Acquisition (DIA) quantitative mass spectrometry. Input files: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Data-Independent Acquisition (DIA) quantitative mass spectrometry with entry step INPUT_CHECK.", "criteria": {"sample,peptides_tsv": null, "sample,mzml": null, "sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_8", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bwa_sampe_0", "category": "resource_profiling", "state": {"process": "BWA_SAMPE", "tool": "bwa/sampe", "description": "Convert paired-end bwa SA coordinate files to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMPE (Convert paired-end bwa SA coordinate files to SAM format) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_high", "target_idx": 2}
{"id": "mod_sentieon_dnascope_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DNAscope algorithm performs an improved version of Haplotype variant calling. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/dnascope": null, "plink/exclude": null, "gunc/mergecheckm": null, "sentieon/applyvarcal": null, "sentieon/bwaindex": null}}, "target": "sentieon/dnascope", "target_idx": 0}
{"id": "resource_busco_download_3", "category": "resource_profiling", "state": {"process": "BUSCO_DOWNLOAD", "tool": "busco/download", "description": "Download database for BUSCO"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_DOWNLOAD (Download database for BUSCO) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_43", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "field_constraint_sample_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"type: integer": null, "format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_last_postmask_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Post-alignment masking (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last/postmask": "Post-alignment masking", "last/lastal": "Aligns query sequences to target sequences indexed with lastdb", "fastq_fastqc_umitools_fastp": "Read QC, UMI extraction and trimming", "kma/kma": "Mapping raw reads directly against redundant databases via KMA alignment", "last/mafconvert": "Converts MAF alignments in another format."}}, "target": "last/postmask", "target_idx": 0}
{"id": "schema_std_molkart_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/molkart", "description": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/molkart?", "criteria": {"sample,nuclear_image,spot_table,membrane_image": null, "fastq_1,fastq_2,group,replicate,control": null, "id,fasta,reference,optional_data,template": null, "sample,vcf,tbi": null}}, "target": "sample,nuclear_image,spot_table,membrane_image", "target_idx": 0}
{"id": "mod_fgumi_downsample_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downsample a BAM by UMI family using streaming with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/downsample": "Downsample a BAM by UMI family using streaming with fgumi", "gatk4/preprocessintervals": "Prepares bins for coverage collection.", "hmmer/hmmrank": "R script that scores output from multiple runs of hmmer/hmmsearch", "fgumi/clip": "Clip overlapping reads in a BAM file with fgumi", "fgumi/dedup": "Mark or remove PCR duplicates using UMI information with fgumi"}}, "target": "fgumi/downsample", "target_idx": 0}
{"id": "mod_stranger_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates output files from ExpansionHunter with the pathologic implications of the repeat sizes. (tools: stranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo/merge": "Merge STR profiles into a multi-sample STR profile", "stranger": "Annotates output files from ExpansionHunter with the pathologic implications of the repeat sizes.", "malt/build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "misopy/index": "Build an indexed representation of a GFF for efficient retrieval of genes", "hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data"}}, "target": "stranger", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_4_4", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment?", "criteria": {"lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_container_environment_specification_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_build_pipeline_1", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "ask_question": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_happy_prepy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py (tools: happy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy_happy": "Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row", "bcftools_sort": "Sorts VCF files", "echtvar_anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "happy_prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "truvari_segment": "Normalization of SVs into disjointed genomic regions"}}, "target": "happy_prepy", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_29", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_fgumi_group_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template, and then templates are sorted by the 5' mapping positions\nof the reads from the template. Reads that have the same end positions are then sub-grouped\nby UMI sequence. This is a high-performance replacement for fgbio GroupReadsByUmi. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hackgap_count": "Fast, JIT-compiled k-mer counter supporting both contiguous and gapped k-mers using multi-way bucketed Cuckoo ", "fgumi_group": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "fgbio_groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "snapaligner_align": "Performs fastq alignment to a fasta reference using SNAP"}}, "target": "fgumi_group", "target_idx": 1}
{"id": "mod_krona_ktupdatetaxonomy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KronaTools Update Taxonomy downloads a taxonomy database (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krona/ktupdatetaxonomy": null, "gfatools/gfa2fa": null, "ngsbits/samplegender": null, "blast/makeblastdb": null, "bakta/baktadbdownload": null}}, "target": "krona/ktupdatetaxonomy", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_0_2", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,bam,bai": null, "sample,cram": null, "sample,vcf": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "samplesheet_arch_rare_disease_trio_0_1", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"sample,bam,bai": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_fasta_gxf_busco_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs BUSCO for input assemblies and their annotations in GFF/GFF3/GTF format, and creates summary plots using `busco --plot` (tools: fasta_gxf_busco_plot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangeratac_mkfastq": null, "agat_convertspgff2gtf": null, "samtools_stats": null, "fasta_gxf_busco_plot": null, "agat_convertgff2bed": null}}, "target": "fasta_gxf_busco_plot", "target_idx": 3}
{"id": "resource_bff_5", "category": "resource_profiling", "state": {"process": "BFF", "tool": "bff", "description": "Generating cell hashing calls from a matrix of count data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFF (Generating cell hashing calls from a matrix of count data.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_plink2_het_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate Inbreeding data with plink2 (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/het": "Calculate Inbreeding data with plink2", "gatk4/combinegvcfs": "Combine per-sample gVCF files produced by HaplotypeCaller into a multi-sample gVCF file", "plink2/filter": "Filters plink bfiles or pfiles with filters such as maf or var", "plink2/extract": "Subset plink pfiles with a text file of variant identifiers", "gatk4/filterintervals": "Filters intervals based on annotations and/or count statistics."}}, "target": "plink2/het", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Multiplexed Oxford Nanopore run with barcode demultiplexing. Input files: Nanopore sequencing run with sample to barcode assignment and flowcell type.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,bam": null, "sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "field_constraint_expected_cells_1_3", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "resource_abacas_3", "category": "resource_profiling", "state": {"process": "ABACAS", "tool": "abacas", "description": "Contiguate draft genome assembly"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABACAS (Contiguate draft genome assembly) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral amplicon sequencing with primers. Input files: Paired-end tiled viral amplicon FASTQs per clinical swab sample.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral amplicon sequencing with primers?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_include_modular_process_syntax_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_mmseqs_easysearch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Searches for the sequences of a fasta file in a database using MMseqs2 (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "mmseqs_easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2", "fastq_align_dedup_bwamem": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate", "nacho_qc": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da"}}, "target": "mmseqs_easysearch", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "data_format": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "resource_amulety_balmpaired_0", "category": "resource_profiling", "state": {"process": "AMULETY_BALMPAIRED", "tool": "amulety/balmpaired", "description": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_BALMPAIRED (A module to create BALM paired embeddings of antibody (BCR) amino acid sequences) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_tagbam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool for tagging BAM files. (tools: tagbam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_trim": null, "bcftools_split": null, "tagbam": null, "expansionhunter": null, "autocycler_cluster": null}}, "target": "tagbam", "target_idx": 2}
{"id": "mod_fastk_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to merge FastK histograms (tools: fastk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bammerge": "Merge a list of sorted bam files", "rbt_vcfsplit": "A tool for splitting VCF/BCF files into N equal chunks, including BND support", "fastk_merge": "A tool to merge FastK histograms", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "salmon_index": "Create index for salmon"}}, "target": "fastk_merge", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/chipseq) for ChIP-seq with IP and input control design. Input files: Paired-end FASTQ reads for immunoprecipitation and input chromatin.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ChIP-seq with IP and input control design with entry step FASTQC.", "criteria": {"sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "pipe_all101_mnaseseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for mnase-seq analysis? Specific context: MNase-seq analysis pipeline using BWA and DANPOS2.. Topics: mnase-seq, nucleosome, nucleosome-maps, nucleosome-positioning. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "mnaseseq", "target_idx": 7}
{"id": "noul_invalid_process_communication_via_globals_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_1", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "core_tool_multiqc_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Aggregate and summarize quality control metrics and analysis logs across FastQC, Cutadapt, and STAR into a single interactive HTML report.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"fastp": "All-in-one FASTQ preprocessor", "fastqc": "Quality control tool for high throughput sequence data", "picard": "Command-line tools for manipulating high-throughput sequencing data", "trimmomatic": "Flexible read trimming tool", "multiqc": "Aggregate bioinformatics analysis results across multiple tools into a single report"}}, "target": "multiqc", "target_idx": 4}
{"id": "mod_annosine_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accelerating de novo SINE annotation in plant and animal genomes (tools: annosine)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "mummer": "MUMmer is a system for rapidly aligning entire genomes", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes"}}, "target": "annosine", "target_idx": 4}
{"id": "resource_bwafastalign_index_1", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_INDEX", "tool": "bwafastalign/index", "description": "Create BWA-FASTALIGN index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_INDEX (Create BWA-FASTALIGN index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "local_subworkflow_nextclade_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should NEXTCLADE (nextclade/run) be built?", "criteria": {"Leave them out": null, "Local subworkflow NEXTCLADE": null, "Use nf-core subworkflow nextclade": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 1}
{"id": "resource_bracken_build_4", "category": "resource_profiling", "state": {"process": "BRACKEN_BUILD", "tool": "bracken/build", "description": "Extends a Kraken2 database to be compatible with Bracken"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BUILD (Extends a Kraken2 database to be compatible with Bracken) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_ganon_report_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a ganon report file from the output of ganon classify (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepsomatic": null, "ganon_report": null, "binette": null, "argnorm": null, "echtvar_encode": null}}, "target": "ganon_report", "target_idx": 1}
{"id": "mod_pindel_pindel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and other structural variants at single-based resolution from next-gen sequence data (tools: pindel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "pindel/pindel": "Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and", "bcftools/csq": "bcftools Haplotype-aware consequence caller", "strvctvre/strvctvre": "a structural variant classifier for exonic deletions and duplications", "genomad/endtoend": "Identify mobile genetic elements present in genomic assemblies"}}, "target": "pindel/pindel", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_3_2", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "BWA_MEM", "library_inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic cancer variant calling with tumor-normal pairs with entry step BWA_MEM.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_18", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bcftools_roh_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROH", "tool": "bcftools/roh", "description": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROH (A program for detecting runs of homo/autozygosity. Only bi-allelic sites are con) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_srst2_srst2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLST database and/or a database of gene sequences (e.g. resistance genes, virulence genes, etc)\nand report the presence of STs and/or reference genes. (tools: srst2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seq2hla": null, "mapad_index": null, "emmtyper": null, "srst2_srst2": null, "plink_fastepistasis": null}}, "target": "srst2_srst2", "target_idx": 3}
{"id": "samplesheet_arch_mira_influenza_sc2_6_1", "category": "samplesheet_schema", "state": {"pipeline": "custom/mira-nf", "assay_type": "Custom MIRA-NF Influenza / SC2 pipeline", "data_format": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns are standard for Custom MIRA-NF Influenza / SC2 pipeline input samplesheet?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_pharmcat_matcher_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to be used in the PharmCAT pipeline, it can also be run independently.\nThe Named Allele Matcher does not currently support structural variants, including gene copy\nnumber. If structural variants are detected in the VCF data, it will be ignored and a warning\nwill be issued.\nIf it detects more than the expected number of alleles in the GT column of the VCF, only the\nfirst two alleles will be used and a warning will be issued. On haploid chromosomes, only\nthe first allele will be used. (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "cellrangeratac_count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "pharmcat_matcher": "The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to", "knotannotsv": "Simple tool to create a customizable html file (to be displayed on a web browser) from an AnnotSV output", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "pharmcat_matcher", "target_idx": 2}
{"id": "resource_angsd_dosaf_4", "category": "resource_profiling", "state": {"process": "ANGSD_DOSAF", "tool": "angsd/dosaf", "description": "Estimate site allele frequencies from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOSAF (Estimate site allele frequencies from BAM files.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_1_5", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_gatk4_genotypegvcfs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform joint genotyping on one or more samples pre-called with HaplotypeCaller. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylph/profile": "Sylph profile command for taxonoming profiling", "picrust2/pipeline": "Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4/genotypegvcfs": "Perform joint genotyping on one or more samples pre-called with HaplotypeCaller.", "gatk4/baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)"}}, "target": "gatk4/genotypegvcfs", "target_idx": 3}
{"id": "field_constraint_bam_0_0", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Longitudinal cancer monitoring across multiple timepoints)", "question": {"type": "choice", "instructions": "Which columns are standard for Longitudinal cancer monitoring across multiple timepoints input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bcftools_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Add or remove annotations. (tools: annotate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purecn_run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "bcftools_concat": "Concatenate VCF files", "samtools_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "bcftools_convert": "Converts certain output formats to VCF", "bcftools_annotate": "Add or remove annotations."}}, "target": "bcftools_annotate", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_1_49", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_1_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,bed": null, "sample,bam,bai": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_mix_operator_async_emission_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bandage_image_5", "category": "resource_profiling", "state": {"process": "BANDAGE_IMAGE", "tool": "bandage/image", "description": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BANDAGE_IMAGE (Render an assembly graph in GFA 1.0 format to PNG and SVG image formats) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_1_3", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_1", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_cooler_dump_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dump a cooler’s data to a text stream. (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jvarkit_vcf2table": "Convert VCF to a user friendly table", "samtools_getrg": "filter/convert SAM/BAM/CRAM file", "cooler_dump": "Dump a cooler’s data to a text stream.", "hmmcopy_gccounter": "gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta", "custom_dumpsoftwareversions": "Custom module used to dump software versions within the nf-core pipeline template"}}, "target": "cooler_dump", "target_idx": 2}
{"id": "mod_vizgenpostprocessing_compiletilesegmentation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module compiles segmentation tiles using Vizgen's post-processing tool. (tools: vizgenpostprocessing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vizgenpostprocessing_preparesegmentation": "The module prepares the specification JSON file for Vizgen's post-processing tool\ncell segmentation workflow.", "picard_collectalignmentsummarymetrics": "Collect metrics about the alignment summary of a paired-end library.", "vizgenpostprocessing_compiletilesegmentation": "The module compiles segmentation tiles using Vizgen's post-processing tool.", "raven": "De novo genome assembler for long uncorrected reads.", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, "}}, "target": "vizgenpostprocessing_compiletilesegmentation", "target_idx": 2}
{"id": "mod_pypolca_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Short read polisher for long read assemblies (tools: pypolca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill.", "gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA", "pypolca/run": "Short read polisher for long read assemblies", "racon": "Consensus module for raw de novo DNA assembly of long uncorrected reads", "pbtk/bam2fastq": "converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq"}}, "target": "pypolca/run", "target_idx": 2}
{"id": "mod_famsa_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using FAMSA (tools: famsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "bedops/gtf2bed": "Convert gtf format to bed format", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "famsa/align": "Aligns sequences using FAMSA", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications"}}, "target": "famsa/align", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_4_3", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Xenium output bundle with transcripts CSV, cell polygons, and morphology images?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_3_2", "category": "samplesheet_schema", "state": {"technology": "Ancient DNA", "workflow_entry": "FASTQC", "library_inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_bam_dedup_umi_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_UMI", "modules": ["umitools/prepareforrsem", "samtools/sort", "bam_dedup_stats_samtools_umicollapse", "bam_dedup_stats_samtools_umitools", "bam_sort_stats_samtools"], "description": "BAM deduplication with UMI processing for both genome and transcriptome alignments"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_UMI (umitools/prepareforrsem, samtools/sort, bam_dedup_stats_samtools_umicollapse, bam_dedup_stats_samtools_umitools, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_dedup_umi": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_DEDUP_UMI": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_dedup_umi", "target_idx": 0}
{"id": "mod_getorganelle_config_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads databases needed for running getorganelle (tools: getorganelle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja_demix": null, "busco_phylogenomics": null, "getorganelle_config": null, "abricate_run": null, "abra2": null}}, "target": "getorganelle_config", "target_idx": 2}
{"id": "mod_metaphlan3_mergemetaphlantables_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges output abundance tables from MetaPhlAn3 (tools: metaphlan3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/calibratedragstrmodel": "estimates the parameters for the DRAGstr model", "metaphlan3/mergemetaphlantables": "Merges output abundance tables from MetaPhlAn3", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "samtools/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "metaphlan3/mergemetaphlantables", "target_idx": 1}
{"id": "pipe_all101_bamtofastq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Converts bam or cram files to fastq format and does quality control.. Topics: bamtofastq, conversion, cramtofastq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pacvar": null, "bamtofastq": null, "slamseq": null, "nascent": null, "smrnaseq": null, "funcprofiler": null, "hicar": null, "bactmap": null, "hlatyping": null, "ribomsqc": null}}, "target": "bamtofastq", "target_idx": 1}
{"id": "field_constraint_fastq_1_1_6", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "field_constraint_sample_1_6", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "type: integer": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "field_constraint_expected_cells_0_4", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_14", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_29", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_mmseqs_linclust_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences in linear time using MMSeqs2 linclust. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_linclust": "Cluster sequences in linear time using MMSeqs2 linclust.", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "mmseqs_createtaxdb": "Adds taxonomy information to an existing MMseqs2 database", "mmseqs_cluster": "Cluster sequences using MMSeqs2 cluster.", "pairtools_sort": "Sort a .pairs/.pairsam file"}}, "target": "mmseqs_linclust", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_4_0", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired FASTQs for both GEX and ATAC modalities per nucleus?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_5_4", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Trio exome/genome sequencing (Proband, Mother, Father).", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_gem2_gemmappability_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Define the mappability of a reference (tools: gem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem2/gemindexer": "Create a GEM index from a FASTA file", "bam_dedup_stats_samtools_umicollapse": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats", "pypgx/createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "gem2/gemmappability": "Define the mappability of a reference", "genmap/index": "create index file for genmap"}}, "target": "gem2/gemmappability", "target_idx": 3}
{"id": "field_constraint_sex_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"pattern: ^\\S+\\.gz$": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "resource_blast_makeblastdb_4", "category": "resource_profiling", "state": {"process": "BLAST_MAKEBLASTDB", "tool": "blast/makeblastdb", "description": "Builds a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_MAKEBLASTDB (Builds a BLAST database) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_agrvate_5", "category": "resource_profiling", "state": {"process": "AGRVATE", "tool": "agrvate", "description": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGRVATE (Rapid identification of Staphylococcus aureus agr locus type and agr operon vari) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bio2zarr_vcfpartition_5", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCFPARTITION", "tool": "bio2zarr/vcfpartition", "description": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCFPARTITION (Outputs a set of region strings that partition indexed VCF/BCF files for paralle) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_metapep_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: From metagenomes to epitopes and beyond. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "metapep": "From metagenomes to epitopes and beyond", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous"}}, "target": "metapep", "target_idx": 3}
{"id": "mod_strelka_somatic_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small cohorts and somatic variation in tumor/normal sample pairs (tools: strelka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "atlas_call": "generate VCF file from a BAM file using various calling methods", "strelka_somatic": "Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small coh", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "strelka_somatic", "target_idx": 2}
{"id": "schema_std_references_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/references. Description: nf-core/references is a bioinformatics pipeline that build references, for multiple use cases.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/references.", "criteria": {"vcf,fasta,genome,site,source": null, "sample,group,path,ref,method": null, "patient,sample,vcf,status,cna": null, "sample,tools,file,index": null}}, "target": "vcf,fasta,genome,site,source", "target_idx": 0}
{"id": "schema_std_reportho_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/reportho", "description": "nf-core pipeline for comparative analysis of ortholog predictions", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/reportho?", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "id,fasta,query": null}}, "target": "id,fasta,query", "target_idx": 3}
{"id": "resource_agat_spmergeannotations_2", "category": "resource_profiling", "state": {"process": "AGAT_SPMERGEANNOTATIONS", "tool": "agat/spmergeannotations", "description": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated names and fixes other oddities met in those files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPMERGEANNOTATIONS (This script merge different gff annotation files in one. It uses the AGAT parser) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_21", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_15", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_40", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_expansionhunter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate repeat sizes using NGS data (tools: expansionhunter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunter": "Estimate repeat sizes using NGS data", "gatk4_haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "strdrop_build": "Build reference json from sequencing coverage in STR VCFs", "expansionhunterdenovo_profile": "Compute genome-wide STR profile", "utils_nextflow_pipeline": "Subworkflow with functionality that may be useful for any Nextflow pipeline"}}, "target": "expansionhunter", "target_idx": 0}
{"id": "mod_gnu_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split a file into consecutive or interleaved sections (tools: gnu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gnu/split": "Split a file into consecutive or interleaved sections", "gnu/sort": "Writes a sorted concatenation of file/s", "samtools/bedcov": "reports coverage over regions in a supplied BED file", "bedtools/maskfasta": "masks sequences in a FASTA file based on intervals defined in a feature file.", "bcftools/pluginsplit": "Split VCF by sample, creating single- or multi-sample VCFs."}}, "target": "gnu/split", "target_idx": 0}
{"id": "schema_std_proteinannotator_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinannotator", "assay": "proteinannotator pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/proteinannotator (Generation of sequence-level annotations for amino acid sequ)?", "criteria": {"patient,sample,vcf,status,cna": null, "family_id,sample,file_path,hpo_terms,sex": null, "fasta,assembly,ncbi,gff,fastq": null, "id,fasta": null}}, "target": "id,fasta", "target_idx": 3}
{"id": "pipe_all101_dualrnaseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for dualrna-seq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. "}}, "target": "dualrnaseq", "target_idx": 3}
{"id": "noul_confusing_combine_with_mix_semantics_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_binning_concoct_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BINNING_CONCOCT", "modules": ["concoct/cutupfasta", "concoct/concoctcoveragetable", "concoct/concoct", "concoct/mergecutupclustering", "concoct/extractfastabins"], "description": "Runs the CONCOCT workflow of contig binning"}, "question": {"type": "choice", "instructions": "How should FASTA_BINNING_CONCOCT (concoct/cutupfasta, concoct/concoctcoveragetable, concoct/concoct, concoct/mergecutupclustering, concoct/extractfastabins) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_BINNING_CONCOCT": null, "Use nf-core subworkflow fasta_binning_concoct": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_binning_concoct", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_13", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_atlas_pmd_4", "category": "resource_profiling", "state": {"process": "ATLAS_PMD", "tool": "atlas/pmd", "description": "Estimate the post-mortem damage patterns of DNA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_PMD (Estimate the post-mortem damage patterns of DNA) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_confusing_combine_with_mix_semantics_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_baysor_segfree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract neighborhood composition vectors (NVCs) from a dataset. (tools: baysor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam/bammerge": null, "vireo": null, "pairtools/select": null, "bigscape/bigscape": null, "baysor/segfree": null}}, "target": "baysor/segfree", "target_idx": 4}
{"id": "mod_iphop_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict phage host using iPHoP (tools: iphop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_create_som_pon_gatk": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a geno", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "semibin/singleeasybin": "metagenomic binning with self-supervised learning", "iphop/predict": "Predict phage host using iPHoP", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "iphop/predict", "target_idx": 3}
{"id": "mod_sparsesignatures_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mutational signature deconvolution of cancer cells (tools: sparsesignatures)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"civicpy/annotate": "A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations o", "nonpareil/nonpareil": "Calculate metagenome redundancy curve from FASTQ files", "thermorawfileparser": "Parses a Thermo RAW file containing mass spectra to an open file format", "sparsesignatures": "mutational signature deconvolution of cancer cells", "sigprofiler": "mutational signature deconvolution of cancer cells"}}, "target": "sparsesignatures", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_4_1", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Raw paired-end Illumina WGS FASTQs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_angsd_realsfs_3", "category": "resource_profiling", "state": {"process": "ANGSD_REALSFS", "tool": "angsd/realsfs", "description": "Estimate site frequency spectrum from site allele frequencies"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_REALSFS (Estimate site frequency spectrum from site allele frequencies) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_pairix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates (tools: pairix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_combine": null, "biscuit_index": null, "cnvkit_reference": null, "bbmap_index": null, "pairix": null}}, "target": "pairix", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_30", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "subworkflow_pkg_quantify_rsem_2", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_RSEM", "modules": ["rsem/calculateexpression", "sentieon/rsemcalculateexpression", "custom/rsemmergecounts", "quant_tximport_summarizedexperiment"], "description": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_RSEM (rsem/calculateexpression, sentieon/rsemcalculateexpression, custom/rsemmergecounts, quant_tximport_summarizedexperiment) be structured in DSL2?", "criteria": {"Use nf-core subworkflow quantify_rsem": null, "Keep the modules in the main workflow": null, "Local subworkflow QUANTIFY_RSEM": null, "Leave them out": null}}, "target": "Use nf-core subworkflow quantify_rsem", "target_idx": 0}
{"id": "noul_exit_code_137_cause_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_strandedness_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null, "pattern: ^[0-9]+$": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "resource_bedops_convert2bed_5", "category": "resource_profiling", "state": {"process": "BEDOPS_CONVERT2BED", "tool": "bedops/convert2bed", "description": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_CONVERT2BED (Convert BAM/GFF/GTF/GVF/PSL files to bed) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_openms_textexporter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Exports various OpenMS XML formats (featureXML, consensusXML, idXML, mzML) to a human-readable text format. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/export": null, "openms/textexporter": null, "metamdbg/asm": null, "seqkit/rmdup": null, "openms/fileconverter": null}}, "target": "openms/textexporter", "target_idx": 1}
{"id": "intent_prepare_data_24", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "prepare_data", "target_idx": 2}
{"id": "mod_hmmer_hmmstat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: display summary statistics for each profile HMM in an HMM database file (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmemit": null, "happy/sompy": null, "hmmer/hmmsearch": null, "quast": null, "hmmer/hmmstat": null}}, "target": "hmmer/hmmstat", "target_idx": 4}
{"id": "pipe_core10_ampliseq_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Fungal ITS1/ITS2 marker gene sequencing to profile soil mycobiome diversity and community composition.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "ampliseq", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_3_2", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CUT&RUN / CUT&TAG chromatin profiling with IgG control with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "mod_fastq_sanitise_seqkit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters and reports malformed FASTQ sequences with seqkit/sana,\nand then pairs any paired-end files using seqkit/pair (tools: fastq_sanitise_seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_sanitise_seqkit": null, "fastqscreen_buildfromindex": null, "adapterremovalfixprefix": null, "bamtofastq10x": null, "skani_dist": null}}, "target": "fastq_sanitise_seqkit", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_2_13", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_19", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "schema_std_epitopeprediction_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/epitopeprediction", "description": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/epitopeprediction?", "criteria": {"sample,alleles,mhc_class,filename": null, "sample_id,mapped,index,file_type": null, "sample_id,idat_red,idat_green,group": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,alleles,mhc_class,filename", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_49", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_41", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_2_5", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,otu_table": null, "sample,primer_fwd,primer_rev": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_ampcombi2_parsetables_0", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_PARSETABLES", "tool": "ampcombi2/parsetables", "description": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_PARSETABLES (A submodule that parses and standardizes the results from various antimicrobial ) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_38", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bcftools_norm_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_NORM", "tool": "bcftools/norm", "description": "Normalize VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_NORM (Normalize VCF file) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_30", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_fetchngs_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pipeline to fetch metadata and raw FastQ files from public databases. Topics: ddbj, download, ena, fastq, geo, sra. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": null, "pacvar": null, "kmermaid": null, "nanostring": null, "slamseq": null, "nanoseq": null, "spatialaxe": null, "fetchngs": null, "createpanelrefs": null, "pairgenomealign": null}}, "target": "fetchngs", "target_idx": 7}
{"id": "noul_include_modular_process_syntax_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fmhfunprofiler_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references. (tools: fmhfunprofiler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "refsolver/identify": "Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver", "fmhfunprofiler": "Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references.", "gnu/sort": "Writes a sorted concatenation of file/s", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "fmhfunprofiler", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_8", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_30", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_ngsbits_bedannotategc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates GC content fraction to regions in a BED file. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "ngsbits_bedannotategc": "Annotates GC content fraction to regions in a BED file.", "plink_recode": "Recodes plink bfiles into a new text fileset applying different modifiers", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}}, "target": "ngsbits_bedannotategc", "target_idx": 2}
{"id": "subworkflow_pkg_bed_scatter_bedtools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BED_SCATTER_BEDTOOLS", "modules": ["bedtools/split"], "description": "Scatters inputted BED files by the amount specified."}, "question": {"type": "choice", "instructions": "How should BED_SCATTER_BEDTOOLS (bedtools/split) be structured in DSL2?", "criteria": {"Local subworkflow BED_SCATTER_BEDTOOLS": null, "Leave them out": null, "Use nf-core subworkflow bed_scatter_bedtools": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bed_scatter_bedtools", "target_idx": 2}
{"id": "mod_cnaqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality control of copy number data from bulk WGS assays (tools: cnaqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnaqc": "Quality control of copy number data from bulk WGS assays", "custom_collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op", "cnvpytor_callcnvs": "Command line tool for calling CNVs in whole genome sequencing data", "canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file"}}, "target": "cnaqc", "target_idx": 0}
{"id": "pipe_core10_mag_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Assembly and binning of metagenomes using SPAdes, MEGAHIT, MetaBAT2, and CheckM quality control.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)"}}, "target": "mag", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_0_3", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_gatk4_asereadcounter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"falint": "A fasta linter/validator", "vclust/prefilter": "The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by ", "vcflib/vcfbreakmulti": "If multiple alleles are specified in a single record, break the record into several lines preserving allele-sp", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "gatk4/asereadcounter", "target_idx": 4}
{"id": "samplesheet_arch_ont_direct_rna_se_3_2", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Oxford Nanopore direct RNA with entry step NANOPLOT.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_vclust_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like ANI and coverage (alignment fraction) (tools: vclust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_split_by_region": null, "vclust/align": null, "concoct/concoctcoveragetable": null, "mobsuite/recon": null, "clusty": null}}, "target": "vclust/align", "target_idx": 1}
{"id": "field_constraint_bai_1_5", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "intent_debug_error_16", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "debug_error", "target_idx": 1}
{"id": "field_constraint_status_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_36", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_13", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_ilastik_multicut_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. (tools: ilastik)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coreograph": null, "ilastik/multicut": null, "hhsuite/reformat": null, "gridss/preprocess": null, "cellpose": null}}, "target": "ilastik/multicut", "target_idx": 1}
{"id": "mod_circexplorer2_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate circRNAs detected in the output from CIRCexplorer2 parse (tools: circexplorer2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"universc": "Module to run UniverSC an open-source pipeline to demultiplex and process single-cell RNA-Seq data", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "samtools_collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma", "parabricks_rnafq2bam": "This tool is the equivalent of fq2bam for RNA-Seq samples, receiving inputs in FASTQ format, performing alignm", "circexplorer2_annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse"}}, "target": "circexplorer2_annotate", "target_idx": 4}
{"id": "noul_channel_operator_map_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_modular_subworkflow_composition_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_26", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_6", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_argnorm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD). (tools: argnorm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "hamronization_amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "hamronization_summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "survivor_simsv": "Simulate an SV VCF file based on a reference genome", "fcsgx_fetchdb": "Fetches the NCBI FCS-GX database using a provided manifest URL"}}, "target": "argnorm", "target_idx": 0}
{"id": "mod_genomescope2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical approach (tools: genomescope2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pilon": "Automatically improve draft assemblies and find variation among strains, including large event detection", "rgi_bwt": "Predict antibiotic resistance from protein or nucleotide data", "genomescope2": "Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical ", "seqkit_translate": "Translate DNA/RNA to protein sequence", "unzipfiles": "Unzip ZIP archive files"}}, "target": "genomescope2", "target_idx": 2}
{"id": "mod_glimpse_chunk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Defines chunks where to run imputation (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse2_chunk": "Defines chunks where to run imputation", "bcftools_pluginimputeinfo": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO met", "doubletdetection": "Doublet detection in single-cell RNA-seq data", "glimpse_chunk": "Defines chunks where to run imputation", "telomerehunter": "In silico estimation of telomere content and composition from cancer genomes"}}, "target": "glimpse_chunk", "target_idx": 3}
{"id": "mod_bcftools_norm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalize VCF file (tools: norm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rsem_preparereference": null, "last_mafswap": null, "ferrohgvs_normalize": null, "bcftools_norm": null, "aardvark_compare": null}}, "target": "bcftools_norm", "target_idx": 3}
{"id": "schema_std_hicar_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hicar", "assay": "hicar pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/hicar (Pipeline for HiCAR data, a robust and sensitive multi-omic c)?", "criteria": {"sample,type,level,msfile": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null, "fastq_1,fastq_2,group,replicate,md5_1": null}}, "target": "fastq_1,fastq_2,group,replicate,md5_1", "target_idx": 3}
{"id": "intent_ask_question_21", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "prepare_data": null, "debug_error": null, "ask_question": null}}, "target": "ask_question", "target_idx": 3}
{"id": "pipe_all101_lsmquant_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for processing and analysis of light-sheet microscopy images.. Topics: 3dunet, image-analysis, image-processing, light-sheet-microcopy, segmentation, stitching. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]"}}, "target": "lsmquant", "target_idx": 9}
{"id": "mod_fastq_download_prefetch_fasterqdump_sratools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA). (tools: fastq_download_prefetch_fasterqdump_sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_download_prefetch_fasterqdump_sratools": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA).", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA.", "entrezdirect/esearch": "Searches a term in a public NCBI database", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "splitubam": "split one ubam into multiple, per line, fast"}}, "target": "fastq_download_prefetch_fasterqdump_sratools", "target_idx": 0}
{"id": "mod_cutesv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: structural-variant calling with cutesv (tools: cutesv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker/classify": "mtDNA deletion and duplication classification downstream of mitosalt", "gatk4/splitncigarreads": "Splits reads that contain Ns in their cigar string", "rpbp/preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "sawfish/jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "cutesv": "structural-variant calling with cutesv"}}, "target": "cutesv", "target_idx": 4}
{"id": "mod_rundbcan_easysubstrate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZymes) from genomic data using the dbCAN annotation tool. (tools: dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/translate": "Translate DNA/RNA to protein sequence", "oarfish/alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "rundbcan/easysubstrate": "Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzyme", "rundbcan/easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo"}}, "target": "rundbcan/easysubstrate", "target_idx": 2}
{"id": "resource_agat_sqstatbasic_0", "category": "resource_profiling", "state": {"process": "AGAT_SQSTATBASIC", "tool": "agat/sqstatbasic", "description": "Provides basic statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SQSTATBASIC (Provides basic statistics in text format from a GFF/GTF annotation file) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_duphold_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast way to add depth information to those calls. This can be used as additional information for filtering variants; for example we will be skeptical of deletion calls that do not have lower than average coverage compared to regions with similar gc-content. (tools: duphold)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cleanifier_download": null, "elprep_filter": null, "duphold": null, "csvtk_sort": null, "nextgenmap": null}}, "target": "duphold", "target_idx": 2}
{"id": "mod_tesorter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An accurate and fast method to classify LTR-retrotransposons in plant genomes (tools: tesorter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "opt_flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple", "tesorter": "An accurate and fast method to classify LTR-retrotransposons in plant genomes", "alignoth": "Creating alignment plots from bam files", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "tesorter", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "data_format": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,matrix": null, "plate,sample,bam": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_pathogensurveillance_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pathogensurveillance", "assay": "pathogensurveillance pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/pathogensurveillance (Surveillance of pathogens using population genomics and sequ)?", "criteria": {"sample,fastq_1,fastq_2,genome": null, "vcf,fasta,genome,site,source": null, "sample_id,name,description,path,path_2": null, "gene_name,alignment,tree,suite,tool": null}}, "target": "sample_id,name,description,path,path_2", "target_idx": 2}
{"id": "mod_last_lastal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns query sequences to target sequences indexed with lastdb (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"conifer": "Calculate confidence scores from Kraken2 output", "last/lastal": "Aligns query sequences to target sequences indexed with lastdb", "last/lastdb": "Prepare sequences for subsequent alignment with lastal.", "last/dotplot": "Makes a dotplot (Oxford Grid) of pair-wise sequence alignments", "pygenprop/info": "Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assign"}}, "target": "last/lastal", "target_idx": 1}
{"id": "mod_poolsnp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PoolSNP is a heuristic SNP caller, which uses an MPILEUP file and a reference genome in FASTA format as inputs. (tools: poolsnp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fq/lint": "fq lint is a FASTQ file pair validator.", "sequencetools/pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "msisensorpro/scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "bcftools/mpileup": "Compresses VCF files", "poolsnp": "PoolSNP is a heuristic SNP caller, which uses an MPILEUP file and a reference genome in FASTA format as inputs"}}, "target": "poolsnp", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_classify_catpack_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CLASSIFY_CATPACK", "modules": ["catpack/addnames", "catpack/bins", "catpack/contigs", "catpack/download", "catpack/prepare", "catpack/summarise", "untar"], "description": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack)."}, "question": {"type": "choice", "instructions": "How should FASTA_CLASSIFY_CATPACK (catpack/addnames, catpack/bins, catpack/contigs, catpack/download, catpack/prepare, catpack/summarise, untar) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_classify_catpack": null, "Local subworkflow FASTA_CLASSIFY_CATPACK": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_classify_catpack", "target_idx": 0}
{"id": "mod_centrifuger_quantification_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quantification (taxonomic profiling) of Centrifuger model (tools: centrifuger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"md5sum": "Create MD5 (128-bit) checksums", "centrifuger_quantification": "Quantification (taxonomic profiling) of Centrifuger model", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "iphop_predict": "Predict phage host using iPHoP"}}, "target": "centrifuger_quantification", "target_idx": 1}
{"id": "noul_undeclared_process_file_inputs_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_drep_dereplicate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome (tools: drep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk/unifiedgenotyper": "SNP and Indel variant caller on a per-locus basis", "drep/dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "abacas": "Contiguate draft genome assembly", "seqwish/induce": "Induce a variation graph in GFA format from alignments in PAF format"}}, "target": "drep/dereplicate", "target_idx": 1}
{"id": "mod_gapseq_doall_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Complete gapseq workflow from genome to gap-filled model (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"repeatmasker_rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "gapseq_doall": "Complete gapseq workflow from genome to gap-filled model", "gapseq_medium": "Predict growth medium from a draft model and pathway predictions", "krakenuniq_download": "Download KrakenUniq databases and related fles", "gapseq_fill": "Perform gap filling on draft metabolic model"}}, "target": "gapseq_doall", "target_idx": 1}
{"id": "pipe_all101_raredisease_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Call and score variants from WGS/WES of rare disease patients.. Topics: diagnostics, rare-disease, snv, structural-variants, variant-annotation, variant-calling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": null, "marsseq": null, "metatdenovo": null, "genomeqc": null, "rnadnavar": null}}, "target": "raredisease", "target_idx": 0}
{"id": "resource_bcftools_annotate_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ANNOTATE", "tool": "bcftools/annotate", "description": "Add or remove annotations."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ANNOTATE (Add or remove annotations.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_status_0_8", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"enum: [auto, forward, reverse]": null, "format: file-path": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "mod_ngmerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merging paired-end reads and removing sequencing adapters. (tools: ngmerge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk_sort": "Sort  CSV (or TSV) tables", "rtgtools_bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "gedi_price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "ngmerge": "Merging paired-end reads and removing sequencing adapters.", "clame": "binning of metagenomic sequences"}}, "target": "ngmerge", "target_idx": 3}
{"id": "resource_busco_phylogenomics_0", "category": "resource_profiling", "state": {"process": "BUSCO_PHYLOGENOMICS", "tool": "busco/phylogenomics", "description": "Construct species phylogenies using BUSCO proteins"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PHYLOGENOMICS (Construct species phylogenies using BUSCO proteins) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_bam_ngscheckmate_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_NGSCHECKMATE", "modules": ["bcftools/mpileup", "ngscheckmate/ncm"], "description": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs."}, "question": {"type": "choice", "instructions": "How should BAM_NGSCHECKMATE (bcftools/mpileup, ngscheckmate/ncm) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_ngscheckmate": null, "Local subworkflow BAM_NGSCHECKMATE": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_ngscheckmate", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_biobambam_bammarkduplicates2_0", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMARKDUPLICATES2", "tool": "biobambam/bammarkduplicates2", "description": "Locate and tag duplicate reads in a BAM file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMARKDUPLICATES2 (Locate and tag duplicate reads in a BAM file) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_process_conditional_execution_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_somalier_relate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/GVCF or from jointly-called VCFs (tools: somalier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions", "ascat": "copy number profiles of tumour cells.", "somalier_extract": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "somalier_relate": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "gunc_downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes"}}, "target": "somalier_relate", "target_idx": 3}
{"id": "field_constraint_fastq_1_0_8", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "resource_busco_busco_1", "category": "resource_profiling", "state": {"process": "BUSCO_BUSCO", "tool": "busco/busco", "description": "Benchmarking Universal Single Copy Orthologs"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_BUSCO (Benchmarking Universal Single Copy Orthologs) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_4_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "mod_fastp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform adapter/quality trimming on sequencing reads (tools: fastp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk/depth": "Creates a bed file containing the depth of data at intervals of an aligned bam.", "bbmap/bbduk": "Adapter and quality trimming of sequencing reads", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "fastp": "Perform adapter/quality trimming on sequencing reads", "seqfu/derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th"}}, "target": "fastp", "target_idx": 3}
{"id": "resource_ashlar_1", "category": "resource_profiling", "state": {"process": "ASHLAR", "tool": "ashlar", "description": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASHLAR (Alignment by Simultaneous Harmonization of Layer/Adjacency Registration) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "core_tool_featurecounts_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Assign and quantify mapped reads to genomic features such as exons, genes, and promoter annotations from sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"featurecounts": null, "stringtie": null, "kallisto": null, "htseq": null, "salmon": null}}, "target": "featurecounts", "target_idx": 0}
{"id": "resource_bcftools_pluginsetgt_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSETGT", "tool": "bcftools/pluginsetgt", "description": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSETGT (Sets genotypes according to the specified criteria and filtering expressions. Fo) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_arcane_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane (tools: arcane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"echtvar_anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "happy_sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic ", "anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}}, "target": "arcane_filter", "target_idx": 4}
{"id": "mod_hackgap_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, JIT-compiled k-mer counter supporting both contiguous and gapped k-mers using multi-way bucketed Cuckoo hash tables. (tools: hackgap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_report": "Generate a ganon report file from the output of ganon classify", "hackgap_count": "Fast, JIT-compiled k-mer counter supporting both contiguous and gapped k-mers using multi-way bucketed Cuckoo ", "rgi_main": "Predict antibiotic resistance from protein or nucleotide data", "windowmasker_ustat": "A program to take a counts file and creates a file of genomic co-ordinates to be masked.", "fastk_merge": "A tool to merge FastK histograms"}}, "target": "hackgap_count", "target_idx": 1}
{"id": "resource_artic_aligntrim_4", "category": "resource_profiling", "state": {"process": "ARTIC_ALIGNTRIM", "tool": "artic/aligntrim", "description": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_ALIGNTRIM (Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme ) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_channel_operator_map_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_19", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_proovframe_map_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: frame-shift correction for long read (meta)genomics - maps proteins to reads (tools: proovframe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proovframe/map": null, "mdust": null, "proovframe/fix": null, "savana/to": null, "dshbio/filtergff3": null}}, "target": "proovframe/map", "target_idx": 0}
{"id": "mod_picard_bedtointervallist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates an interval list from a bed file and a reference dict (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_bedtointervallist": null, "bamtools_convert": null, "xengsort_index": null, "bedgovcf": null, "openms_peakpickerhires": null}}, "target": "picard_bedtointervallist", "target_idx": 0}
{"id": "mod_celesta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unsupervised machine learning for cell type identification in multiplexed imaging using protein expression and cell neighborhood information without ground truth (tools: celesta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"celesta": "Unsupervised machine learning for cell type identification in multiplexed imaging using protein expression and", "transdecoder_predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "mcstaging_imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata.", "bam_markduplicates_samtools": "Samtools markduplicate SAM/BAM/CRAM file", "imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op"}}, "target": "celesta", "target_idx": 0}
{"id": "samplesheet_arch_faire_seq_chromatin_1_2", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_7_2", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "MUTECT2", "library_inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "sample,vcf": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "mod_ultra_pipeline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: uLTRA aligner - A wrapper around minimap2 to improve small exon detection (tools: ultra)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra/pipeline": null, "openms/idripper": null, "kmcp/compute": null, "bbmap/index": null, "biscuit/qc": null}}, "target": "ultra/pipeline", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_35", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_rastair_mbiasparser_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parses Rastair mbias output to assess the ideal cutoff for read trimming and reports the values. (tools: rastair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"elprep_filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "bismark_methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "rastair_mbiasparser": "Parses Rastair mbias output to assess the ideal cutoff for read trimming and reports the values.", "vcftools": "A set of tools written in Perl and C++ for working with VCF files"}}, "target": "rastair_mbiasparser", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_4_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: High molecular weight environmental metagenomic long reads per sampling site?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "mod_proteinortho_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Proteinortho is a tool to detect orthologous genes within different species. (tools: proteinortho)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eggnogmapper": null, "agat_spextractsequences": null, "savana_cna": null, "kraken2_kraken2": null, "proteinortho": null}}, "target": "proteinortho", "target_idx": 4}
{"id": "samplesheet_arch_viral_ont_single_5_2", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral genome sequencing on Oxford Nanopore MinION / GridION.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "resource_bamtools_convert_5", "category": "resource_profiling", "state": {"process": "BAMTOOLS_CONVERT", "tool": "bamtools/convert", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_CONVERT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_36", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_ganon_table_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a multi-sample report file from the output of ganon report runs (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani_search": "Memory-efficient ANI database queries with skani.", "civicpy_annotate": "A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations o", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "ganon_table": "Generate a multi-sample report file from the output of ganon report runs"}}, "target": "ganon_table", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_0_45", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_all101_metapep_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for metapep analysis? Specific context: From metagenomes to epitopes and beyond. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "metapep": "From metagenomes to epitopes and beyond", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]"}}, "target": "metapep", "target_idx": 5}
{"id": "subworkflow_pkg_bam_impute_stitch_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_STITCH", "modules": ["stitch", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using STITCH software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_STITCH (stitch, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow bam_impute_stitch": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_IMPUTE_STITCH": null}}, "target": "Use nf-core subworkflow bam_impute_stitch", "target_idx": 1}
{"id": "resource_amplify_predict_1", "category": "resource_profiling", "state": {"process": "AMPLIFY_PREDICT", "tool": "amplify/predict", "description": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPLIFY_PREDICT (AMPlify is an attentive deep learning model for antimicrobial peptide prediction) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_20", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "resource_biscuit_biscuitblaster_0", "category": "resource_profiling", "state": {"process": "BISCUIT_BISCUITBLASTER", "tool": "biscuit/biscuitblaster", "description": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BISCUITBLASTER (A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM f) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_backsub_0", "category": "resource_profiling", "state": {"process": "BACKSUB", "tool": "backsub", "description": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACKSUB (Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_bam_stats_mirna_mirtop_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 format. (tools: bam_stats_mirna_mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop_gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations", "miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "strdrop_call": "Detect drops in STR coverage", "bam_stats_mirna_mirtop": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 ", "samtools_fixmate": "Samtools fixmate is a tool that can fill in information (insert size, cigar, mapq) about paired end reads onto"}}, "target": "bam_stats_mirna_mirtop", "target_idx": 3}
{"id": "mod_hisat2_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align RNA-Seq reads to a reference with HISAT2 (tools: hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi": null, "pureclip": null, "simpleaf/index": null, "hisat2/align": null, "ampcombi2/cluster": null}}, "target": "hisat2/align", "target_idx": 3}
{"id": "resource_argnorm_2", "category": "resource_profiling", "state": {"process": "ARGNORM", "tool": "argnorm", "description": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARGNORM (Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed b) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_vcflib_vcfbreakmulti_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: If multiple alleles are specified in a single record, break the record into several lines preserving allele-specific INFO fields (tools: vcflib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcflib/vcfbreakmulti": "If multiple alleles are specified in a single record, break the record into several lines preserving allele-sp", "vcflib/vcffixup": "Generates a VCF stream where AC and NS have been generated for each record using sample genotypes.", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "samtools/samples": "Write sample names and path to reference genome of an alignment to a text file.", "rtgtools/cnveval": "The cnveval tool of RTG tools. It is used to evaluate called CNV regions for agreement with a baseline CNV set"}}, "target": "vcflib/vcfbreakmulti", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "data_format": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,matrix,barcodes,features": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "pipe_all101_magmap_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for magmap analysis? Specific context: Best-practice analysis pipeline for mapping reads to a (large) collections of genomes. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes"}}, "target": "magmap", "target_idx": 9}
{"id": "samplesheet_arch_vcf_annotation_pipeline_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Downstream functional annotation of pre-called VCF files)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf,tbi": null, "sample,bam,bai": null, "sample,vcf": null, "sample,bed": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_4_1", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FastQ reads per sample?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_process_conditional_execution_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_cobrameta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining of contigs fragmented during de novo assembly. (tools: cobra-meta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fairy/coverage": "Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a Meta", "cobrameta": "A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining o", "strelka/somatic": "Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small coh", "quast": "Quality Assessment Tool for Genome Assemblies", "gatk4/variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo"}}, "target": "cobrameta", "target_idx": 1}
{"id": "mod_hmmer_hmmfetch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: extract hmm from hmm database file or create index for hmm database (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eggnogmapper": "Fast genome-wide functional annotation through orthology assignment.", "hmmer/hmmemit": "emit sequences from a profile HMM", "concoct/mergecutupclustering": "Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py", "hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment", "hmmer/hmmfetch": "extract hmm from hmm database file or create index for hmm database"}}, "target": "hmmer/hmmfetch", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_0_12", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_48", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_6", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_bam_telomere_estimation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter (tools: bam_telomere_estimation)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"telseq": "Telseq: a software for calculating telomere length", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope", "pairtools_sort": "Sort a .pairs/.pairsam file", "custom_summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a", "bam_telomere_estimation": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter"}}, "target": "bam_telomere_estimation", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wgs_pe_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Standard Paired-end Whole Genome Sequencing (WGS)", "data_format": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_glimpse2_concordance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Program to compute the genotyping error rate at the sample or marker level. (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "glimpse2/concordance": "Program to compute the genotyping error rate at the sample or marker level.", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "glimpse2/chunk": "Defines chunks where to run imputation", "gappa/examineheattree": "colours a phylogeny with placement densities"}}, "target": "glimpse2/concordance", "target_idx": 1}
{"id": "pipe_all101_lsmquant_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for processing and analysis of light-sheet microscopy images.. Topics: 3dunet, image-analysis, image-processing, light-sheet-microcopy, segmentation, stitching. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hlatyping": null, "phaseimpute": null, "marsseq": null, "sarek": null, "proteinfamilies": null, "pacvar": null, "lsmquant": null, "scnanoseq": null, "rnasplice": null, "differentialabundance": null}}, "target": "lsmquant", "target_idx": 6}
{"id": "qc_adapt_ont_ultra_long_1_24", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_10", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_foldseek_easysearch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search for protein structural hits against a foldseek database of protein structures (tools: foldseek)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cleanifier/filter": "Fast, lightweight contamination removal from microbiome data (FASTQ) using a probabilistic Cuckoo filter or Cu", "picard/fastqtosam": "Converts a FASTQ file to an unaligned BAM or SAM file.", "clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "blast/blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "foldseek/easysearch": "Search for protein structural hits against a foldseek database of protein structures"}}, "target": "foldseek/easysearch", "target_idx": 4}
{"id": "schema_std_abotyper_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/abotyper", "description": "A pipeline for characterising the Human Blood Group and Red Cell Antigens using Oxford Nanopore third-generation sequencing data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/abotyper?", "criteria": {"sample,fastq_1,fastq_2,bam,seq_type": null, "sample,condition,assay,peak_file,footprinting": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,barcode": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bamtools_stats_2", "category": "resource_profiling", "state": {"process": "BAMTOOLS_STATS", "tool": "bamtools/stats", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_STATS (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_1_4", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral amplicon sequencing with primers?", "criteria": {"sample,fasta": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_channel_filter_operator_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_h5ad_removebackground_barcodes_cellbender_anndata_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use cellbender for empty droplet removal (tools: h5ad_removebackground_barcodes_cellbender_anndata)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anndata/barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "anndata/getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file", "h5ad_removebackground_barcodes_cellbender_anndata": "Use cellbender for empty droplet removal", "vizgenpostprocessing/compiletilesegmentation": "The module compiles segmentation tiles using Vizgen's post-processing tool.", "svtk/countsvtypes": "Count the instances of each SVTYPE observed in each sample in a VCF."}}, "target": "h5ad_removebackground_barcodes_cellbender_anndata", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Parse Biosciences Split-seq combinatorial barcoding", "data_format": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,well,plate": null, "sample,bam": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_dynamic_resource_allocation_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_cobs_classicconstruct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a classic bloom filter COBS index (tools: cobs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "cobs/classicconstruct": "Builds a classic bloom filter COBS index", "cobs/compactconstruct": "Builds a compact bloom filter COBS index", "bcftools/index": "Index VCF tools", "gatk4/determinegermlinecontigploidy": "Determines the baseline contig ploidy for germline samples given counts data"}}, "target": "cobs/classicconstruct", "target_idx": 1}
{"id": "mod_sentieon_wgsmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects whole genome quality metrics from a bam file (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "sentieon_wgsmetrics": "Collects whole genome quality metrics from a bam file", "bamreadcount": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencin", "bcftools_pluginimputeinfo": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO met"}}, "target": "sentieon_wgsmetrics", "target_idx": 2}
{"id": "mod_foldcomp_decompress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decompression tool for foldcomp compressed structures (tools: foldcomp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caalm_caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES", "foldcomp_decompress": "Decompression tool for foldcomp compressed structures", "vclust_align": "The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like", "gatk_realignertargetcreator": "Generates a list of locations that should be considered for local realignment prior genotyping.", "bcftools_csq": "bcftools Haplotype-aware consequence caller"}}, "target": "foldcomp_decompress", "target_idx": 1}
{"id": "mod_bedtools_genomecov_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., aligned sequences) for a given genome. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gnu/sort": null, "bamtools/convert": null, "bedgovcf": null, "bedtools/genomecov": null, "controlfreec/assesssignificance": null}}, "target": "bedtools/genomecov", "target_idx": 3}
{"id": "mod_rpbp_estimateorfbayesfactors_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian models to its per-codon\nP-site count vector: a \"translated\" model that expects P-site density\nto concentrate at codon-start positions (the in-frame signal a\ntranslating ribosome produces), and an \"untranslated\" / noise model\nfor the same data. The Bayes factor (ratio of marginal likelihoods)\nquantifies how much the data favour the translated hypothesis.\n\nEmits a BED-style table with one row per ORF carrying genomic\ncoordinates plus the mean and variance of the log Bayes factor across\nMCMC samples. Downstream, `rpbp/selectfinalpredictionset` applies\nBayes-factor, length and overlap rules to this table to produce the\nfinal filtered prediction set.\n\nUses the Stan models bundled inside the rpbp Python package. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp_estimateorfbayesfactors": "Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian ", "rpbp_preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "nanofilt": "Filtering and trimming of Oxford Nanopore Sequencing data", "rpbp_selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s", "modkit_repair": "Repair the MM/ML tags on trimmed or hard-clipped ONT reads using untrimmed ONT reads."}}, "target": "rpbp_estimateorfbayesfactors", "target_idx": 0}
{"id": "mod_bwamem2_mem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA (tools: bwamem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA", "taxpasta_standardise": "Standardise the output of a wide range of taxonomic profilers", "bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "umitools_group": "Group reads based on their UMI and mapping coordinates"}}, "target": "bwamem2_mem", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_5_5", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Single-end Illumina RNA-seq with strandedness.", "criteria": {"sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "resource_agat_spfilterfeaturefromkilllist_0", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERFEATUREFROMKILLLIST", "tool": "agat/spfilterfeaturefromkilllist", "description": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERFEATUREFROMKILLLIST (The script aims to remove features based on a kill list. The default behaviour i) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_dshbio_exportsegments_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Export assembly segment sequences in GFA 1.0 format to FASTA format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_rseqc": null, "gfatools_gfa2fa": null, "bandage_image": null, "dshbio_exportsegments": null, "trtools_mergestr": null}}, "target": "dshbio_exportsegments", "target_idx": 3}
{"id": "subworkflow_pkg_bam_applybqsr_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_APPLYBQSR", "modules": ["gatk4/applybqsr", "samtools/merge"], "description": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using"}, "question": {"type": "choice", "instructions": "How should BAM_APPLYBQSR (gatk4/applybqsr, samtools/merge) be structured in DSL2?", "criteria": {"Local subworkflow BAM_APPLYBQSR": null, "Use nf-core subworkflow bam_applybqsr": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_applybqsr", "target_idx": 1}
{"id": "mod_bam_stringtie_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a unified annotation. (tools: bam_stringtie_merge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_stringtie_merge": null, "savana_to": null, "deseq2_differential": null, "folddisco_query": null, "fusioninspector": null}}, "target": "bam_stringtie_merge", "target_idx": 0}
{"id": "resource_bamtools_convert_4", "category": "resource_profiling", "state": {"process": "BAMTOOLS_CONVERT", "tool": "bamtools/convert", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_CONVERT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay_type": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "data_format": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_createtaxdb_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/createtaxdb. Description: Parallelised and automated construction of metagenomic classifier databases of different tools.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/createtaxdb.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "id,taxid,fasta_dna,fasta_aa": null}}, "target": "id,taxid,fasta_dna,fasta_aa", "target_idx": 3}
{"id": "intent_build_pipeline_14", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_3_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "template": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Pacific Biosciences HiFi sequencing with entry step HIFIADAPTERFILT.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_fastq_subsample_fq_salmon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subsample fastq (tools: fastq_subsample_fq_salmon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_subsample_fq_salmon": "Subsample fastq", "cnvpytor_histogram": "calculates read depth histograms", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "paraclu": "Paraclu finds clusters in data attached to sequences.", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "fastq_subsample_fq_salmon", "target_idx": 0}
{"id": "resource_antismash_antismashlite_5", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITE", "tool": "antismash/antismashlite", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITE (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_megahit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An ultra-fast metagenomic assembler for large and complex metagenomics (tools: megahit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"salsa2": "SALSA, A tool to scaffold long read assemblies with HiC", "bbmap_clumpify": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "megahit": "An ultra-fast metagenomic assembler for large and complex metagenomics", "abacas": "Contiguate draft genome assembly"}}, "target": "megahit", "target_idx": 3}
{"id": "mod_agrvate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rapid identification of Staphylococcus aureus agr locus type and agr operon variants (tools: agrvate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "subread/featurecounts": "Count reads that map to genomic features", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}}, "target": "agrvate", "target_idx": 4}
{"id": "resource_bwa_mem_5", "category": "resource_profiling", "state": {"process": "BWA_MEM", "tool": "bwa/mem", "description": "Performs fastq alignment to a fasta reference using BWA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_MEM (Performs fastq alignment to a fasta reference using BWA) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_high", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_0_4", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking. Input files: Circulating tumor DNA FASTQs across patient clinical draw intervals.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking with entry step FASTQC.", "criteria": {"sample,timepoint,fastq": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_0_1", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hi-C chromosome conformation capture mapping?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,matrix,contacts": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_xz_decompress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decompresses files with xz. (tools: xz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spring/decompress": "Fast, efficient, lossless decompression of FASTQ files.", "openms/idmerger": "Merges several idXML files into one idXML file.", "xz/decompress": "Decompresses files with xz.", "gunzip": "Compresses and decompresses files.", "cleanifier/filter": "Fast, lightweight contamination removal from microbiome data (FASTQ) using a probabilistic Cuckoo filter or Cu"}}, "target": "xz/decompress", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_6", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_vclust_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Vclust cluster performs threshold-based clustering by assigning a genome sequence to a cluster if its similarity (e.g., ANI) to the cluster meets or exceeds a user-defined threshold. (tools: vclust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq/cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences", "nacho/qc": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "pmdtools/filter": "pmdtools command to filter ancient DNA molecules from others", "cdhit/cdhitest": "Cluster nucleotide sequences using sequence similarity", "vclust/cluster": "Vclust cluster performs threshold-based clustering by assigning a genome sequence to a cluster if its similari"}}, "target": "vclust/cluster", "target_idx": 4}
{"id": "noul_channel_factory_inside_process_body_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_hicar_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.. Topics: atac, atac-seq, hic, hicar, multi-omics, transcriptome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": null, "magmap": null, "proteinfold": null, "hicar": null, "sopa": null, "marsseq": null, "pairgenomealign": null, "pangenome": null}}, "target": "hicar", "target_idx": 3}
{"id": "mod_fastq_align_dna_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align fastq files to a reference genome (tools: fastq_align_dna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cutadapt": "Removes adapter sequences from sequencing reads", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "kallistobustools/count": "quantifies scRNA-seq data from fastq files using kb-python.", "fastq_align_dna": "Align fastq files to a reference genome"}}, "target": "fastq_align_dna", "target_idx": 4}
{"id": "resource_bcftools_call_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CALL", "tool": "bcftools/call", "description": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily lost in the process of transition under htslib, but will be added back on popular demand.\nThe original calling model can be invoked with the -c option."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CALL (This command replaces the former bcftools view caller.\nSome of the original func) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_vsearch_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences using a single-pass, greedy centroid-based clustering algorithm. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "numorph/intensity": "performs shading correction and intensity normalization between tile stacks", "seqtk/subseq": "Select only sequences that match the filtering condition", "vsearch/sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).", "vsearch/cluster": "Cluster sequences using a single-pass, greedy centroid-based clustering algorithm."}}, "target": "vsearch/cluster", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_0_3", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_gatk4_markduplicates_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originating from a single fragment of DNA. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "stitch": "STITCH is an R program for reference panel free, read aware, low coverage sequencing genotype imputation. STIT", "gatk4/markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "samplesheetparser/info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c"}}, "target": "gatk4/markduplicates", "target_idx": 2}
{"id": "mod_gridss_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmasker. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss_annotate": "Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmaske", "gridss_preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and ", "samtools_coverage": "produces a histogram or table of coverage per chromosome", "gridss_gridss": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "flye": "De novo assembler for single molecule sequencing reads"}}, "target": "gridss_annotate", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/raredisease) for Trio exome/genome sequencing (Proband, Mother, Father). Input files: Paired-end FASTQs with pedigree relationships and affected status.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Trio exome/genome sequencing (Proband, Mother, Father).", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_xeniumranger_importsegmentation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger importsegmentation module runs `xeniumranger import-segmentation`\nto recompute Xenium Onboard Analysis outputs using external segmentation results.\nIt supports two execution modes mirroring the Xenium Ranger CLI: an image-based\nmode that accepts nuclei and/or cell masks (TIFF/NPY) or GeoJSON polygons together\nwith optional coordinate transforms and unit definitions, and a transcript-based\nmode that ingests Baysor-style transcript assignment CSV files plus visualization\npolygons. Use the image-based inputs when providing label masks or polygons, or\nswitch to the transcript-based inputs when supplying transcript-level assignments\nso the appropriate command-line arguments are passed to Xenium Ranger. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt/ltrharvest": null, "proseg/proseg2baysor": null, "xeniumranger/importsegmentation": null, "annosine": null, "spotiflow": null}}, "target": "xeniumranger/importsegmentation", "target_idx": 2}
{"id": "mod_custom_addmostseverepli_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate a VEP annotated VCF with the most severe pLi field (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sexdeterrmine": "Calculate the relative coverage on the Gonosomes vs Autosomes from the output of samtools depth, with error ba", "custom/addmostseverepli": "Annotate a VEP annotated VCF with the most severe pLi field", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bwameth/index": "Performs indexing of c2t converted reference genome"}}, "target": "custom/addmostseverepli", "target_idx": 1}
{"id": "resource_busco_generateplot_5", "category": "resource_profiling", "state": {"process": "BUSCO_GENERATEPLOT", "tool": "busco/generateplot", "description": "BUSCO plot generation tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_GENERATEPLOT (BUSCO plot generation tool) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_kma_kma_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mapping raw reads directly against redundant databases via KMA alignment (tools: kma)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf2cytosure": "Convert VCF with structural variations to CytoSure format", "ariba_run": "Query input FASTQs against Ariba formatted databases", "deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "kma_kma": "Mapping raw reads directly against redundant databases via KMA alignment"}}, "target": "kma_kma", "target_idx": 4}
{"id": "mod_catpack_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads the required files for either Nr or GTDB for building into a CAT database (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shapeit5/phasecommon": null, "catpack/reads": null, "catpack/addnames": null, "pydamage/filter": null, "catpack/download": null}}, "target": "catpack/download", "target_idx": 4}
{"id": "resource_ataqv_mkarv_2", "category": "resource_profiling", "state": {"process": "ATAQV_MKARV", "tool": "ataqv/mkarv", "description": "mkarv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_MKARV (mkarv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wes_pe_2_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bamaligncleaner_2", "category": "resource_profiling", "state": {"process": "BAMALIGNCLEANER", "tool": "bamaligncleaner", "description": "removes unused references from header of sorted BAM/CRAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMALIGNCLEANER (removes unused references from header of sorted BAM/CRAM files.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_ngsbits_updhunter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: UPD detection from trio variant data. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picrust2_pipeline": "Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "atlas_call": "generate VCF file from a BAM file using various calling methods", "kaiju_kaiju2table": "write your description here", "ngsbits_updhunter": "UPD detection from trio variant data."}}, "target": "ngsbits_updhunter", "target_idx": 4}
{"id": "noul_exit_code_137_cause_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_rseqc_tin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate TIN (transcript integrity number) from RNA-seq reads (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond_blastx": "Queries a DIAMOND database using blastx mode", "ariba_run": "Query input FASTQs against Ariba formatted databases", "rseqc_tin": "Calculate TIN (transcript integrity number) from RNA-seq reads", "ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with"}}, "target": "rseqc_tin", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cageseq) for CAGE-seq 5-prime capped transcript end sequencing. Input files: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CAGE-seq 5-prime capped transcript end sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,tss_bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/chipseq --input samplesheet.csv (Assay: ChIP-seq with IP and input control design)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "intent_debug_error_14", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "debug_error", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_39", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_41", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_gstama_polyacleanup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3) (tools: gstama)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scvitools_solo": "Detect doublets in single-cell RNA-Seq data", "riker_multi": "Run multiple riker collectors in a single BAM pass using riker multi. Specify\ntools via ext.args (e.g. '--tool", "gstama_polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)", "autocycler_cluster": "Cluster replicons in compressed assemblies with Autocycler.", "autocycler_combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}}, "target": "gstama_polyacleanup", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: ATAC-seq chromatin accessibility with biological replicates)", "question": {"type": "choice", "instructions": "Which columns are standard for ATAC-seq chromatin accessibility with biological replicates input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "noul_channel_factory_inside_process_body_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Genome analysis from reference-compressed CRAM files", "data_format": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted CRAM alignments with companion CRAI indexes?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,cram,crai": null, "sample,cram": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_0_2", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fast5": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "pipe_all101_sopa_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for segmentation. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "seqsubmit": "nf-core pipeline for data submission to ENA", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data"}}, "target": "sopa", "target_idx": 5}
{"id": "mod_dshbio_splitgff3_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split features in gzipped GFF3 format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt/gff3validator": "GenomeTools gt-gff3validator utility to strictly validate a GFF3 file", "dshbio/splitgff3": "Split features in gzipped GFF3 format", "ribotish/predict": "Quality control of riboseq bam data", "arriba/arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "dshbio/filtergff3": "Filter features in gzipped GFF3 format"}}, "target": "dshbio/splitgff3", "target_idx": 1}
{"id": "schema_std_alleleexpression_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/alleleexpression", "assay": "alleleexpression pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/alleleexpression (Alleleexpression is a nf-core pipeline for allele-specific e)?", "criteria": {"id,taxid,fasta_dna,fasta_aa": null, "vcf,fasta,genome,site,source": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample,fastq_1,fastq_2,vcf", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_25", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bedtools_unionbedg_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_UNIONBEDG", "tool": "bedtools/unionbedg", "description": "Combines multiple BedGraph files into a single file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_UNIONBEDG (Combines multiple BedGraph files into a single file) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_1_5", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_annotsv_installannotations_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Install the AnnotSV annotations (tools: annotsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paragraph_vcf2paragraph": "Convert a VCF file to a JSON graph", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "annotsv_installannotations": "Install the AnnotSV annotations", "openms_idripper": "Split a merged identification file into their originating identification files"}}, "target": "annotsv_installannotations", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_3", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_rundbcan_database_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: command from run_dbcan to prepare the database for dbCAN annotation. (tools: run_dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/installannotations": null, "rundbcan/cazymeannotation": null, "rundbcan/database": null, "transdecoder/predict": null, "snpsift/annotate": null}}, "target": "rundbcan/database", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_11", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_jvarkit_dict2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract BED file from hts files containing a dictionary (VCF,BAM, CRAM, DICT, etc...) (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"epang/place": "phylogenetic placement of query sequences in a reference tree", "atlas/call": "generate VCF file from a BAM file using various calling methods", "jvarkit/dict2bed": "Extract BED file from hts files containing a dictionary (VCF,BAM, CRAM, DICT, etc...)", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration"}}, "target": "jvarkit/dict2bed", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cageseq) for CAGE-seq 5-prime capped transcript end sequencing. Input files: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cageseq, determine the input samplesheet column structure for: CAGE-seq 5-prime capped transcript end sequencing.", "criteria": {"sample,tss_bed": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "resource_bedops_convert2bed_1", "category": "resource_profiling", "state": {"process": "BEDOPS_CONVERT2BED", "tool": "bedops/convert2bed", "description": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_CONVERT2BED (Convert BAM/GFF/GTF/GVF/PSL files to bed) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_4_3", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "mod_deeptools_plotprofile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: plots values produced by deeptools_computematrix as a profile plot (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samblaster": "This module combines samtools and samblaster in order to use\nsamblaster capability to filter or tag SAM files,", "krona_ktimportkrona": "Collect multiple krona reports into a single html file", "deeptools_plotheatmap": "plots values produced by deeptools_computematrix as a heatmap", "deeptools_plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "trtools_mergestr": "MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file."}}, "target": "deeptools_plotprofile", "target_idx": 3}
{"id": "samplesheet_arch_germline_lane_split_0_3", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_mirdeep2_mapper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: miRDeep2 Mapper is a tool that prepares deep sequencing reads for downstream miRNA detection by collapsing reads, mapping them to a genome, and outputting the required files for miRNA discovery. (tools: mirdeep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco/generateplot": "BUSCO plot generation tool", "mirdeep2/mapper": "miRDeep2 Mapper is a tool that prepares deep sequencing reads for downstream miRNA detection by collapsing rea", "fcsgx/fetchdb": "Fetches the NCBI FCS-GX database using a provided manifest URL", "mapad/map": "Map short-reads to an indexed reference genome", "mirdeep2/mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs."}}, "target": "mirdeep2/mapper", "target_idx": 1}
{"id": "mod_catpack_summarise_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarises results from CAT/BAT/RAT classification steps (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "catpack/summarise": "Summarises results from CAT/BAT/RAT classification steps", "diamond/blastp": "Queries a DIAMOND database using blastp mode", "gtdbtk/classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "catpack/bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins)."}}, "target": "catpack/summarise", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP", "modules": ["ensemblvep/vep", "tabix/tabix"], "description": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP (ensemblvep/vep, tabix/tabix) be structured in DSL2?", "criteria": {"Local subworkflow VCF_ANNOTATE_ENSEMBLVEP": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_annotate_ensemblvep": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep", "target_idx": 2}
{"id": "field_constraint_status_0_13", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_5_4", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/pacvar, determine the input samplesheet column structure for: PacBio HiFi unaligned BAM variant calling.", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/smrnaseq", "assay_type": "Small RNA / miRNA sequencing", "data_format": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,mirna_id": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_17", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_cnvkit_coverage_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/genemetrics": "Copy number variant detection from high-throughput sequencing data", "integronfinder": "Detect integrons in DNA sequences", "parabricks/dbsnp": "NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database", "cnvkit/coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "cnvkit/batch": "Copy number variant detection from high-throughput sequencing data"}}, "target": "cnvkit/coverage", "target_idx": 3}
{"id": "mod_elprep_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter, sort and markdup sam/bam files, with optional BQSR and variant calling. (tools: elprep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"xeniumranger/rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "elprep/filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "picard/meanqualitybycycle": "Collect metrics about the mean quality by cycle of a paired-end library.", "clame": "binning of metagenomic sequences"}}, "target": "elprep/filter", "target_idx": 1}
{"id": "mod_gfatools_stat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summary statistics for GFA files (tools: gfatools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bio2zarr/vcf2zarrconvert": null, "gfatools/stat": null, "custom/collectstats": null, "assemblyscan": null, "emboss/revseq": null}}, "target": "gfatools/stat", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Metagenomic MAG assembly with comparative groups. Input files: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Metagenomic MAG assembly with comparative groups with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "mod_fcsgx_cleangenome_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome assemblies (tools: fcsgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertgff2bed": null, "biscuit/biscuitblaster": null, "fcsgx/cleangenome": null, "agat/convertspgff2tsv": null, "gatk4/filtervarianttranches": null}}, "target": "fcsgx/cleangenome", "target_idx": 2}
{"id": "mod_cellranger_multi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's pipelines to analyze sequencing data produced from various Chromium technologies, including Single Cell Gene Expression, Single Cell Immune Profiling, Feature Barcoding, and Cell Multiplexing. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools/extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "cellranger/multi": "Module to use Cell Ranger's pipelines to analyze sequencing data produced from various Chromium technologies, ", "quant_tximport_summarizedexperiment": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedEx"}}, "target": "cellranger/multi", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_24", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_fgbio_callmolecularconsensusreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls consensus sequences from reads with the same unique molecular tag. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_downsample": null, "ganon_buildcustom": null, "elprep_merge": null, "fgumi_dedup": null, "fgbio_callmolecularconsensusreads": null}}, "target": "fgbio_callmolecularconsensusreads", "target_idx": 4}
{"id": "mod_suppa_clusterevents_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster events based on PSI values and significantly differentially spliced events using SUPPA2. (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star_genomegenerate": null, "leafcutter_differentialsplicing": null, "vcf2cytosure": null, "suppa_clusterevents": null, "suppa_generateevents": null}}, "target": "suppa_clusterevents", "target_idx": 3}
{"id": "mod_gatk4_calibratedragstrmodel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: estimates the parameters for the DRAGstr model (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "verifybamid/verifybamid": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "gatk4/calibratedragstrmodel": "estimates the parameters for the DRAGstr model", "fasta_hmmsearch_rank_fastas": "Run hmmsearch and output separate fasta files for top scoring hits to each profile"}}, "target": "gatk4/calibratedragstrmodel", "target_idx": 3}
{"id": "mod_deacon_indexintersect_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Intersect multiple deacon indexes (A ∩ B ...) (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqe": "fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data.", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "ultra_index": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment", "deacon_indexintersect": "Intersect multiple deacon indexes (A ∩ B ...)", "bcftools_index": "Index VCF tools"}}, "target": "deacon_indexintersect", "target_idx": 3}
{"id": "mod_bam_tumor_normal_somatic_variant_calling_strelka_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform variant calling on a paired tumor normal set of samples using strelka somatic mode.\nf1r2 output of mutect2 is run through learnreadorientationmodel to get the artifact priors.\nRun the input bam files through getpileupsummarries and then calculatecontamination to get the contamination and segmentation tables.\nFilter the mutect2 output vcf using filtermutectcalls, artifact priors and the contamination & segmentation tables for additional filtering. (tools: bam_tumor_normal_somatic_variant_calling_strelka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/tnhaplotyper2": null, "sentieon/tnscope": null, "vizgenpostprocessing/runsegmentationontile": null, "lofreq/filter": null, "bam_tumor_normal_somatic_variant_calling_strelka": null}}, "target": "bam_tumor_normal_somatic_variant_calling_strelka", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_1_16", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_6_5", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns are standard for Custom MIRA-NF Influenza / SC2 pipeline input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_bwa_samse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert bwa SA coordinate file to SAM format (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_samse": "Convert bwa SA coordinate file to SAM format", "bwa_aln": "Find SA coordinates of the input reads for bwa short-read mapping", "diamond_deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust", "bam_rseqc": "Subworkflow to run multiple commands in the RSeqC package", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "bwa_samse", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_6_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns are standard for RNA gene fusion detection (Arriba, STAR-Fusion) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_variantextractor_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deterministic and standard extractor of SNVs, indels and structural variants (SVs)\nfrom VCF files. Homogenizes multiallelic variants, MNPs and SVs (including imprecise\npaired breakends and single breakends) to facilitate downstream processing. (tools: variant-extractor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"variantextractor": null, "scvitools_solo": null, "skani_triangle": null, "bcftools_annotate": null, "aardvark_merge": null}}, "target": "variantextractor", "target_idx": 0}
{"id": "mod_holodeck_simulate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simulate sequencing reads from a reference genome with holodeck (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker_plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "bismark_summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "holodeck_eval": "Evaluate alignment accuracy of holodeck-simulated reads", "holodeck_simulate": "Simulate sequencing reads from a reference genome with holodeck"}}, "target": "holodeck_simulate", "target_idx": 4}
{"id": "mod_seqkit_translate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Translate DNA/RNA to protein sequence (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_translate": null, "seqkit_replace": null, "samplesheetparser_diff": null, "seqkit_pair": null, "saltshaker_call": null}}, "target": "seqkit_translate", "target_idx": 0}
{"id": "mod_trgt_genotype_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tandem repeat genotyping from PacBio HiFi data (tools: trgt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hasheddrops": "Generating cell hashing calls from a matrix of count data.", "trgt/genotype": "Tandem repeat genotyping from PacBio HiFi data", "hifiadapterfilt/hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "macsyfinder/download": "Download MacSyFinder models using msf_data", "bam2fastx/bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}}, "target": "trgt/genotype", "target_idx": 1}
{"id": "mod_fastq_preprocess_seqkit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that preprocesses FASTQ files (tools: fastq_preprocess_seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash_sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "openms_idmassaccuracy": "Calculates a distribution of the mass error from given mass spectra and IDs.", "ariba_getref": "Download and prepare database for Ariba analysis", "ariba_run": "Query input FASTQs against Ariba formatted databases", "fastq_preprocess_seqkit": "Subworkflow that preprocesses FASTQ files"}}, "target": "fastq_preprocess_seqkit", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_1_18", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_kmcp_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct KMCP database from k-mer files (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_combinebrackenoutputs": null, "kmcp_index": null, "fastq_remove_rrna": null, "binette": null, "fasta_gtf_bam_rpbp": null}}, "target": "kmcp_index", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_28", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_nanomonsv_parse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parse all the supporting reads of putative somatic SVs using nanomonsv.\nAfter successful completion, you will find supporting reads stratified by\ndeletions, insertions, and rearrangements.\nA precursor to \"nanomonsv get\" (tools: nanomonsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nanomonsv_parse": "Parse all the supporting reads of putative somatic SVs using nanomonsv.\nAfter successful completion, you will ", "skani_triangle": "All-to-all ANI computation.", "saltshaker_call": "mtDNA deletion and duplication calling downstream of mitosalt", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "caddsv_run": "Score structural variants with CADD-SV."}}, "target": "nanomonsv_parse", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_4_0", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs with pedigree relationships and affected status?", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_5_5", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "template": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/dualrnaseq, determine the input samplesheet column structure for: Dual RNA-seq simultaneous host and pathogen transcriptomics.", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,host_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "mod_dshbio_filtergff3_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter features in gzipped GFF3 format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt_gff3": "GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files", "fastq_align_mapad": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and index", "dshbio_filtergff3": "Filter features in gzipped GFF3 format", "sentieon_bwaindex": "Create BWA index for reference genome", "dshbio_splitgff3": "Split features in gzipped GFF3 format"}}, "target": "dshbio_filtergff3", "target_idx": 2}
{"id": "mod_chromograph_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Chromograph is a python package to create PNG images from genetics data such as BED and WIG files. (tools: chromograph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "td2_longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files."}}, "target": "chromograph", "target_idx": 4}
{"id": "field_constraint_expected_cells_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "mod_ectyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In silico prediction of E. coli serotype (tools: ectyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "ectyper": "In silico prediction of E. coli serotype", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "fgumi/simplexmetrics": "Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data"}}, "target": "ectyper", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_1_4", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "intent_debug_error_19", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "debug_error": null, "ask_question": null}}, "target": "debug_error", "target_idx": 2}
{"id": "mod_sigprofiler_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mutational signature deconvolution of cancer cells (tools: sigprofilermatrixgenerator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sparsesignatures": "mutational signature deconvolution of cancer cells", "sigprofiler": "mutational signature deconvolution of cancer cells", "snpsift/dbnsfp": "The dbNSFP is an integrated database of functional predictions from multiple algorithms", "ribodetector": "Accurate and rapid RiboRNA sequences Detector based on deep learning", "gunzip": "Compresses and decompresses files."}}, "target": "sigprofiler", "target_idx": 1}
{"id": "noul_publishdir_directive_usage_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_custom_orfnormalise_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for cross-caller merging.\n\nAn \"ORF caller\" is a tool that scans ribosome-profiling (Ribo-seq) data and\npredicts which open reading frames are being translated. Each caller writes\nits own table format and uses its own location encoding, classification\nvocabulary, and confidence score. This module reconciles five callers into\none harmonised schema. The `caller` val input selects the parser;\nsupported values:\n\n  - ribocode    (RiboCode predicted ORF table; transcript-coord input,\n                 lifted to genomic blocks against the GTF)\n  - ribotish    (Ribo-TISH predict output; GenomePos + optional Blocks)\n  - ribotricer  (Ribotricer detect-orfs translating ORFs TSV; ORF span\n                 parsed from ORF_ID, multi-exon blocks recovered by\n                 intersecting with host-transcript exon structure from\n                 the GTF)\n  - rpbp        (Rp-Bp predicted-orfs BED12 with extra columns)\n  - price       (PRICE orfs.tsv; Gedi-style Location field, already genomic)\n\nOutput BED12 column order:\n  chrom start end name score strand thickStart thickEnd itemRgb\n  blockCount blockSizes blockStarts\nThe BED `name` column carries `<caller>|<caller-native-id>`. The BED `score`\ncolumn is the caller's native score rescaled to 0-1000 (higher == more\nconfident regardless of native direction).\n\nOutput sidecar TSV columns:\n  orf_id caller sample_id chrom start end strand gene_id transcript_id\n  orf_class aa_length score orf_type_native is_smorf\n\n`orf_type_native` carries the caller's own ORF-type label verbatim, so every\nharmonisation decision below stays auditable without re-running the caller.\nORF-type tokens are matched exactly (casefolded) against each caller's closed\nvocabulary, on the part before any colon so that a qualified label such as\nRibo-TISH's `Novel:CDSFrameOverlap` matches on `Novel`. Tokens whose location\nmatches no entry cause the process to fail; successful outputs report\n`unmapped_orf_type=0` on the `# parser_columns:` provenance line.\n\n`orf_class` is purely positional: it records where the ORF sits relative to\nthe annotated CDS and never encodes its length. Select small ORFs with the\n`is_smorf` column (`aa_length` <= `--smorf-max-aa`, default 100).\n\n`aa_length` is derived as `(nucleotide_length - 3) // 3` for every caller\nexcept Ribo-TISH, whose `AALen` column is taken verbatim. If `AALen` counts\nthe stop codon, `is_smorf` is caller-dependent by one residue exactly at the\n`--smorf-max-aa` boundary. Not reconciled: it needs a Ribo-TISH run whose\nnucleotide lengths can be compared against `AALen` directly.\n\nHarmonised `orf_class` vocabulary written into the sidecar TSV:\n\n  - canonical_cds: ORF maps to an annotated CDS (including truncated /\n                   extended variants of one).\n  - uORF:          upstream ORF, not overlapping the CDS.\n  - uoORF:         upstream ORF overlapping the CDS out of frame.\n  - dORF:          downstream ORF, not overlapping the CDS.\n  - doORF:         downstream ORF overlapping the CDS out of frame.\n  - intORF:        ORF contained within the CDS, out of frame.\n  - novel_u:       novel / intergenic ORF not assigned to an annotated CDS.\n  - other:         anything a caller cannot place.\n\nNot every caller can report every class, so the absence of a class for one\ncaller is a tool limitation rather than evidence about the ORF:\n\n  - Ribo-TISH's `5'UTR` covers both uORF and uoORF, and `3'UTR` both dORF\n    and doORF: `tisType()` tests only the start position.\n  - PRICE's vocabulary has no doORF.\n  - ribotricer's `internal` is the terminal fall-through of\n    `check_orf_type()` rather than a positive out-of-frame call, so it maps\n    to `other`; mapping it to intORF would assert a frame relationship\n    ribotricer never tested.\n\nPer-caller mapping notes (lossy collapses):\n\n  - PRICE's `Gene` column concatenates every gene overlapping an ORF's\n    genomic span, so `gene_id` is resolved from the GTF via the ORF's\n    transcript id; the `Gene` column is used only for transcripts absent\n    from the annotation, and can then carry a multi-gene value.\n  - PRICE `iORF` maps to `intORF` and `orphan` to `novel_u` (it is both the\n    not-transcript-consistent label and PRICE's fall-through). `intronic`\n    has no positional equivalent and maps to `other`. The exact PRICE\n    sub-type is preserved in `orf_type_native`.\n  - Rp-Bp's predicted-orfs BED carries no ORF-type column; this module\n    defaults every Rp-Bp call to `canonical_cds` (the post-\n    selectfinalpredictionset curated set is dominated by canonical\n    CDSs). uORF/dORF/novel calls present in Rp-Bp's separate\n    `.tab.gz` / `extracted-orfs.bed.gz` files are not propagated here.\n\nEach caller's native confidence score has a \"direction\" - some are\nlower-is-better (p-values), some are higher-is-better (Bayes factors,\nphase scores):\n\n  ribocode:   min  (combined p-value)\n  ribotish:   min  (combined p-value)\n  ribotricer: max  (phase_score)\n  rpbp:       max  (Bayes factor mean)\n  price:      min  (p-value)\n\nDownstream merging uses this to pick the best per-ORF call. (tools: orfnormalise)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "gedi_price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "custom_orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c", "fcsgx_cleangenome": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome asse"}}, "target": "custom_orfnormalise", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_43", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_bam_dedup_stats_samtools_umitools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats (tools: bam_dedup_stats_samtools_umitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "calder2": "Hierarchical Hi-C compartment computation", "bam_dedup_stats_samtools_umitools": "UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats", "fgbio_zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub"}}, "target": "bam_dedup_stats_samtools_umitools", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "assay_type": "RNA gene fusion detection (Arriba, STAR-Fusion)", "data_format": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end oncology RNA-seq reads for chimeric transcript discovery?", "criteria": {"sample,fusion_bed": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "pipe_all101_methylseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair. Topics: bisulfite-sequencing, dna-methylation, em-seq, epigenome, epigenomics, methyl-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"eager": null, "methylseq": null, "readsimulator": null, "demo": null, "rnaseq": null, "cutandrun": null, "scnanoseq": null, "chipseq": null}}, "target": "methylseq", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_4_1", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,matrix,contacts": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_0", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_strelka_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA", "modules": ["gatk4/mergevcfs", "strelka/somatic"], "description": "Perform variant calling on a paired tumor normal set of samples using strelka somatic mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA (gatk4/mergevcfs, strelka/somatic) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA": null, "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_2_5", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_hmmsearch_rank_fastas_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_HMMSEARCH_RANK_FASTAS", "modules": ["hmmer/hmmsearch", "hmmer/hmmrank", "seqtk/subseq"], "description": "Run hmmsearch and output separate fasta files for top scoring hits to each profile"}, "question": {"type": "choice", "instructions": "How should FASTA_HMMSEARCH_RANK_FASTAS (hmmer/hmmsearch, hmmer/hmmrank, seqtk/subseq) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTA_HMMSEARCH_RANK_FASTAS": null, "Use nf-core subworkflow fasta_hmmsearch_rank_fastas": null}}, "target": "Use nf-core subworkflow fasta_hmmsearch_rank_fastas", "target_idx": 3}
{"id": "core_tool_mutect2_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Somatic short variant detection (SNVs and small indels) comparing matched tumor and normal sequencing data with Bayesian somatic likelihood filtering.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"mutect2": "Call somatic SNVs and indels via local assembly of haplotypes with tumor/normal comparison", "varscan2": "Somatic caller", "somaticsniper": "Somatic SNV caller", "strelka2": "Fast somatic caller", "vardict": "Variant caller"}}, "target": "mutect2", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/smrnaseq) for Small RNA / miRNA sequencing. Input files: Single-end 50bp miRNA reads with 3-prime adapter.", "question": {"type": "choice", "instructions": "Which columns are standard for Small RNA / miRNA sequencing input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,mirna_id": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_ngsbits_samplegender_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determines the gender of a sample from the BAM/CRAM file. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "ngsbits_samplegender": "Determines the gender of a sample from the BAM/CRAM file.", "fastq_align_dedup_bwamem": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate", "disambiguate": "Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ fi"}}, "target": "ngsbits_samplegender", "target_idx": 2}
{"id": "resource_bcftools_pluginsplit_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSPLIT", "tool": "bcftools/pluginsplit", "description": "Split VCF by sample, creating single- or multi-sample VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSPLIT (Split VCF by sample, creating single- or multi-sample VCFs.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_seqfu_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Statistics for FASTA or FASTQ files (tools: seqfu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_qc_stats": "Generate statistics for short read sequencing data using multiple tools", "seqkit/seq": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "seqfu/stats": "Statistics for FASTA or FASTQ files", "saltshaker/call": "mtDNA deletion and duplication calling downstream of mitosalt", "custom/collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op"}}, "target": "seqfu/stats", "target_idx": 2}
{"id": "resource_bcftools_pluginfilltags_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFILLTAGS", "tool": "bcftools/pluginfilltags", "description": "Compute and fill various INFO tags"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFILLTAGS (Compute and fill various INFO tags) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_ucsc_gtftogenepred_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert GTF files to GenePred format (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spflagshortintrons": null, "agat_spkeeplongestisoform": null, "ucsc_wigtobigwig": null, "ucsc_gtftogenepred": null, "meryl_histogram": null}}, "target": "ucsc_gtftogenepred", "target_idx": 3}
{"id": "mod_fastq_remove_rrna_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2 (tools: fastq_remove_rrna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_remove_rrna": "Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2", "shinyngs/staticexploratory": "Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "ariba/run": "Query input FASTQs against Ariba formatted databases", "varlociraptor/callvariants": "Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlocira"}}, "target": "fastq_remove_rrna", "target_idx": 0}
{"id": "mod_gnu_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Writes a sorted concatenation of file/s (tools: gnu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_generateplot": "BUSCO plot generation tool", "gnu_sort": "Writes a sorted concatenation of file/s", "clame": "binning of metagenomic sequences", "crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs", "mcstaging_imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata."}}, "target": "gnu_sort", "target_idx": 1}
{"id": "resource_abricate_summary_2", "category": "resource_profiling", "state": {"process": "ABRICATE_SUMMARY", "tool": "abricate/summary", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_SUMMARY (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_clustalo_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align sequences using Clustal Omega (tools: clustalo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/merge": null, "ashlar": null, "nonpareil/nonpareil": null, "abra2": null, "clustalo/align": null}}, "target": "clustalo/align", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_bam_1_3", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_bwaaln_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWAALN", "modules": ["bwa/aln", "bwa/sampe", "bwa/samse", "samtools/index"], "description": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWAALN (bwa/aln, bwa/sampe, bwa/samse, samtools/index) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_BWAALN": null, "Use nf-core subworkflow fastq_align_bwaaln": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_align_bwaaln", "target_idx": 2}
{"id": "local_subworkflow_nextclade_2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for NEXTCLADE (nextclade/run).", "criteria": {"Local subworkflow NEXTCLADE": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow nextclade": null, "Leave them out": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 0}
{"id": "samplesheet_arch_germline_lane_split_6_0", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multi-lane Illumina sequencing run of clinical samples input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bcftools_norm_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_NORM", "tool": "bcftools/norm", "description": "Normalize VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_NORM (Normalize VCF file) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_samplesheetparser_info_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample count, lanes, index type, read lengths,\nadapter sequences, experiment name, and instrument platform.\nUseful for logging run metadata or conditional branching in pipelines. (tools: samplesheet-parser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser_info": null, "cellranger_mkfastq": null, "mm2plus_align": null, "bcl2fastq": null, "plasmidid": null}}, "target": "samplesheetparser_info", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_35", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_30", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_hmmer_hmmbuild_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: create an hmm profile from a multiple sequence alignment (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"holodeck_simulate": "Simulate sequencing reads from a reference genome with holodeck", "gatk4_mergemutectstats": "Merges mutect2 stats generated on different intervals/regions", "skani_search": "Memory-efficient ANI database queries with skani.", "entrezdirect_xtract": "Queries an NCBI database using an UID", "hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment"}}, "target": "hmmer_hmmbuild", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_1_23", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_align_hisat2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_HISAT2", "modules": ["hisat2/align", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using hisat2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_HISAT2 (hisat2/align, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_HISAT2": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_hisat2": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_align_hisat2", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_1_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_blobtk_depth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a bed file containing the depth of data at intervals of an aligned bam. (tools: blobtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk_depth": "Creates a bed file containing the depth of data at intervals of an aligned bam.", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "portcullis_full": "Run all Portcullis steps in one go", "bamclipper": "This module is used to clip primer sequences from your alignments.", "deeptools_plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu"}}, "target": "blobtk_depth", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_4_2", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed single-end long reads from tiled viral amplicons?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "field_constraint_fastq_2_1_8", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_6_5", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Viral amplicon sequencing with primers input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_oatk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An nf-core module for the OATK (tools: oatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"getorganelle_fromreads": "Assembles organelle genomes from genomic data", "plink2_pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "oatk": "An nf-core module for the OATK", "samtools_sormadup": "Collate/Fixmate/Sort/Markdup SAM/BAM/CRAM file", "mitohifi_mitohifi": "A python workflow that assembles mitogenomes from Pacbio HiFi reads"}}, "target": "oatk", "target_idx": 2}
{"id": "schema_std_sopa_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sopa", "description": "Nextflow version of Sopa - spatial omics pipeline and analysis", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/sopa?", "criteria": {"sample,alleles,mhc_class,filename": null, "sample,fastq_1,fastq_2,library_id,lane": null, "sample,fastq_1,fastq_2,replicate,control": null, "sample,id,data_path,fastq_dir,cytaimage": null}}, "target": "sample,id,data_path,fastq_dir,cytaimage", "target_idx": 3}
{"id": "pipe_all101_variantprioritization_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for variantprioritization. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]"}}, "target": "variantprioritization", "target_idx": 5}
{"id": "qc_adapt_targeted_amplicon_1_39", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_1_3", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "field_constraint_fastq_2_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "mod_gatk4_createsomaticpanelofnormals_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a panel of normals constraining germline and artifactual sites for use with mutect2. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "elprep_fastatoelfasta": "Convert a file in FASTA format to the ELFASTA format", "gatk4_createsomaticpanelofnormals": "Create a panel of normals constraining germline and artifactual sites for use with mutect2.", "fgbio_callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag.", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "gatk4_createsomaticpanelofnormals", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_4_1", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,primer_its1,primer_its2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_31", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_channel_collect_operator_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_gzrt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupted (tools: gzrt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "kaiju/kaiju2krona": "Convert Kaiju's tab-separated output file into a tab-separated text file which can be imported into Krona.", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt", "ariba/getref": "Download and prepare database for Ariba analysis", "ariba/run": "Query input FASTQs against Ariba formatted databases"}}, "target": "gzrt", "target_idx": 2}
{"id": "resource_adapterremovalfixprefix_0", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVALFIXPREFIX", "tool": "adapterremovalfixprefix", "description": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with DeDup."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVALFIXPREFIX (Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names a) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking. Input files: Circulating tumor DNA FASTQs across patient clinical draw intervals.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bio2zarr_vcf2zarrconvert_5", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARRCONVERT", "tool": "bio2zarr/vcf2zarrconvert", "description": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARRCONVERT (Convert VCF data to the VCF Zarr specification reliably, in parallel or distribu) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_pirate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pangenome toolbox for bacterial genomes (tools: pirate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_indeppairwise": null, "pirate": null, "agat_convertbed2gff": null, "faa_seqfu_seqkit": null, "agat_convertspgff2gtf": null}}, "target": "pirate", "target_idx": 1}
{"id": "mod_pharmcat_reporter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescribing recommendations for clinical decision support. (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone_copy": null, "pharmcat_matcher": null, "ribotish_predict": null, "pharmcat_reporter": null, "pharmcat_phenotyper": null}}, "target": "pharmcat_reporter", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay_type": "PacBio HiFi unaligned BAM variant calling", "data_format": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "mod_utils_nfvalidation_plugin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use nf-validation to initiate and validate a pipeline (tools: utils_nfvalidation_plugin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proteus/readproteingroups": "reads a maxQuant proteinGroups file with Proteus", "fastavalidator": "\"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror lo", "utils_references": "Functionality for dealing with references that may be useful for any Nextflow pipeline", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD"}}, "target": "utils_nfvalidation_plugin", "target_idx": 3}
{"id": "mod_carveme_carve_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe (tools: carveme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq_requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "carveme_carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "scanpy_filter": "Filter cells and genes in single-cell RNA-seq data using Scanpy", "chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files.", "gapseq_medium": "Predict growth medium from a draft model and pathway predictions"}}, "target": "carveme_carve", "target_idx": 1}
{"id": "mod_unzipfiles_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unzip ZIP archive files (tools: unzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl_align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection", "gunzip": "Compresses and decompresses files.", "bedtools_getfasta": "extract sequences in a FASTA file based on intervals defined in a feature file.", "unzipfiles": "Unzip ZIP archive files", "unzip": "Unzip ZIP archive files"}}, "target": "unzipfiles", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_20", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_samplesheetparser_info_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample count, lanes, index type, read lengths,\nadapter sequences, experiment name, and instrument platform.\nUseful for logging run metadata or conditional branching in pipelines. (tools: samplesheet-parser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser/info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "bases2fastq": "Demultiplex Element Biosciences bases files", "merquryfk/ploidyplot": "An improved version of Smudgeplot using FastK", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "cellrangerarc/mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma"}}, "target": "samplesheetparser/info", "target_idx": 0}
{"id": "mod_chewbbaca_createschema_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a schema to determine the allelic profiles of a genome (tools: chewbbaca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ichorcna_createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "purecn_run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "chewbbaca_createschema": "Create a schema to determine the allelic profiles of a genome", "foldseek_createdb": "Create a database from protein structures", "chewbbaca_allelecall": "Determine the allelic profiles of a genome using a pre-defined schema"}}, "target": "chewbbaca_createschema", "target_idx": 2}
{"id": "resource_bbmap_bbsplit_3", "category": "resource_profiling", "state": {"process": "BBMAP_BBSPLIT", "tool": "bbmap/bbsplit", "description": "Split sequencing reads by mapping them to multiple references simultaneously"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBSPLIT (Split sequencing reads by mapping them to multiple references simultaneously) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "intent_prepare_data_14", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "prepare_data", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_48", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_gsea_gsea_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: run the Broad Gene Set Enrichment tool in GSEA mode (tools: gsea)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_filterdifferentialtable": "Filters a differential expression table based on logFC and adjusted p-value thresholds", "gprofiler2_gost": "runs a functional enrichment analysis with gprofiler2", "purgedups_purgedups": "Purge haplotigs and overlaps for an assembly", "gsea_gsea": "run the Broad Gene Set Enrichment tool in GSEA mode", "custom_tabulartogseacls": "Make a GSEA class file (.cls) from tabular inputs"}}, "target": "gsea_gsea", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_5_5", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Long-read Oxford Nanopore environmental metagenomic sequencing.", "criteria": {"sample,fastq_1,group": null, "sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq with strandedness", "data_format": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "resource_bowtie_build_2", "category": "resource_profiling", "state": {"process": "BOWTIE_BUILD", "tool": "bowtie/build", "description": "Create bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_BUILD (Create bowtie index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_phenotype_1_9", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "enum: [normal, tumor]": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic tumor-normal calling from pre-aligned BAM files)", "question": {"type": "choice", "instructions": "Which columns are standard for Somatic tumor-normal calling from pre-aligned BAM files input samplesheet?", "criteria": {"patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "resource_bbmap_align_0", "category": "resource_profiling", "state": {"process": "BBMAP_ALIGN", "tool": "bbmap/align", "description": "Align short or PacBio reads to a reference genome using BBMap"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_ALIGN (Align short or PacBio reads to a reference genome using BBMap) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_45", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "schema_std_omicsgenetraitassociation_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/omicsgenetraitassociation. Description: A nextflow pipeline which integrates multiple omic data streams and performs coordinated analysis.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/omicsgenetraitassociation.", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "sample,fastq_1,fastq_2,genome": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "sample,trait,pascal,twas,additional_sources", "target_idx": 0}
{"id": "field_constraint_strandedness_1_0", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"type: boolean": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "subworkflow_pkg_bam_split_by_region_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SPLIT_BY_REGION", "modules": ["samtools/view", "samtools/index"], "description": "Split the reads in the input bam by specified genomic region."}, "question": {"type": "choice", "instructions": "How should BAM_SPLIT_BY_REGION (samtools/view, samtools/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_split_by_region": null, "Local subworkflow BAM_SPLIT_BY_REGION": null}}, "target": "Use nf-core subworkflow bam_split_by_region", "target_idx": 2}
{"id": "mod_fastq_fastqc_umitools_trimgalore_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read QC, UMI extraction and trimming (tools: fastq_fastqc_umitools_trimgalore)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "fastq_fastqc_umitools_trimgalore": "Read QC, UMI extraction and trimming", "meryl/histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "mosdepth": "Calculates genome-wide sequencing coverage."}}, "target": "fastq_fastqc_umitools_trimgalore", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_33", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_rhocall_viz_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call regions of homozygosity and make tentative UPD calls (tools: rhocall)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/rohviz": "Visualise the output of bcftools roh", "vcf_annotate_ensemblvep": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file", "rhocall/annotate": "Markup VCF file using rho-calls.", "strdrop/call": "Detect drops in STR coverage", "rhocall/viz": "Call regions of homozygosity and make tentative UPD calls"}}, "target": "rhocall/viz", "target_idx": 4}
{"id": "field_constraint_sample_0_14", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"format: file-path": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "field_constraint_sample_0_1", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_4_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single fastq per sample?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "noul_exit_code_137_cause_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_ampcombi_5", "category": "resource_profiling", "state": {"process": "AMPCOMBI", "tool": "ampcombi", "description": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI (A tool to parse and summarise results from antimicrobial peptides tools and pres) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_cageseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags.. Topics: cage, cage-seq, cageseq-data, gene-expression, rna. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "metapep": "From metagenomes to epitopes and beyond", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]"}}, "target": "cageseq", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_align_mapad_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_MAPAD", "modules": ["mapad/map", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_MAPAD (mapad/map, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_mapad": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_MAPAD": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_mapad", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_45", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_melon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs taxonomic profiling of long metagenomic reads against the melon database (tools: melon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"minibwa_map": "Align fastq reads to a fasta reference using minibwa", "expansionhunterdenovo_profile": "Compute genome-wide STR profile", "hmmer_hmmstat": "display summary statistics for each profile HMM in an HMM database file", "melon": "Performs taxonomic profiling of long metagenomic reads against the melon database", "octopusv_plotcircos": "Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file."}}, "target": "melon", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_4_0", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Circulating tumor DNA FASTQs across patient clinical draw intervals?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_2_4", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin", "pipeline": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_5_5", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Genome analysis from reference-compressed CRAM files.", "criteria": {"sample,cram,crai": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,cram,crai", "target_idx": 0}
{"id": "resource_bedops_gtf2bed_0", "category": "resource_profiling", "state": {"process": "BEDOPS_GTF2BED", "tool": "bedops/gtf2bed", "description": "Convert gtf format to bed format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_GTF2BED (Convert gtf format to bed format) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_mmseqs_createtaxdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds taxonomy information to an existing MMseqs2 database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/createindex": null, "mmseqs/easysearch": null, "orfm": null, "glimpse/sample": null, "mmseqs/createtaxdb": null}}, "target": "mmseqs/createtaxdb", "target_idx": 4}
{"id": "local_subworkflow_preparereports_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should this step (custom/preparereports, multiqc) be packaged: Custom aggregation and MultiQC reporting?", "criteria": {"Local subworkflow PREPAREREPORTS": null, "Use nf-core subworkflow preparereports": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 0}
{"id": "core_tool_kallisto_bustools_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Ultra-fast pseudoalignment and barcode/UMI processing for single-cell RNA-seq generating bustools count matrices.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"starsolo": null, "alevin": null, "salmon": null, "kallisto_bustools": null, "cellranger": null}}, "target": "kallisto_bustools", "target_idx": 3}
{"id": "mod_bowtie2_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bowtie2 (tools: bowtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "bowtie2/align": "Align reads to a reference genome using bowtie2", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "atlas/recal": "Gives an estimation of the sequencing bias based on known invariant sites", "custom/multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "bowtie2/align", "target_idx": 1}
{"id": "noul_channel_collect_operator_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_wisecondorx_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find copy number aberrations (tools: wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "wisecondorx_predict": "Find copy number aberrations", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "dssp_mkdssp": "Calculates secondary structure assignments from PDB files using mkdssp (DSSP).\nDSSP is a standard tool for ass", "pairtools_stats": "Calculate pairs statistics"}}, "target": "wisecondorx_predict", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_4_0", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter", "pipeline": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end 50bp miRNA reads with 3-prime adapter?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_channel_collect_operator_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_kmergenie_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KmerGenie estimates the best k-mer length for genome de novo assembly (tools: kmergenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastk_fastk": null, "kmergenie": null, "fungtion_downloadmodels": null, "controlfreec_assesssignificance": null, "fastk_histex": null}}, "target": "kmergenie", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_36", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_faire_seq_chromatin_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for FAIRE-seq / DNAse-seq open chromatin profiling. Input files: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: FAIRE-seq / DNAse-seq open chromatin profiling.", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "intent_prepare_data_23", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "prepare_data": null, "build_pipeline": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 1}
{"id": "local_subworkflow_variantsofint_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should VARIANTSOFINT (custom/variantsofint) be built?", "criteria": {"Use nf-core subworkflow variantsofint": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow VARIANTSOFINT": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_2_5", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,environment": null, "sample,fastq_1": null, "sample,bam": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 0}
{"id": "pipe_all101_seqinspector_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput.. Topics: genomics, quality-control. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. "}}, "target": "seqinspector", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_46", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "assay_type": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "data_format": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fastq_1,fastq_2,long_fastq": null, "sample,bam": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 0}
{"id": "schema_std_bacass_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "description": "Simple bacterial assembly and annotation pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/bacass?", "criteria": {"sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,condition,assay,peak_file,footprinting": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,fastq_1,fastq_2,barcode": null}}, "target": "ID,R1,R2,LongFastQ,Fast5", "target_idx": 2}
{"id": "noul_process_conditional_execution_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_differential_functional_enrichment_3", "category": "subworkflow_packaging", "state": {"subworkflow": "DIFFERENTIAL_FUNCTIONAL_ENRICHMENT", "modules": ["gprofiler2/gost", "gsea/gsea", "decoupler/decoupler", "propr/grea", "custom/tabulartogseagct", "custom/tabulartogseacls", "custom/tabulartogseachip"], "description": "Run functional analysis on differential abundance analysis output"}, "question": {"type": "choice", "instructions": "How should DIFFERENTIAL_FUNCTIONAL_ENRICHMENT (gprofiler2/gost, gsea/gsea, decoupler/decoupler, propr/grea, custom/tabulartogseagct, custom/tabulartogseacls, custom/tabulartogseachip) be structured in DSL2?", "criteria": {"Use nf-core subworkflow differential_functional_enrichment": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow DIFFERENTIAL_FUNCTIONAL_ENRICHMENT": null}}, "target": "Use nf-core subworkflow differential_functional_enrichment", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_0_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fasta": null, "sample,bam": null, "sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "schema_std_rnafusion_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "assay": "rnafusion pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnafusion (RNA-seq analysis pipeline for detection of gene-fusions)?", "criteria": {"sample,fastq_1,fastq_2,bam,bai": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_11", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_methyldackel_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts per-base methylation metrics from alignments (tools: methyldackel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "pbtk/pbindex": "Minimalistic tool which creates an index file that enables random access into PacBio BAM files", "bismark/report": "Collects bismark alignment reports", "vembrane/table": "Creates tabular (TSV) files from VCF/BCF data with flexible Python expressions", "methyldackel/extract": "Extracts per-base methylation metrics from alignments"}}, "target": "methyldackel/extract", "target_idx": 4}
{"id": "mod_happy_happy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row, hap.py will generate and match alternate sequences in a superlocus. A superlocus is a small region of the genome (sized between 1 and around 1000 bp) that contains one or more variants. (tools: happy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy_sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic ", "happy_prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "happy_happy": "Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row", "mageck_test": "Mageck test performs a robust ranking aggregation (RRA) to identify positively or negatively selected genes in"}}, "target": "happy_happy", "target_idx": 3}
{"id": "mod_xeniumranger_resegment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger resegment module allows you to generate a new segmentation of the morphology image space by rerunning the Xenium Onboard Analysis (XOA) segmentation algorithms with modified parameters. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proseg_proseg2baysor": null, "gnu_sort": null, "scimap_mcmicro": null, "xeniumranger_resegment": null, "authentict_deam2cont": null}}, "target": "xeniumranger_resegment", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_46", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_yte_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A YAML template engine with Python expressions (tools: yte)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass.", "quarto_prerender": "Pre-render a Quarto document to markdown, including parametrization", "custom_pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi", "jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill.", "yte": "A YAML template engine with Python expressions"}}, "target": "yte", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_2_30", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_tcoffee_regressive_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/regressive": "Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "fastq_qc_stats": "Generate statistics for short read sequencing data using multiple tools", "eido/validate": "Validate samplesheet or PEP config against a schema", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "tcoffee/regressive", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Xenium in situ subcellular spatial RNA transcriptomics)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Xenium in situ subcellular spatial RNA transcriptomics with entry step INPUT_CHECK.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "mod_hifiadapterfilt_downloaddb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database contains two adapter sequences: NGB00972.1\n(Pacific Biosciences Blunt Adapter, 45 bp) and NGB00973.1 (C2 Primer, 35 bp).\nThis module is consumed by hifiadapterfilt/hifiadapterfilt as a prerequisite to\nprovide the BLAST database for adapter detection. (tools: hifiadapterfilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "hifiadapterfilt/hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "foldcomp/compress": "Efficient compression tool for protein structures", "bam2fastx/bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "varlociraptor/preprocess": "Obtains per-sample observations for the actual calling process with varlociraptor calls"}}, "target": "hifiadapterfilt/downloaddb", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_0_1", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,bed": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "mod_falint_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fasta linter/validator (tools: falint)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/update": null, "tcoffee/alncompare": null, "agat/spextractsequences": null, "tsebra": null, "falint": null}}, "target": "falint", "target_idx": 4}
{"id": "resource_bases2fastq_0", "category": "resource_profiling", "state": {"process": "BASES2FASTQ", "tool": "bases2fastq", "description": "Demultiplex Element Biosciences bases files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASES2FASTQ (Demultiplex Element Biosciences bases files) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_cat_fastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are automatically gzip-compressed during concatenation. (tools: cat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/sormadup": null, "gatk4/applyvqsr": null, "fasta_classify_catpack": null, "cat/fastq": null, "scanpy/pca": null}}, "target": "cat/fastq", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_2_37", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_gatk4_mutect2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call somatic SNVs and indels via local assembly of haplotypes. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylphtax_taxprof": null, "gatk4_baserecalibrator": null, "gatk4_mutect2": null, "gatk4_applyvqsr": null, "pbptyper": null}}, "target": "gatk4_mutect2", "target_idx": 2}
{"id": "resource_beagle5_beagle_1", "category": "resource_profiling", "state": {"process": "BEAGLE5_BEAGLE", "tool": "beagle5/beagle", "description": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEAGLE5_BEAGLE (Beagle v5.5 is a software package for phasing genotypes and for imputing ungenot) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_2_0", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_0_12", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_pharmcat_phenotyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The PharmCAT Phenotyper is a core module of the Pharmacogenomics Clinical Annotation Tool\nthat translates patient diplotypes into specific, actionable metabolizer phenotypes\n(e.g., Poor Metabolizer). It operates by analyzing the JSON output from the Named\nAllele Matcher, mapping these results to established clinical guidelines (such as\nCPIC) to predict drug response. (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_split_by_region": "Split the reads in the input bam by specified genomic region.", "pharmcat/phenotyper": "The PharmCAT Phenotyper is a core module of the Pharmacogenomics Clinical Annotation Tool\nthat translates pati", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "ucsc/wigtobigwig": "Convert ascii format wig file to binary big wig format", "bcftools/annotate": "Add or remove annotations."}}, "target": "pharmcat/phenotyper", "target_idx": 1}
{"id": "mod_nextgenmap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using NextGenMap (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "plink2_pca": "Perform PCA analysis using PLINK", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "nextgenmap": "Performs fastq alignment to a fasta reference using NextGenMap"}}, "target": "nextgenmap", "target_idx": 4}
{"id": "mod_concoct_cutupfasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cut up fasta file in non-overlapping or overlapping parts of equal length. (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "picard_collectinsertsizemetrics": "Collect metrics about the insert size distribution of a paired-end library.", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "kofamscan": "Produces annotation using kofamscan against a Profile database and a KO list", "concoct_concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile"}}, "target": "concoct_cutupfasta", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_2_7", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "field_constraint_fastq_2_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "type: required string": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_bamutil_clipoverlap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality. (tools: bamutil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": null, "kallisto/index": null, "quast": null, "ascat": null, "bamutil/clipoverlap": null}}, "target": "bamutil/clipoverlap", "target_idx": 4}
{"id": "intent_build_pipeline_20", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_backsub_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data. (tools: backsub)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging/phenoimager2mc": "Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per c", "mcstaging/imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata.", "nextclade/datasetget": "Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ impleme", "backsub": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data.", "metacache/build": "Taxonomic profiling database building with MetaCache"}}, "target": "backsub", "target_idx": 3}
{"id": "noul_invalid_process_communication_via_globals_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_rnastructurome_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data. Topics: dms, map, rna-structure, rnacentral, rnaframework, rt-stop. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnastructurome": null, "crisprseq": null, "bamtofastq": null, "funcprofiler": null, "isoseq": null}}, "target": "rnastructurome", "target_idx": 0}
{"id": "field_constraint_status_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "pipe_all101_seqinspector_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for genomics analysis? Specific context: Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput.. Topics: genomics, quality-control. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp"}}, "target": "seqinspector", "target_idx": 7}
{"id": "mod_plink_fastepistasis_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ensemblvep_filtervep": null, "freyja_boot": null, "prinseqplusplus": null, "plink_epistasis": null, "plink_fastepistasis": null}}, "target": "plink_fastepistasis", "target_idx": 4}
{"id": "resource_agat_spaddintrons_1", "category": "resource_profiling", "state": {"process": "AGAT_SPADDINTRONS", "tool": "agat/spaddintrons", "description": "Add intron features to gtf/gff file without intron features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPADDINTRONS (Add intron features to gtf/gff file without intron features.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_blast_updateblastdb_3", "category": "resource_profiling", "state": {"process": "BLAST_UPDATEBLASTDB", "tool": "blast/updateblastdb", "description": "Downloads a BLAST database from NCBI"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_UPDATEBLASTDB (Downloads a BLAST database from NCBI) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_0_47", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_virusrecom_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Information-theory-based method for recombination detection of viral lineages using weighted information content (WIC). (tools: virusrecom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"virusrecom": "Information-theory-based method for recombination detection of viral lineages using weighted information conte", "checkv/endtoend": "Assess the quality of metagenome-assembled viral genomes.", "minimac4/impute": "Imputation of genotypes using a reference panel", "catpack/summarise": "Summarises results from CAT/BAT/RAT classification steps", "gubbins": "Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively iden"}}, "target": "virusrecom", "target_idx": 0}
{"id": "pipe_core10_atacseq_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Assay for Transposase-Accessible Chromatin to quantify differential accessibility between drug-treated and untreated lymphocytes.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"chipseq": null, "viralrecon": null, "ampliseq": null, "rnaseq": null, "sarek": null, "taxprofiler": null, "scrnaseq": null, "mag": null, "eager": null, "atacseq": null}}, "target": "atacseq", "target_idx": 9}
{"id": "samplesheet_arch_ancient_dna_eager_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/eager --input samplesheet.csv (Assay: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_mmseqs_createtaxdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds taxonomy information to an existing MMseqs2 database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit_aggbw": "Aggregates a bigWig signal over constant-length intervals\ndefined in a BED file.", "mmseqs_createindex": "Creates sequence index for mmseqs database", "last_postmask": "Post-alignment masking", "mmseqs_createtaxdb": "Adds taxonomy information to an existing MMseqs2 database", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file"}}, "target": "mmseqs_createtaxdb", "target_idx": 3}
{"id": "resource_atlasgeneannotationmanipulation_gtf2featureannotation_0", "category": "resource_profiling", "state": {"process": "ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION", "tool": "atlasgeneannotationmanipulation/gtf2featureannotation", "description": "Generate tables of feature metadata from GTF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION (Generate tables of feature metadata from GTF files) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_fgbio_collectduplexseqmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects a suite of metrics to QC duplex sequencing data. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag.", "plasmidfinder": "Identify plasmids in bacterial sequences and assemblies", "fgumi_downsample": "Downsample a BAM by UMI family using streaming with fgumi", "fgbio_collectduplexseqmetrics": "Collects a suite of metrics to QC duplex sequencing data.", "fastq_align_hisat2": "Align reads to a reference genome using hisat2 then sort with samtools"}}, "target": "fgbio_collectduplexseqmetrics", "target_idx": 3}
{"id": "mod_hpsuissero_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotype prediction of Haemophilus parasuis assemblies (tools: hpsuissero)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hpsuissero": "Serotype prediction of Haemophilus parasuis assemblies", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "bcl2fastq": "Demultiplex Illumina BCL files", "samtools/depth": "Computes the depth at each position or region."}}, "target": "hpsuissero", "target_idx": 0}
{"id": "noul_module_metadata_propagation_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_rustqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, and SAMtools stats (tools: rustqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "samtools/getrg": "filter/convert SAM/BAM/CRAM file", "rustqc": "All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, an"}}, "target": "rustqc", "target_idx": 4}
{"id": "noul_container_environment_specification_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "schema_std_marsseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/marsseq", "assay": "marsseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/marsseq (MARS-seq v2 pre-processing pipeline with velocity)?", "criteria": {"fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "id,path": null, "sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "fastq_1,fastq_2,batch,amp_batches,seq_batches", "target_idx": 0}
{"id": "schema_std_abotyper_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/abotyper", "assay": "abotyper pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/abotyper (A pipeline for characterising the Human Blood Group and Red )?", "criteria": {"sample,fastq_1,fastq_2,vcf": null, "sample,fastq_1,fastq_2,strandedness,type": null, "sample,alleles,mhc_class,filename": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_goatools_findenrichment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find enriched GO terms in a list of genes (tools: goatools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi/sort": "Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm.", "decoupler/decoupler": "decoupler is a package containing different statistical methods\nto extract biological activities from omics da", "caddsv/run": "Score structural variants with CADD-SV.", "homer/findpeaks": "Find peaks with HOMER suite", "goatools/findenrichment": "Find enriched GO terms in a list of genes"}}, "target": "goatools/findenrichment", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_40", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_bcftools_consensus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses VCF files (tools: consensus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "oarfish/alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "bcftools/consensus": "Compresses VCF files", "bcftools/filter": "Filters VCF files"}}, "target": "bcftools/consensus", "target_idx": 3}
{"id": "pipe_all101_callingcards_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for callingcards. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "callingcards": "A pipeline for processing calling cards data", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]"}}, "target": "callingcards", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_26", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_blast_tblastn_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a BLAST DNA database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm2/predict": "CheckM2 bin quality prediction", "fastq_create_umi_consensus_fgbio": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads\nconvert them to unmapped B", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "blast/tblastn": "Queries a BLAST DNA database", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}}, "target": "blast/tblastn", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_9", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_7", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_undeclared_process_file_inputs_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_crumble_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Controllable lossy compression of BAM/CRAM files (tools: crumble)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat_fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "crumble": "Controllable lossy compression of BAM/CRAM files", "entrezdirect_xtract": "Queries an NCBI database using an UID", "mmseqs_createtaxdb": "Adds taxonomy information to an existing MMseqs2 database", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "crumble", "target_idx": 1}
{"id": "mod_hmmer_hmmrank_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: R script that scores output from multiple runs of hmmer/hmmsearch (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmrank": "R script that scores output from multiple runs of hmmer/hmmsearch", "hmmer/eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie", "eklipse": "tool for detection and quantification of large mtDNA rearrangements.", "hmmer/eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "custom/collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op"}}, "target": "hmmer/hmmrank", "target_idx": 0}
{"id": "mod_admixture_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datasets, where the individuals are unrelated (for example, the individuals in a case-control association study). (tools: admixture)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sushie": "Software to perform multi-ancestry SNP fine-mapping on molecular data", "nanolyse": "DNA contaminant removal using NanoLyse", "angsd_contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome.", "admixture": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datas", "bam_taps_conversion": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis"}}, "target": "admixture", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Metagenomic MAG assembly with comparative groups)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "schema_std_phaseimpute_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/phaseimpute", "assay": "phaseimpute pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/phaseimpute (A bioinformatics pipeline to phase and impute genetic data)?", "criteria": {"sample,fastq_1,strandedness": null, "id,raw_file": null, "sample,vcf,tbi": null, "sample,tools,file,index": null}}, "target": "sample,tools,file,index", "target_idx": 3}
{"id": "field_constraint_strandedness_1_6", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"pattern: ^[0-9]+$": null, "type: boolean": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_33", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_dna_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DNA", "modules": ["bowtie2/align", "bwa/mem", "bwamem2/mem", "dragmap/align", "snapaligner/align", "strobealign"], "description": "Align fastq files to a reference genome"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DNA (bowtie2/align, bwa/mem, bwamem2/mem, dragmap/align, snapaligner/align, strobealign) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_align_dna": null, "Local subworkflow FASTQ_ALIGN_DNA": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_dna", "target_idx": 1}
{"id": "resource_autocycler_trim_5", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_TRIM", "tool": "autocycler/trim", "description": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_TRIM (Trim cluster assembly graphs to remove unsupported segments prior to resolution.) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/hic) for Hi-C chromosome conformation capture mapping. Input files: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_fastquorum_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/fastquorum", "description": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/fastquorum?", "criteria": {"sample,fastq_1,fastq_2,library_id,lane": null, "sample,type,level,msfile": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,library_id,lane", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_27", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_6", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_scanpy_scrublet_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect doublets in single-cell RNA-seq data using Scrublet via Scanpy (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy_scrublet": "Detect doublets in single-cell RNA-seq data using Scrublet via Scanpy", "openms_psmfeatureextractor": "Computes extra features for each input PSM for use with Percolator rescoring.", "scanpy_hashsolo": "Probabilistic demultiplexing of cell hashing data", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "shinyngs_app": "build and deploy Shiny apps for interactively mining differential abundance data"}}, "target": "scanpy_scrublet", "target_idx": 0}
{"id": "mod_amulety_embed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety_embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "amulety_antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety.", "bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file", "amulety_antiberty": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety.", "rundbcan_database": "command from run_dbcan to prepare the database for dbCAN annotation."}}, "target": "amulety_embed", "target_idx": 0}
{"id": "resource_bbmap_repair_0", "category": "resource_profiling", "state": {"process": "BBMAP_REPAIR", "tool": "bbmap/repair", "description": "Re-pairs reads that became disordered or had some mates eliminated."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_REPAIR (Re-pairs reads that became disordered or had some mates eliminated.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_fastq_trim_fastp_fastqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read QC, fastp trimming and read qc (tools: fastq_trim_fastp_fastqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": null, "ensemblvep_download": null, "fastq_trim_fastp_fastqc": null, "falco": null, "ngmerge": null}}, "target": "fastq_trim_fastp_fastqc", "target_idx": 2}
{"id": "mod_vcf_impute_glimpse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference panel, and genetic maps to perform imputation\nand outputs phased and imputed VCF files.\nMeta map of all channels, except ch_input, will be used to perform joint operations.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: vcf_impute_glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse_phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods", "regtools_junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.", "glimpse_concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "survivor_bedpetovcf": "Converts a bedpe file to a VCF file (beta version)"}}, "target": "vcf_impute_glimpse", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_34", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wgs_pe_3_2", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Standard Paired-end Whole Genome Sequencing (WGS) with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_svync_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to standardize VCF files from structural variant callers (tools: svync)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "annotsv_installannotations": "Install the AnnotSV annotations", "svync": "A tool to standardize VCF files from structural variant callers", "huggingface_download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont"}}, "target": "svync", "target_idx": 2}
{"id": "schema_std_ampliseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "description": "Amplicon sequencing analysis workflow using DADA2 and QIIME2", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/ampliseq?", "criteria": {"sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,input,output_path,checksum_md5,checksum_sha": null}}, "target": "sample,fastq_1,fastq_2,sampleID,forwardReads", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_31", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_modular_subworkflow_composition_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_5_5", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: Fungal ITS1/ITS2 marker gene amplicon surveillance.", "criteria": {"sample,fastq_1": null, "sample,primer_its1,primer_its2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_mmseqs_search_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search and calculate a score for similar sequences in a query and a target database. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/cluster": "Cluster sequences using MMSeqs2 cluster.", "strelka/somatic": "Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small coh", "mmseqs/search": "Search and calculate a score for similar sequences in a query and a target database.", "hmmer/eslsfetch": "Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. T", "mmseqs/createtsv": "Create a tsv file from a query and a target database as well as the result database"}}, "target": "mmseqs/search", "target_idx": 2}
{"id": "mod_mirtrace_qc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool for quality control and tracing taxonomic origins of microRNA sequencing data (tools: mirtrace)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"narfmap/align": "Performs fastq alignment to a reference using NARFMAP", "seqcluster/collapse": "Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file.", "mirtrace/qc": "A tool for quality control and tracing taxonomic origins of microRNA sequencing data", "miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data"}}, "target": "mirtrace/qc", "target_idx": 2}
{"id": "mod_vcf_extract_relate_somalier_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform somalier extraction and relate stats on input VCFs (tools: vcf_extract_relate_somalier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt_stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs", "sylph_sketchsamples": "Sketching/indexing sequencing reads", "vsearch_sintax": "Taxonomic classification using the sintax algorithm.", "custom_collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op"}}, "target": "vcf_extract_relate_somalier", "target_idx": 1}
{"id": "resource_amulety_balmpaired_5", "category": "resource_profiling", "state": {"process": "AMULETY_BALMPAIRED", "tool": "amulety/balmpaired", "description": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_BALMPAIRED (A module to create BALM paired embeddings of antibody (BCR) amino acid sequences) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "core_tool_spades_metaspades_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? De novo assembler specifically optimized for complex microbial metagenomic mixtures, recovering contigs across unequal coverage depths.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"canu": "Long read assembler", "megahit": "Metagenomic assembler", "unicycler": "Hybrid assembler", "flye": "Long read assembler", "spades_metaspades": "metaSPAdes is a sub-tool of SPAdes designed for metagenomics assembly"}}, "target": "spades_metaspades", "target_idx": 4}
{"id": "mod_ivar_trim_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim primer sequences rom a BAM file with iVar (tools: ivar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastcov": "Generate a coverage plot from one or more bam files", "sentieon/hsmetrics": "Collects hybrid-selection (HS) metrics for a SAM or BAM file.", "bbmap/bbduk": "Adapter and quality trimming of sequencing reads", "ivar/trim": "Trim primer sequences rom a BAM file with iVar", "ivar/variants": "Call variants from a BAM file using iVar"}}, "target": "ivar/trim", "target_idx": 3}
{"id": "resource_ascat_2", "category": "resource_profiling", "state": {"process": "ASCAT", "tool": "ascat", "description": "copy number profiles of tumour cells."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASCAT (copy number profiles of tumour cells.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_hmmer_eslalimask_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mask multiple sequence alignments (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crabs/import": "In-house generated or curated data can be imported into CRABS.", "hmmer/eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi", "vcf_filter_bcftools_ensemblvep": "Filter VCF file with bcftools and filter_vep", "hmmer/eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "hmmer/eslalimask": "Mask multiple sequence alignments"}}, "target": "hmmer/eslalimask", "target_idx": 4}
{"id": "resource_bwamem2_index_2", "category": "resource_profiling", "state": {"process": "BWAMEM2_INDEX", "tool": "bwamem2/index", "description": "Create BWA-mem2 index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAMEM2_INDEX (Create BWA-mem2 index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "mod_hostile_fetch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads required reference genomes for Hostile (tools: hostile)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon_filter": "Filter DNA sequences using index of reference genome", "hostile_fetch": "Downloads required reference genomes for Hostile", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs", "gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU", "hostile_clean": "Removes host reads from short- and long-read FASTQ sequencing files"}}, "target": "hostile_fetch", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "data_format": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral genome sequencing on Oxford Nanopore MinION / GridION with entry step NANOPLOT.", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "noul_channel_collect_operator_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_4_4", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Aligned BAM files?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "field_constraint_strandedness_1_8", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"pattern: ^[0-9]+$": null, "type: boolean": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_4_0", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Raw paired-end Illumina WGS FASTQs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_41", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_controlfreec_freec2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot Freec output (tools: controlfreec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "controlfreec/freec2circos": "Format Freec output to circos input format", "controlfreec/freec2bed": "Plot Freec output", "force/cube": "Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spat", "controlfreec/assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC"}}, "target": "controlfreec/freec2bed", "target_idx": 2}
{"id": "intent_debug_error_8", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "debug_error", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pre-aligned BAM variant calling pipeline", "data_format": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "noul_channel_mix_operator_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_bam_applybqsr_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_APPLYBQSR", "modules": ["gatk4/applybqsr", "samtools/merge"], "description": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using"}, "question": {"type": "choice", "instructions": "How should BAM_APPLYBQSR (gatk4/applybqsr, samtools/merge) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_applybqsr": null, "Leave them out": null, "Local subworkflow BAM_APPLYBQSR": null}}, "target": "Use nf-core subworkflow bam_applybqsr", "target_idx": 1}
{"id": "mod_sentieon_bwaindex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA index for reference genome (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pear": "PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger.", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "sentieon/bwaindex": "Create BWA index for reference genome", "megahit": "An ultra-fast metagenomic assembler for large and complex metagenomics", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali"}}, "target": "sentieon/bwaindex", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_0_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_viralintegration_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach.. Topics: chimeric-alignment, ctat, viral-integration, virus, virusintegrationfinder. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"slamseq": null, "genomeassembler": null, "viralintegration": null, "riboseq": null, "bacass": null}}, "target": "viralintegration", "target_idx": 2}
{"id": "resource_bedops_gtf2bed_3", "category": "resource_profiling", "state": {"process": "BEDOPS_GTF2BED", "tool": "bedops/gtf2bed", "description": "Convert gtf format to bed format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_GTF2BED (Convert gtf format to bed format) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_kma_kma_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mapping raw reads directly against redundant databases via KMA alignment (tools: kma)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "fastq_align_dedup_bwameth": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate", "ariba/getref": "Download and prepare database for Ariba analysis", "kma/kma": "Mapping raw reads directly against redundant databases via KMA alignment"}}, "target": "kma/kma", "target_idx": 4}
{"id": "field_constraint_strandedness_1_1", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"pattern: ^[0-9]+$": null, "type: boolean": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "mod_merquryfk_hapmaker_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_taps_conversion": null, "meryl_histogram": null, "meryl_count": null, "bismark_align": null, "merquryfk_hapmaker": null}}, "target": "merquryfk_hapmaker", "target_idx": 4}
{"id": "samplesheet_arch_rare_disease_trio_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Trio exome/genome sequencing (Proband, Mother, Father)", "data_format": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns are standard for Trio exome/genome sequencing (Proband, Mother, Father) input samplesheet?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bedtools_sort_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SORT", "tool": "bedtools/sort", "description": "Sorts a feature file by chromosome and other criteria."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SORT (Sorts a feature file by chromosome and other criteria.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_medium", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_28", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_baysor_preview_3", "category": "resource_profiling", "state": {"process": "BAYSOR_PREVIEW", "tool": "baysor/preview", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_PREVIEW (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_spring_decompress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, efficient, lossless decompression of FASTQ files. (tools: spring)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "concoct_mergecutupclustering": "Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py", "spring_decompress": "Fast, efficient, lossless decompression of FASTQ files.", "custom_clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "ariba_run": "Query input FASTQs against Ariba formatted databases"}}, "target": "spring_decompress", "target_idx": 2}
{"id": "mod_alignoth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creating alignment plots from bam files (tools: alignoth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "snpsift_annmemcreate": "Create memory-optimized SnpSift vardb databases from VCF files for use with SnpSift annMem annotation.\nConvert", "alignoth": "Creating alignment plots from bam files", "dshbio_exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "alignoth", "target_idx": 2}
{"id": "mod_purecn_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run PureCN workflow to normalize, segment and determine purity and ploidy (tools: purecn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifitrimmer_processblast": "Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrima", "jvarkit_wgscoverageplotter": "Plot whole genome coverage from BAM/CRAM file as SVG", "purecn_run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "purecn_intervalfile": "Generate on and off-target intervals for PureCN from a list of targets", "purecn_normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as"}}, "target": "purecn_run", "target_idx": 2}
{"id": "mod_bioformats2raw_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification. (tools: bioformats2raw)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bftools/showinf": "Extract OME xml data from OME-tif", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "deepvariant/callvariants": "Call variants from the examples produced by make_examples", "taxpasta/merge": "Standardise and merge two or more taxonomic profiles into a single table", "bioformats2raw": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible "}}, "target": "bioformats2raw", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_1_24", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bcftools_pluginsplit_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSPLIT", "tool": "bcftools/pluginsplit", "description": "Split VCF by sample, creating single- or multi-sample VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSPLIT (Split VCF by sample, creating single- or multi-sample VCFs.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_art_illumina_4", "category": "resource_profiling", "state": {"process": "ART_ILLUMINA", "tool": "art/illumina", "description": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ART_ILLUMINA (Simulation tool to generate synthetic Illumina next-generation sequencing reads) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_blast_blastn_5", "category": "resource_profiling", "state": {"process": "BLAST_BLASTN", "tool": "blast/blastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_ripgrep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ripgrep recursively searches directories for a regex pattern (tools: ripgrep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment", "minia": "Minia is a short-read assembler based on a de Bruijn graph", "ampir": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ", "entrezdirect/esearch": "Searches a term in a public NCBI database", "ripgrep": "ripgrep recursively searches directories for a regex pattern"}}, "target": "ripgrep", "target_idx": 4}
{"id": "resource_bioawk_1", "category": "resource_profiling", "state": {"process": "BIOAWK", "tool": "bioawk", "description": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOAWK (Bioawk is an extension to Brian Kernighan's awk, adding the support of several c) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_sex_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "intent_prepare_data_2", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "prepare_data", "target_idx": 0}
{"id": "resource_bedgovcf_4", "category": "resource_profiling", "state": {"process": "BEDGOVCF", "tool": "bedgovcf", "description": "Convert a BED file to a VCF file according to a YAML config"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDGOVCF (Convert a BED file to a VCF file according to a YAML config) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_25", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_48", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_2", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_41", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_trim_fastp_fastqc_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TRIM_FASTP_FASTQC", "modules": ["fastqc", "fastp"], "description": "Read QC, fastp trimming and read qc"}, "question": {"type": "choice", "instructions": "How should FASTQ_TRIM_FASTP_FASTQC (fastqc, fastp) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_TRIM_FASTP_FASTQC": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_trim_fastp_fastqc": null}}, "target": "Use nf-core subworkflow fastq_trim_fastp_fastqc", "target_idx": 3}
{"id": "noul_modular_subworkflow_composition_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_gatk4_postprocessgermlinecnvcalls_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Postprocesses the output of GermlineCNVCaller and generates VCFs and denoised copy ratios (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_postprocessgermlinecnvcalls": "Postprocesses the output of GermlineCNVCaller and generates VCFs and denoised copy ratios", "cnvkit_batch": "Copy number variant detection from high-throughput sequencing data", "ampir": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ", "gcta_addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "cnaqc": "Quality control of copy number data from bulk WGS assays"}}, "target": "gatk4_postprocessgermlinecnvcalls", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_37", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_2", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_trtools_mergestr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file. (tools: trtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trtools_mergestr": "MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file.", "expansionhunter": "Estimate repeat sizes using NGS data", "samclip": "Filters SAM/BAM/CRAM files for soft and hard clipped alignments", "hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data", "pyrodigal": "Pyrodigal is a Python module that provides bindings to Prodigal, a fast, reliable protein-coding gene predicti"}}, "target": "trtools_mergestr", "target_idx": 0}
{"id": "resource_artic_aligntrim_2", "category": "resource_profiling", "state": {"process": "ARTIC_ALIGNTRIM", "tool": "artic/aligntrim", "description": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_ALIGNTRIM (Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_5_2", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin", "pipeline": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/chipseq, determine the input samplesheet column structure for: ChIP-seq with IP and input control design.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "pipe_all101_mag_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Assembly and binning of metagenomes. Topics: annotation, assembly, binning, long-read-sequencing, metagenomes, metagenomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mag": null, "imcyto": null, "cageseq": null, "ampliseq": null, "eager": null, "pairgenomealign": null, "circdna": null, "isoseq": null, "viralintegration": null, "proteinfold": null}}, "target": "mag", "target_idx": 0}
{"id": "mod_filtlong_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtlong filters long reads based on quality measures or short read data. (tools: filtlong)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"filtlong": "Filtlong filters long reads based on quality measures or short read data.", "gstama_collapse": "Collapse redundant transcript models in Iso-Seq data.", "trgt_merge": "Merge TRGT VCFs from multiple samples", "xeniumranger_relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts.", "chopper": "Filter and trim long read data."}}, "target": "filtlong", "target_idx": 0}
{"id": "intent_debug_error_6", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "debug_error", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_47", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_2_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_5_5", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "template": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/riboseq, determine the input samplesheet column structure for: Ribosome profiling (Ribo-seq) footprint sequencing.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "mod_nacho_qc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter data is a messenger-RNA/micro-RNA (mRNA/miRNA) expression assay and works with fluorescent barcodes.\nEach barcode is assigned a mRNA/miRNA, which can be counted after bonding with its target.\nAs a result each count of a specific barcode represents the presence of its target mRNA/miRNA. (tools: NACHO)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nacho/qc": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "mirtop/counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns ", "vembrane/sort": "Sort VCF/BCF files by custom Python expressions for variant prioritization", "mirdeep2/mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs.", "vcf2zarr/explode": "Convert VCF(s) to intermediate columnar format"}}, "target": "nacho/qc", "target_idx": 0}
{"id": "noul_container_environment_specification_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_busco_plot_3", "category": "resource_profiling", "state": {"process": "BUSCO_PLOT", "tool": "busco/plot", "description": "BUSCO summary plot generation using the built-in 'busco --plot' command"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PLOT (BUSCO summary plot generation using the built-in 'busco --plot' command) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_5", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_impute_glimpse_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_GLIMPSE", "modules": ["glimpse/chunk", "glimpse/phase", "glimpse/ligate", "bcftools/index"], "description": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_GLIMPSE (glimpse/chunk, glimpse/phase, glimpse/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_impute_glimpse": null, "Local subworkflow VCF_IMPUTE_GLIMPSE": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_impute_glimpse", "target_idx": 0}
{"id": "mod_medaka_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to create consensus sequences and variant calls from nanopore sequencing data (tools: medaka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": null, "medaka": null, "samplesheetparser/diff": null, "abyss/abysspe": null, "busco/plot": null}}, "target": "medaka", "target_idx": 1}
{"id": "mod_entrezdirect_esearch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Searches a term in a public NCBI database (tools: entrezdirect)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect/esummary": "Queries an NCBI database using Unique Identifier(s)", "goat/taxonsearch": "Query metadata for any taxon across the tree of life.", "minimap2/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "plastid/makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-", "entrezdirect/esearch": "Searches a term in a public NCBI database"}}, "target": "entrezdirect/esearch", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_0_18", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "pipe_all101_drugresponseeval_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for testing drug response prediction models in a statistically and biologically sound way.. Topics: cell-lines, cross-validation, deep-learning, drug-response, drug-response-prediction, drugs. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": null, "drugresponseeval": null, "nascent": null, "metaboigniter": null, "detaxizer": null, "riboseq": null, "mnaseseq": null, "slamseq": null}}, "target": "drugresponseeval", "target_idx": 1}
{"id": "mod_seq2hla_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Precision HLA typing and expression from RNA-seq data using seq2HLA (tools: seq2hla)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA", "t1k/build": "A module to create a reference database and coordinate files for T1K.", "bam_cnv_wisecondorx": "A subworkflow for calling CNVs using WisecondorX", "t1k/run": "write your description here", "rastair/mbias": "Assess C->T conversion as a readout for methylation on a per-read-position basis."}}, "target": "seq2hla", "target_idx": 0}
{"id": "noul_default_empty_channel_behavior_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_9", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_kaiju_kaiju2krona_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert Kaiju's tab-separated output file into a tab-separated text file which can be imported into Krona. (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju/kaiju2krona": "Convert Kaiju's tab-separated output file into a tab-separated text file which can be imported into Krona.", "ganon/classify": "Classify FASTQ files against ganon database", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "gatk4/modelsegments": "Converts copy number ratios (and optonally allelic counts) to copy number segments", "gridss/generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements."}}, "target": "kaiju/kaiju2krona", "target_idx": 0}
{"id": "resource_amulety_antiberty_1", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTY", "tool": "amulety/antiberty", "description": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTY (A module to create antiberty embeddings of antibody (BCR) amino acid sequences u) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedtools_multiinter_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MULTIINTER", "tool": "bedtools/multiinter", "description": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MULTIINTER (Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_haplogrep3_classify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: classification into haplogroups (tools: haplogrep3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pydamage_filter": "Damage parameter estimation for ancient DNA", "haplogrep2_classify": "classification into haplogroups", "conifer": "Calculate confidence scores from Kraken2 output", "popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "haplogrep3_classify": "classification into haplogroups"}}, "target": "haplogrep3_classify", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_1_2", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_5_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Paired-end Whole Exome Sequencing (WES) target capture.", "criteria": {"sample,bed": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_sentieon_datametrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects multiple quality metrics from a bam file (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "bamreadcount": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencin", "mmseqs_contig_taxonomy": "Assign taxonomy to contigs using the MMseqs2 workflow.", "sentieon/datametrics": "Collects multiple quality metrics from a bam file", "paragraph/vcf2paragraph": "Convert a VCF file to a JSON graph"}}, "target": "sentieon/datametrics", "target_idx": 3}
{"id": "mod_vsearch_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences using a single-pass, greedy centroid-based clustering algorithm. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_varcal": "Module for Sentieons VarCal. The VarCal algorithm calculates the Variant Quality Score Recalibration (VQSR).\nV", "vsearch_cluster": "Cluster sequences using a single-pass, greedy centroid-based clustering algorithm.", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "vsearch_sintax": "Taxonomic classification using the sintax algorithm."}}, "target": "vsearch_cluster", "target_idx": 1}
{"id": "mod_bedtools_closest_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: For each feature in A, finds the closest feature (upstream or downstream) in B. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/genomecov": null, "bedtools/closest": null, "bedtools/groupby": null, "anndata/barcodes": null, "fgbio/filterconsensusreads": null}}, "target": "bedtools/closest", "target_idx": 1}
{"id": "subworkflow_pkg_bam_variant_calling_sort_freebayes_bcftools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS", "modules": ["freebayes", "bcftools/sort"], "description": "Call variants using freebayes, then sort and index"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS (freebayes, bcftools/sort) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS": null, "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools", "target_idx": 2}
{"id": "mod_oarfish_alignmentprojectionmode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Project an existing spliced genome BAM (e.g. from minimap2 -ax splice) onto the annotated transcripts, then quantify. (tools: oarfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"oarfish_alignmentprojectionmode": null, "art_illumina": null, "angsd_soapsnpcalibration": null, "bamtofastq10x": null, "truvari_segment": null}}, "target": "oarfish_alignmentprojectionmode", "target_idx": 0}
{"id": "noul_undeclared_process_file_inputs_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "local_subworkflow_prepontreads_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should PREPONTREADS (porechop, nanoplot) be built?", "criteria": {"Local subworkflow PREPONTREADS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null, "Leave them out": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_2_4", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,primer_its1,primer_its2": null, "sample,fastq_1": null, "sample,unite_fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_suppa_clusterevents_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster events based on PSI values and significantly differentially spliced events using SUPPA2. (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa/clusterevents": "Cluster events based on PSI values and significantly differentially spliced events using SUPPA2.", "leafcutter/differentialsplicing": "Perform differential splicing analysis to identify junctions with significant changes in splicing between cond", "suppa/generateevents": "Generates alternative splicing events from a GTF file using SUPPA.", "chopper": "Filter and trim long read data.", "vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file"}}, "target": "suppa/clusterevents", "target_idx": 0}
{"id": "intent_prepare_data_8", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "prepare_data", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_29", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_fastq_align_dedup_bismark_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align BS-Seq reads to a reference genome using bismark, deduplicate and sort (tools: fastq_align_dedup_bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dragen_germline": null, "fastq_align_dedup_bismark": null, "bismark_genomepreparation": null, "numorph_resample": null, "bismark_align": null}}, "target": "fastq_align_dedup_bismark", "target_idx": 1}
{"id": "local_subworkflow_preparereports_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should this step (custom/preparereports, multiqc) be packaged: Custom aggregation and MultiQC reporting?", "criteria": {"Local subworkflow PREPAREREPORTS": null, "Use nf-core subworkflow preparereports": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_5", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_aria2_1", "category": "resource_profiling", "state": {"process": "ARIA2", "tool": "aria2", "description": "CLI Download utility"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIA2 (CLI Download utility) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_44", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "noul_module_metadata_propagation_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_pbjasmine_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify specific base modifications in PacBio HiFi reads by analyzing polymerase kinetic signatures (tools: pbjasmine)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "alignoth": "Creating alignment plots from bam files", "pbjasmine": "Identify specific base modifications in PacBio HiFi reads by analyzing polymerase kinetic signatures", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "deepmased_predict": "DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED"}}, "target": "pbjasmine", "target_idx": 2}
{"id": "mod_custom_orfmerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `custom/orfnormalise` upstream and\n(typically) `bedtools/getfasta` + `seqkit/translate` downstream to obtain\nthe AA FASTA.\n\nRows sharing an identical exon structure are grouped first and clustered as a\nsingle proxy chosen by class specificity, then the members are restored. Class\nselects the strategy, so without this an ORF that two callers class differently\nwould be split across strategies and could never merge.\n\nProxies are then partitioned by clustering strategy. The harmonised `orf_class`\nwritten by `custom/orfnormalise` selects the strategy but is never part of a\ngrouping key, because callers disagree on class for the same ORF (Ribo-TISH\nreports `5'UTR` for both uORFs and CDS-overlapping uORFs) and keying on it\nwould emit one catalogue row per disagreeing caller:\n\n  - canonical_cds:        grouped by (transcript_id, strand), then\n                          reciprocal-overlap clustered within the\n                          transcript so a short truncated variant is\n                          not folded into the full-length CDS.\n  - uORF, uoORF, dORF,    collapse by (transcript_id, strand, start,\n    doORF, intORF, other: end). A single transcript can host multiple\n                          distinct uORFs / dORFs / internal ORFs, so\n                          keying on the outer span keeps them in\n                          separate clusters while still merging\n                          cross-caller calls that agree on coordinates.\n  - novel_u:              greedy reciprocal-overlap clustering on summed\n                          exon-block intersection at `--reciprocal-overlap`\n                          (default 0.8). Catches fuzzy cross-caller\n                          matches and exact-coordinate collapses in\n                          one pass. Order-dependent at the boundary:\n                          a chain A-B-C where A-B and B-C overlap at\n                          ~0.85 but A-C only at ~0.75 may cluster as\n                          {A,B,C} or {A,B}+{C} depending on iteration\n                          order. Rare in practice at 0.8.\n\nCross-caller consensus is recorded in two column families on the\ncatalogue TSV:\n\n  - `called_by_<caller>`: 0/1 indicator per supported caller\n                          (ribotish, ribocode, ribotricer, rpbp, price).\n  - `score_<caller>`:     best score from that caller within the cluster.\n                          Score direction is per-caller (p-values are\n                          minimised; Bayes factors / phase scores are\n                          maximised).\n\nCross-sample recurrence is recorded in two further columns:\n\n  - `n_samples`:          number of distinct samples contributing to the\n                          cluster (a cohort recurrence metric).\n  - `samples`:            sorted, comma-separated list of those sample ids.\n\nEmits a small MultiQC custom-content TSV (per-class counts) for\ninclusion in downstream MultiQC reports.\n\nAlongside the full catalogue, emits a consensus view (`*.consensus.*`)\nfiltered to ORFs supported by at least `--min-callers` distinct callers\nand recurring in at least `--min-samples` samples (both default 1, i.e.\nno filtering, so the consensus view equals the full catalogue). Raising\neither threshold yields a higher-confidence catalogue without altering\nthe full one. (tools: orfmerge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_orfmerge": "Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `cus", "cnvpytor_partition": "Calculate segmentation for specified bin size (multiple bin sizes separate by space)", "ltrharvest": "Predicts LTR retrotransposons using the parallel version of GenomeTools gt-ltrharvest\nutility included in the ", "dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "gedi_indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction"}}, "target": "custom_orfmerge", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_2_5", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,kraken_db": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_archive_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip (tools: archive_extract)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"flye": "De novo assembler for single molecule sequencing reads", "tar": "Compress directories into tarballs with various compression options", "archive_extract": "Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip", "krona_ktupdatetaxonomy": "KronaTools Update Taxonomy downloads a taxonomy database", "cat_cat": "A module for concatenation of gzipped or uncompressed files"}}, "target": "archive_extract", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_0", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/pacvar) for PacBio HiFi unaligned BAM variant calling. Input files: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/pacvar, determine the input samplesheet column structure for: PacBio HiFi unaligned BAM variant calling.", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "mod_plink2_vcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Import variant genetic data using plink2 (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/extract": "Subset plink pfiles with a text file of variant identifiers", "plink2/vcf": "Import variant genetic data using plink2", "fusionreport/detect": "fusionreport_detect", "blobtk/create": "Creates a minimal blobdir.", "plink2/indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium"}}, "target": "plink2/vcf", "target_idx": 1}
{"id": "resource_agat_spmergeannotations_3", "category": "resource_profiling", "state": {"process": "AGAT_SPMERGEANNOTATIONS", "tool": "agat/spmergeannotations", "description": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated names and fixes other oddities met in those files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPMERGEANNOTATIONS (This script merge different gff annotation files in one. It uses the AGAT parser) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_mag_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for annotation. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "mag", "target_idx": 8}
{"id": "samplesheet_arch_metagenome_mag_grouped_3_2", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Metagenomic MAG assembly with comparative groups with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "mod_diamond_blastx_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a DIAMOND database using blastx mode (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_access": null, "cnaqc": null, "any2fasta": null, "amrfinderplus_update": null, "diamond_blastx": null}}, "target": "diamond_blastx", "target_idx": 4}
{"id": "mod_cnvkit_target_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transform bait intervals into targets more suitable for CNVkit. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools_flip": "Flip pairs to get an upper-triangular matrix", "varscan_processsomatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "cnvkit_export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "cnvkit_fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "cnvkit_target": "Transform bait intervals into targets more suitable for CNVkit."}}, "target": "cnvkit_target", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_2_21", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/eager --input samplesheet.csv (Assay: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_agat_spfilterfeaturefromkilllist_5", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERFEATUREFROMKILLLIST", "tool": "agat/spfilterfeaturefromkilllist", "description": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERFEATUREFROMKILLLIST (The script aims to remove features based on a kill list. The default behaviour i) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_rpbp_selectfinalpredictionset_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the standard Rp-Bp prediction\nrules: a minimum Bayes-factor cutoff (favouring translated over\nuntranslated), a minimum ORF length, and overlap resolution so that\namong overlapping candidates only the highest-scoring representative\nis kept.\n\nEmits three files describing the same prediction set: a BED of ORF\ngenomic coordinates plus score, a FASTA of ORF DNA sequences\n(extracted from the genome FASTA), and a FASTA of the corresponding\ntranslated protein sequences. This is the terminal step of the Rp-Bp\nper-sample chain. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "rpbp/selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s", "rpbp/getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "fastq_align_dedup_bismark": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort", "picard/collectrnaseqmetrics": "Collect metrics from a RNAseq BAM file"}}, "target": "rpbp/selectfinalpredictionset", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_1_3", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "noul_channel_join_operator_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "assay_type": "Ribosome profiling (Ribo-seq) footprint sequencing", "data_format": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,cdna_fasta": null, "sample,fastq_1,strandedness": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_1_3", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hi-C chromosome conformation capture mapping?", "criteria": {"sample,bam": null, "sample,bed": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_0", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_nonpareil_nonpareilcurvesr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate summary reports with raw data for Nonpareil NPO curves, including MultiQC compatible JSON/TSV files (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ldak/thinpredictors": null, "biomformat/convert": null, "binette": null, "nonpareil/nonpareilcurvesr": null, "sawfish/discover": null}}, "target": "nonpareil/nonpareilcurvesr", "target_idx": 3}
{"id": "resource_bedtools_maskfasta_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MASKFASTA", "tool": "bedtools/maskfasta", "description": "masks sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MASKFASTA (masks sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_msisensorpro_pro_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MSIsensor-pro/pro is a tool used to evaluate MSI using single (tumor) sample sequencing data (tools: msisensorpro)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro_pro": "MSIsensor-pro/pro is a tool used to evaluate MSI using single (tumor) sample sequencing data", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "msisensorpro_msisomatic": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "deacon_indexdiff": "Subtract minimizers in deacon index (or fasta file) from another index (A - B)", "msisensorpro_baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis"}}, "target": "msisensorpro_pro", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should VARIANTSOFINT (custom/variantsofint) be built?", "criteria": {"Leave them out": null, "Use nf-core subworkflow variantsofint": null, "Keep the modules in the main workflow": null, "Local subworkflow VARIANTSOFINT": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 3}
{"id": "resource_bcftools_convert_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONVERT", "tool": "bcftools/convert", "description": "Converts certain output formats to VCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONVERT (Converts certain output formats to VCF) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_2_31", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "schema_std_hlatyping_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hlatyping", "description": "Precision HLA typing from next-generation sequencing data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/hlatyping?", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "fasta,assembly,ncbi,gff,fastq": null}}, "target": "sample,fastq_1,fastq_2,bam,seq_type", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_6_4", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities", "pipeline": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi unaligned BAM variant calling input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_2_0", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_6_4", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multi-lane Illumina sequencing run of clinical samples input samplesheet?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_rgi_cardannotation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Preprocess the CARD database for RGI to predict antibiotic resistance from protein or nucleotide data (tools: rgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate_run": null, "amrfinderplus_update": null, "rgi_cardannotation": null, "xengsort_index": null, "checkm2_databasedownload": null}}, "target": "rgi_cardannotation", "target_idx": 2}
{"id": "mod_starfusion_detect_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast and Accurate Fusion Transcript Detection from RNA-Seq (tools: star-fusion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusioninspector": null, "starfusion/detect": null, "ivar/variants": null, "arriba/download": null, "clair3": null}}, "target": "starfusion/detect", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_9", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "local_subworkflow_daisribosome_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for DAISRIBOSOME (dais).", "criteria": {"Local subworkflow DAISRIBOSOME": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow daisribosome": null, "Leave them out": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 0}
{"id": "noul_confusing_combine_with_mix_semantics_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "schema_std_marsseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/marsseq. Description: MARS-seq v2 pre-processing pipeline with velocity.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/marsseq.", "criteria": {"sample,fastq_1,fastq_2,fasta,run_accession": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "patient,sample,vcf,status,cna": null, "sample,type,level,msfile": null}}, "target": "fastq_1,fastq_2,batch,amp_batches,seq_batches", "target_idx": 1}
{"id": "mod_kmcp_compute_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate k-mers (sketches) from FASTA/Q sequences (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "biobambam/bammarkduplicates2": "Locate and tag duplicate reads in a BAM file", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt", "kmcp/compute": "Generate k-mers (sketches) from FASTA/Q sequences"}}, "target": "kmcp/compute", "target_idx": 4}
{"id": "noul_confusing_combine_with_mix_semantics_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_mygene_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fetch the GO concepts for a list of genes (tools: mygene)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mygene": "Fetch the GO concepts for a list of genes", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "ferrohgvs/normalize": "Normalize HGVS variant descriptions to canonical form with ferro", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "skani/dist": "Simple ANI calculation between reference and query genomes."}}, "target": "mygene", "target_idx": 0}
{"id": "field_constraint_bam_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_2", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_fastq_align_bowtie2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bowtie2 then sort with samtools (tools: fastq_align_bowtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"raxmlng": null, "ampcombi2_parsetables": null, "ampcombi2_cluster": null, "caalm_caalm": null, "fastq_align_bowtie2": null}}, "target": "fastq_align_bowtie2", "target_idx": 4}
{"id": "mod_seqkit_replace_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use seqkit to find/replace strings within sequences and sequence headers (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_sliding": "Use seqkit to generate sliding windows of input fasta", "smoove_call": "smoove simplifies and speeds calling and genotyping SVs for short reads. It also improves specificity by remov", "qualimap_rnaseq": "Evaluate alignment data", "seqkit_split2": "Split single or paired-end fastq.gz files", "seqkit_replace": "Use seqkit to find/replace strings within sequences and sequence headers"}}, "target": "seqkit_replace", "target_idx": 4}
{"id": "pipe_all101_seqinspector_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput.. Topics: genomics, quality-control. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"reportho": null, "metapep": null, "seqinspector": null, "nanostring": null, "hic": null}}, "target": "seqinspector", "target_idx": 2}
{"id": "resource_bcftools_plugintag2tag_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINTAG2TAG", "tool": "bcftools/plugintag2tag", "description": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINTAG2TAG (Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_5_3", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnafusion, determine the input samplesheet column structure for: RNA gene fusion detection (Arriba, STAR-Fusion).", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "mod_bacphlip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A bacteriophage lifestyle prediction tool (tools: bacphlip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genomad_endtoend": null, "pbtk_pbmerge": null, "regtools_junctionsextract": null, "genomad_download": null, "bacphlip": null}}, "target": "bacphlip", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_7", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq", "data_format": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_merqury_hapmers_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A script to generate hap-mer dbs for trios (tools: merqury)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vg_index": "write your description here", "ribowaltz": "Calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data", "merqury_hapmers": "A script to generate hap-mer dbs for trios", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "merqury_hapmers", "target_idx": 2}
{"id": "mod_phenoimager2mc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Formatting PhenoImager TIFF output files into stacked and normalized OME-TIFF files per cycle, compatible as ASHLAR and MCMICRO input. (tools: phenoimager2mc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bftools/showinf": "Extract OME xml data from OME-tif", "imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "phenoimager2mc": "Formatting PhenoImager TIFF output files into stacked and normalized OME-TIFF files per cycle, compatible as A", "bcftools/roh": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}}, "target": "phenoimager2mc", "target_idx": 3}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "noul_mix_operator_async_emission_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_phenotype_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "enum: [normal, tumor]": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "field_constraint_sample_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "type: integer": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_3_1", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Multiome single-cell joint RNA and ATAC chromatin with entry step FASTQC.", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_6_0", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multiplexed Oxford Nanopore run with barcode demultiplexing input samplesheet?", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,barcode": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "schema_std_proteinannotator_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinannotator", "assay": "proteinannotator pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/proteinannotator (Generation of sequence-level annotations for amino acid sequ)?", "criteria": {"sample,fastq_1": null, "id,fasta": null, "id,fasta,query": null, "sample,fastq_1,fastq_2,group": null}}, "target": "id,fasta", "target_idx": 1}
{"id": "core_tool_gatk_haplotypecaller_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Germline SNP and Indel variant calling via local de novo haplotype assembly across active genomic regions.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"deepvariant": null, "mutect2": null, "strelka2": null, "gatk_haplotypecaller": null, "freebayes": null}}, "target": "gatk_haplotypecaller", "target_idx": 3}
{"id": "pipe_all101_bamtofastq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for bamtofastq analysis? Specific context: Converts bam or cram files to fastq format and does quality control.. Topics: bamtofastq, conversion, cramtofastq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "bamtofastq", "target_idx": 6}
{"id": "local_subworkflow_nextclade_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should this step (nextclade/run) be packaged: Viral clade typing and QC?", "criteria": {"Local subworkflow NEXTCLADE": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow nextclade": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 0}
{"id": "samplesheet_arch_smartseq_plate_based_5_5", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq.", "criteria": {"sample,well,fastq": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_hmmer_hmmsearch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: search profile(s) against a sequence database (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmsearch": "search profile(s) against a sequence database", "hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "hmmer/hmmfetch": "extract hmm from hmm database file or create index for hmm database", "minimac4/impute": "Imputation of genotypes using a reference panel", "chewbbaca/createschema": "Create a schema to determine the allelic profiles of a genome"}}, "target": "hmmer/hmmsearch", "target_idx": 0}
{"id": "resource_bandage_image_1", "category": "resource_profiling", "state": {"process": "BANDAGE_IMAGE", "tool": "bandage/image", "description": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BANDAGE_IMAGE (Render an assembly graph in GFA 1.0 format to PNG and SVG image formats) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_hmmcopy_mapcounter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a bigwig file (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pilon": "Automatically improve draft assemblies and find variation among strains, including large event detection", "canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "hmmcopy_readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows", "hmmcopy_mapcounter": "mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a big", "nonpareil_curve": "Visualise metagenome redundancy curve in PNG format from a single Nonpareil npo file"}}, "target": "hmmcopy_mapcounter", "target_idx": 3}
{"id": "field_constraint_expected_cells_1_2", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_5_2", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions", "pipeline": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/diaproteomics, determine the input samplesheet column structure for: Data-Independent Acquisition (DIA) quantitative mass spectrometry.", "criteria": {"sample,fasta": null, "sample,mzml": null, "sample,raw_file,condition": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "mod_fgumi_clip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clip overlapping reads in a BAM file with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"peka": null, "htslib_bgziptabix": null, "fgumi_clip": null, "humann3_humann": null, "clippy": null}}, "target": "fgumi_clip", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_1_20", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_createtaxdb_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Parallelised and automated construction of metagenomic classifier databases of different tools. Topics: database, database-builder, metagenomic-profiling, metagenomics, profiling, taxonomic-profiling. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnaseq": null, "imcyto": null, "chipseq": null, "reportho": null, "hic": null, "nanoseq": null, "diaproteomics": null, "kmermaid": null, "pacvar": null, "createtaxdb": null}}, "target": "createtaxdb", "target_idx": 9}
{"id": "qc_adapt_singlecell_multiqc_2_20", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "field_constraint_sex_0_4", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "field_constraint_status_1_10", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_bam_stats_mirna_mirtop_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 format. (tools: bam_stats_mirna_mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangeratac/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkref", "pycoqc": "write your description here", "mirtop/counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns ", "bam_stats_mirna_mirtop": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 ", "mirtop/gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations"}}, "target": "bam_stats_mirna_mirtop", "target_idx": 3}
{"id": "mod_entrezdirect_xtract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries an NCBI database using an UID (tools: entrezdirect)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect/xtract": null, "gappa/examinegraft": null, "entrezdirect/esearch": null, "hmmer/hmmbuild": null, "cnvkit/target": null}}, "target": "entrezdirect/xtract", "target_idx": 0}
{"id": "pipe_all101_taxprofiler_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data. Topics: classification, illumina, long-reads, metagenomics, microbiome, nanopore. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": null, "hgtseq": null, "rnasplice": null, "longraredisease": null, "hlatyping": null, "mag": null, "eager": null, "proteinfold": null}}, "target": "taxprofiler", "target_idx": 0}
{"id": "schema_std_eager_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay": "eager pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/eager (A fully reproducible and state-of-the-art ancient DNA analys)?", "criteria": {"sample,fastq_1,fastq_2,pool,hash_index": null, "sample,group,path,ref,method": null, "id,fasta,sequence": null, "sample_id,bam,vcf,library_id,lane": null}}, "target": "sample_id,bam,vcf,library_id,lane", "target_idx": 3}
{"id": "mod_motus_profile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic meta-omics profiling using universal marker genes (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep3_classify": "classification into haplogroups", "motus_profile": "Taxonomic meta-omics profiling using universal marker genes", "conifer": "Calculate confidence scores from Kraken2 output", "coptr_merge": "Merge reads that were mapped to multiple indices", "fgbio_fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI"}}, "target": "motus_profile", "target_idx": 1}
{"id": "pipe_all101_diaproteomics_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for data-independent-proteomics. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "diaproteomics", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_1", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_6_5", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns are standard for CAGE-seq 5-prime capped transcript end sequencing input samplesheet?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1": null, "sample,tss_bed": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_plink2_remove_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove samples from a plink2 dataset (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_filter": null, "plink2_pca": null, "last_train": null, "hpsuissero": null, "plink2_remove": null}}, "target": "plink2_remove", "target_idx": 4}
{"id": "mod_ldak_thinpredictors_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinned predictor list for weighted kinship workflows (tools: ldak6)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/extract": "Subset plink pfiles with a text file of variant identifiers", "somalier/relate": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "ldak/thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "bio2zarr/vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster.", "somalier/extract": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/"}}, "target": "ldak/thinpredictors", "target_idx": 2}
{"id": "mod_sratools_prefetch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download sequencing data from the NCBI Sequence Read Archive (SRA). (tools: sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_gatherbqsrreports": "Gathers scattered BQSR recalibration reports into a single file", "fgumi_dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "sratools_prefetch": "Download sequencing data from the NCBI Sequence Read Archive (SRA).", "crabs_import": "In-house generated or curated data can be imported into CRABS.", "geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA"}}, "target": "sratools_prefetch", "target_idx": 2}
{"id": "resource_bismark_genomepreparation_4", "category": "resource_profiling", "state": {"process": "BISMARK_GENOMEPREPARATION", "tool": "bismark/genomepreparation", "description": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_GENOMEPREPARATION (Converts a specified reference genome into two different bisulfite\nconverted ver) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_caalm_downloadmodels_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The downloaded directory is used as input to the\nCAALM_CAALM annotation module for CAZyme prediction. (tools: huggingface_hub)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan/easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "caalm/downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "metacache/query": "Metacache query command for taxonomic classification", "amplify/predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "controlfreec/makegraph2": "Plot Freec output"}}, "target": "caalm/downloadmodels", "target_idx": 1}
{"id": "mod_krakentools_combinekreports_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes multiple kraken-style reports and combines them into a single report file (tools: krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krakentools_kreport2krona": "Takes a Kraken report file and prints out a krona-compatible TEXT file", "ribocode_ribocode": "Call ORFs with RiboCode from Ribo-Seq data", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "krakentools_combinekreports": "Takes multiple kraken-style reports and combines them into a single report file", "genomescope2": "Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical "}}, "target": "krakentools_combinekreports", "target_idx": 3}
{"id": "samplesheet_arch_germline_lane_split_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Multi-lane Illumina sequencing run of clinical samples)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Multi-lane Illumina sequencing run of clinical samples.", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should this step (custom/variantsofint) be packaged: Variant filtering and clinical annotation aggregation?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow variantsofint": null, "Leave them out": null, "Local subworkflow VARIANTSOFINT": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 3}
{"id": "subworkflow_pkg_bam_qc_picard_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_PICARD", "modules": ["picard/collectmultiplemetrics", "picard/collectwgsmetrics", "picard/collecthsmetrics"], "description": "Produces comprehensive statistics from BAM file"}, "question": {"type": "choice", "instructions": "How should BAM_QC_PICARD (picard/collectmultiplemetrics, picard/collectwgsmetrics, picard/collecthsmetrics) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_qc_picard": null, "Local subworkflow BAM_QC_PICARD": null}}, "target": "Use nf-core subworkflow bam_qc_picard", "target_idx": 2}
{"id": "mod_gemmi_cif2json_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert macromolecular structure files from mmCIF format to JSON format using gemmi. (tools: gemmi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_idmassaccuracy": "Calculates a distribution of the mass error from given mass spectra and IDs.", "helitronscanner_draw": "HelitronScanner draw tool for Helitron transposons in genomes", "foldmason_easymsa": "Aligns protein structures using foldmason", "gemmi_cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "foldmason_createdb": "Creates a database for Foldmason."}}, "target": "gemmi_cif2json", "target_idx": 3}
{"id": "mod_bam_docounts_contamination_angsd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate contamination of the X-chromosome with ANGSD (tools: bam_docounts_contamination_angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy_register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "angsd_gl": "Calculated genotype likelihoods from BAM files.", "bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "bam_docounts_contamination_angsd": "Calculate contamination of the X-chromosome with ANGSD", "angsd_docounts": "Calculates base frequency statistics across reference positions from BAM."}}, "target": "bam_docounts_contamination_angsd", "target_idx": 3}
{"id": "mod_gatk_realignertargetcreator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a list of locations that should be considered for local realignment prior genotyping. (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/merge": null, "bamclipper": null, "platypus": null, "gatk/realignertargetcreator": null, "atlas/pmd": null}}, "target": "gatk/realignertargetcreator", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_11", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_dastool_fastatocontig2bin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format (tools: dastool)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct_concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "concoct_concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "genmap_index": "create index file for genmap", "seqtk_comp": "Computes sequence statistics from FASTQ or FASTA files", "dastool_fastatocontig2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format"}}, "target": "dastool_fastatocontig2bin", "target_idx": 4}
{"id": "mod_duphold_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast way to add depth information to those calls. This can be used as additional information for filtering variants; for example we will be skeptical of deletion calls that do not have lower than average coverage compared to regions with similar gc-content. (tools: duphold)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"elprep/filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "biobambam/bamsormadup": "Parallel sorting and duplicate marking", "gedi/price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "hisat3n/build": "Build HISAT-3N index for nucleotide conversion sequencing alignment"}}, "target": "duphold", "target_idx": 3}
{"id": "schema_std_rnastructurome_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnastructurome", "assay": "rnastructurome pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnastructurome (a bioinformatics pipeline for analysing chemical high-throug)?", "criteria": {"SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,type,level,msfile": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null}}, "target": "sample,sample_id,fastq_1,fastq_2,method", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_1", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_ultra_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment (tools: ultra)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra/pipeline": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection", "ultra/index": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment", "vsearch/sintax": "Taxonomic classification using the sintax algorithm.", "tcoffee/seqreformat": "Reformats files with t-coffee", "biscuit/index": "Indexes a reference genome for use with Biscuit"}}, "target": "ultra/index", "target_idx": 1}
{"id": "mod_nanolyse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DNA contaminant removal using NanoLyse (tools: nanolyse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_explore_search_plot_tidk": null, "barrnap": null, "abra2": null, "nanolyse": null, "calder2": null}}, "target": "nanolyse", "target_idx": 3}
{"id": "mod_fq_lint_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fq lint is a FASTQ file pair validator. (tools: fq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": null, "fq_lint": null, "kallistobustools_count": null, "ariba_getref": null, "cellbender_merge": null}}, "target": "fq_lint", "target_idx": 1}
{"id": "mod_flash_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform merging of mate paired-end sequencing reads (tools: flash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "tcoffee_extractfrompdb": "Reformats the header of PDB files with t-coffee", "flash": "Perform merging of mate paired-end sequencing reads", "numorph_intensity": "performs shading correction and intensity normalization between tile stacks"}}, "target": "flash", "target_idx": 3}
{"id": "mod_ragtag_scaffold_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. Gaps (stretches of \"N\" characters) are placed\nbetween adjacent query sequences to indicate the presence of unknown sequence.\nRagTag uses whole-genome alignments to a reference assembly to scaffold query sequences.\nRagTag does not alter input query sequence in any way and only orders and orients sequences, joining them with gaps. (tools: ragtag)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spaceranger/count": "Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data", "cdhit/cdhit": "Cluster protein sequences using sequence similarity", "ragtag/scaffold": "Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. G", "salsa2": "SALSA, A tool to scaffold long read assemblies with HiC", "longstitch": "\"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - "}}, "target": "ragtag/scaffold", "target_idx": 2}
{"id": "resource_biscuit_index_1", "category": "resource_profiling", "state": {"process": "BISCUIT_INDEX", "tool": "biscuit/index", "description": "Indexes a reference genome for use with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_INDEX (Indexes a reference genome for use with Biscuit) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gffread_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validate, filter, convert and perform various other operations on GFF files (tools: gffread)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra_align": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Map reads on genome", "gffread": "Validate, filter, convert and perform various other operations on GFF files", "fq_lint": "fq lint is a FASTQ file pair validator.", "agat_convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "agat_spaddintrons": "Add intron features to gtf/gff file without intron features."}}, "target": "gffread", "target_idx": 1}
{"id": "pipe_all101_seqsubmit_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core pipeline for data submission to ENA. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drop": null, "demultiplex": null, "createpanelrefs": null, "seqsubmit": null, "scnanoseq": null, "taxprofiler": null, "pangenome": null, "bacass": null, "cageseq": null, "chipseq": null}}, "target": "seqsubmit", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Parse Biosciences Split-seq combinatorial barcoding", "data_format": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,well,plate": null, "sample,bam": null, "sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_bam_qc_picard_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces comprehensive statistics from BAM file (tools: bam_qc_picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics.", "eautils_fastqstats": "Calculate general and per-base statistics from FASTQ files", "fastani": "Alignment-free computation of Average Nucleotide Identity (ANI)", "bam_qc_picard": "Produces comprehensive statistics from BAM file", "assemblyscan": "Assembly summary statistics in JSON format"}}, "target": "bam_qc_picard", "target_idx": 3}
{"id": "pipe_all101_phyloplace_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.. Topics: evolution, evolutionary-tree, phylogenetic-placement, phylogenetics, sequence-classification, taxonomy-assignment. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "phyloplace", "target_idx": 0}
{"id": "subworkflow_pkg_bam_variant_calling_sort_freebayes_bcftools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS", "modules": ["freebayes", "bcftools/sort"], "description": "Call variants using freebayes, then sort and index"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS (freebayes, bcftools/sort) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools": null, "Local subworkflow BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools", "target_idx": 1}
{"id": "resource_abricate_summary_0", "category": "resource_profiling", "state": {"process": "ABRICATE_SUMMARY", "tool": "abricate/summary", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_SUMMARY (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_publishdir_directive_usage_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_mira_influenza_sc2_4_1", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end surveillance FASTQs from respiratory pathogen panels?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_named_output_channel_access_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_agat_convertspgxf2gxf_1", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGXF2GXF", "tool": "agat/convertspgxf2gxf", "description": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGXF2GXF (Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_mmseqs_fasta_cluster_3", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_FASTA_CLUSTER", "modules": ["mmseqs/createdb", "mmseqs/cluster", "mmseqs/linclust", "mmseqs/createtsv"], "description": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file."}, "question": {"type": "choice", "instructions": "How should MMSEQS_FASTA_CLUSTER (mmseqs/createdb, mmseqs/cluster, mmseqs/linclust, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow MMSEQS_FASTA_CLUSTER": null, "Use nf-core subworkflow mmseqs_fasta_cluster": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow mmseqs_fasta_cluster", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_0_1", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,bam": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "core_tool_fastp_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? All-in-one FASTQ preprocessor performing automated adapter trimming, polyG tail clipping, quality filtering, and base correction.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"fastp": null, "fastqc": null, "cutadapt": null, "multiqc": null, "trimmomatic": null}}, "target": "fastp", "target_idx": 0}
{"id": "mod_sentieon_tnscope_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, using a Haplotyper algorithm. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "magus/align": "Multiple Sequence Alignment using Graph Clustering", "sentieon/tnscope": "TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, us", "sentieon/bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "sentieon/bwaindex": "Create BWA index for reference genome"}}, "target": "sentieon/tnscope", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_32", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_1_3", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,well,plate": null, "sample,subpool,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_vt_decomposeblocksub_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decomposes biallelic block substitutions into its constituent SNPs. (tools: vt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tif_registration_stainwarpy": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy", "gatk4_mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "gatk4_combinegvcfs": "Combine per-sample gVCF files produced by HaplotypeCaller into a multi-sample gVCF file", "vt_decomposeblocksub": "Decomposes biallelic block substitutions into its constituent SNPs.", "eigenstratdatabasetools_eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset."}}, "target": "vt_decomposeblocksub", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_2_4", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_2_0", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "mod_gcta_remlldms_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run REML-LDMS heritability estimation with an MGRM manifest (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_extract": null, "gcta_adjustgrm": null, "gcta_remlldms": null, "hifiadapterfilt_hifiadapterfilt": null, "gcta_bivariateremlldms": null}}, "target": "gcta_remlldms", "target_idx": 2}
{"id": "resource_amulety_esm2_4", "category": "resource_profiling", "state": {"process": "AMULETY_ESM2", "tool": "amulety/esm2", "description": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ESM2 (A module to create esm2 embeddings of antibody (BCR) amino acid sequences using ) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bcftools_norm_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_NORM", "tool": "bcftools/norm", "description": "Normalize VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_NORM (Normalize VCF file) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_bgzip_index_dict_samtools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BGZIP_INDEX_DICT_SAMTOOLS", "modules": ["htslib/bgziptabix", "samtools/dict", "samtools/faidx"], "description": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA file."}, "question": {"type": "choice", "instructions": "How should FASTA_BGZIP_INDEX_DICT_SAMTOOLS (htslib/bgziptabix, samtools/dict, samtools/faidx) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTA_BGZIP_INDEX_DICT_SAMTOOLS": null, "Use nf-core subworkflow fasta_bgzip_index_dict_samtools": null}}, "target": "Use nf-core subworkflow fasta_bgzip_index_dict_samtools", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq. Input files: FastQ reads per sample.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_48", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pre-aligned BAM variant calling pipeline)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pre-aligned BAM variant calling pipeline with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_20", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_executor_support_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_40", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_msisensorpro_baseline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msisensor-pro/pro tumor-only MSI detection. (tools: msisensorpro)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra/pipeline": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection", "controlfreec/freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "controlfreec/freec2bed": "Plot Freec output", "tcoffee/seqreformat": "Reformats files with t-coffee", "msisensorpro/baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis"}}, "target": "msisensorpro/baseline", "target_idx": 4}
{"id": "schema_std_readsimulator_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/readsimulator", "assay": "readsimulator pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/readsimulator (A pipeline to simulate sequencing reads, such as Amplicon, T)?", "criteria": {"sample,fastq_1,strandedness": null, "sample,seed": null, "sample,condition,assay,peak_file,footprinting": null, "sample,tools,file,index": null}}, "target": "sample,seed", "target_idx": 1}
{"id": "resource_ataqv_mkarv_0", "category": "resource_profiling", "state": {"process": "ATAQV_MKARV", "tool": "ataqv/mkarv", "description": "mkarv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_MKARV (mkarv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_controlfreec_freec2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot Freec output (tools: controlfreec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvpytor_importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file.", "controlfreec_freec2bed": "Plot Freec output", "samtools_depth": "Computes the depth at each position or region.", "cnvnator_convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "bowtie2_align": "Align reads to a reference genome using bowtie2"}}, "target": "controlfreec_freec2bed", "target_idx": 1}
{"id": "mod_plink_indeppairwise_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of variants in the current window with squared correlation greater than the threshold are noted and variants are greedily pruned from the window until no such pairs remain. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/indeppairwise": null, "plink/indep": null, "odgi/draw": null, "gridss/assemble": null, "plink/exclude": null}}, "target": "plink/indeppairwise", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_4_2", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end oncology RNA-seq reads for chimeric transcript discovery?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fusion_bed": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_22", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_finaletoolkit_wps_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription start sites. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit/adjustwps": "Adjusts raw Windowed Protection Score (WPS) by applying a median filter\nand Savitsky-Golay filter.", "finaletoolkit/wps": "Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID"}}, "target": "finaletoolkit/wps", "target_idx": 1}
{"id": "mod_nonpareil_curve_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualise metagenome redundancy curve in PNG format from a single Nonpareil npo file (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vizgenpostprocessing/compiletilesegmentation": "The module compiles segmentation tiles using Vizgen's post-processing tool.", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "doubletdetection": "Doublet detection in single-cell RNA-seq data", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "nonpareil/curve": "Visualise metagenome redundancy curve in PNG format from a single Nonpareil npo file"}}, "target": "nonpareil/curve", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_0_35", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_3_1", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 16S rRNA / ITS microbiome amplicon profiling with entry step FASTQC.", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_ataqv_ataqv_4", "category": "resource_profiling", "state": {"process": "ATAQV_ATAQV", "tool": "ataqv/ataqv", "description": "ataqv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_ATAQV (ataqv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_gem3_gem3indexer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a GEM index from a FASTA file (tools: gem3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "crabz/compress": "Compress files with crabz", "bam_cnv_wisecondorx": "A subworkflow for calling CNVs using WisecondorX", "gem3/gem3indexer": "Create a GEM index from a FASTA file", "ariba/run": "Query input FASTQs against Ariba formatted databases"}}, "target": "gem3/gem3indexer", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_8_3", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "template": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,antibody,control": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "mod_fibertoolsrs_predictm6a_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict m6A positions using HiFi kinetics data and encode the results in the MM and ML bam tags. Also adds nucleosome (nl, ns) and MTase sensitive patches (al, as) (tools: fibertoolsrs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkv_downloaddatabase": "Construct the database necessary for checkv's quality assessment", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "fibertoolsrs_predictm6a": "Predict m6A positions using HiFi kinetics data and encode the results in the MM and ML bam tags. Also adds nuc", "oatk": "An nf-core module for the OATK", "bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts."}}, "target": "fibertoolsrs_predictm6a", "target_idx": 2}
{"id": "mod_purgedups_histplot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots the read coverage from a purge dups statistics file and cutoffs. (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purgedups/pbcstat": null, "mashtree": null, "cooler/merge": null, "cnvpytor/importreaddepth": null, "purgedups/histplot": null}}, "target": "purgedups/histplot", "target_idx": 4}
{"id": "samplesheet_arch_singlecell_parse_splitseq_0_2", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,bam": null, "sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_vcflib_vcfuniq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: List unique genotypes. Like GNU uniq, but for VCF records. Remove records which have the same position, ref, and alt as the previous record. (tools: vcflib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcflib/vcfuniq": "List unique genotypes. Like GNU uniq, but for VCF records. Remove records which have the same position, ref, a", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "vcflib/vcffilter": "Command line tools for parsing and manipulating VCF files.", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "ultra/index": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment"}}, "target": "vcflib/vcfuniq", "target_idx": 0}
{"id": "mod_emmtyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: EMM typing of Streptococcus pyogenes assemblies (tools: emmtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nonpareil/curve": null, "emmtyper": null, "amrfinderplus/run": null, "any2fasta": null, "refsolver/compare": null}}, "target": "emmtyper", "target_idx": 1}
{"id": "resource_anarcii_4", "category": "resource_profiling", "state": {"process": "ANARCII", "tool": "anarcii", "description": "A language model for antigen receptor numbering"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANARCII (A language model for antigen receptor numbering) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gt_gff3_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem2_gemmappability": "Define the mappability of a reference", "gatk4_variantstotable": "Extract fields from a VCF file to a tab-delimited table", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "gt_gff3": "GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file"}}, "target": "gt_gff3", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_ngscheckmate_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_NGSCHECKMATE", "modules": ["ngscheckmate/fastq", "ngscheckmate/vafncm"], "description": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs."}, "question": {"type": "choice", "instructions": "How should FASTQ_NGSCHECKMATE (ngscheckmate/fastq, ngscheckmate/vafncm) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_ngscheckmate": null, "Leave them out": null, "Local subworkflow FASTQ_NGSCHECKMATE": null}}, "target": "Use nf-core subworkflow fastq_ngscheckmate", "target_idx": 1}
{"id": "field_constraint_expected_cells_0_10", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_3", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "schema_std_variantbenchmarking_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/variantbenchmarking", "assay": "variantbenchmarking pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/variantbenchmarking (Pipeline to evaluate and validate the accuracy of variant ca)?", "criteria": {"sample,group,path,ref,method": null, "sample,alleles,mhc_class,filename": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "id,test_vcf,test_regions,caller,subsample", "target_idx": 3}
{"id": "local_subworkflow_preparereports_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPAREREPORTS (custom/preparereports, multiqc).", "criteria": {"Local subworkflow PREPAREREPORTS": null, "Leave them out": null, "Use nf-core subworkflow preparereports": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_16", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "field_constraint_sex_1_2", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"pattern: ^\\S+\\.gz$": null, "format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "mod_wipertools_fastqgather_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that merges FASTQ chunks produced by wipertools_fastqscatter (tools: fastqgather)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequencetools_pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "wipertools_fastqgather": "A tool of the wipertools suite that merges FASTQ chunks produced by wipertools_fastqscatter", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}}, "target": "wipertools_fastqgather", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_2_4", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_0_0", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status", "pipeline": "nf-core/eager"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_4_0", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads from tumor biopsy without matched normal?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bedtools_flank_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_FLANK", "tool": "bedtools/flank", "description": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_FLANK (Creates two new flanking intervals for each interval in a BED/GFF/VCF file.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_scnanoseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics. Topics: 10xgenomics, long-read-sequencing, nanopore, rna-seq, rnaseq, scrna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants"}}, "target": "scnanoseq", "target_idx": 1}
{"id": "field_constraint_bam_0_1", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "noul_channel_join_operator_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Standard Paired-end Whole Genome Sequencing (WGS)", "data_format": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_45", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "pipe_all101_multiplesequencealign_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]"}}, "target": "multiplesequencealign", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_bam_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic tumor-normal calling from pre-aligned BAM files", "data_format": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic tumor-normal calling from pre-aligned BAM files input samplesheet?", "criteria": {"sample,vcf": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_0_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "template": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "field_constraint_bai_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "mod_fgumi_fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a BAM file to interleaved FASTQ format with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_splitmerge": null, "bamaligncleaner": null, "ensemblvep_filtervep": null, "fgumi_fastq": null, "octopusv_svcf2bed": null}}, "target": "fgumi_fastq", "target_idx": 3}
{"id": "mod_fasta_index_methylseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate index files from reference fasta for bismark, bwameth and bwamem aligners (tools: fasta_index_methylseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "fasta_index_methylseq": "Generate index files from reference fasta for bismark, bwameth and bwamem aligners", "htseq/count": "count how many reads map to each feature", "bismark/methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali"}}, "target": "fasta_index_methylseq", "target_idx": 1}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_ctatsplicing_prepgenomelib_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reference preparation for CTAT-splicing (tools: ctatsplicing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusioninspector": "Validation of Fusion Transcript Predictions", "survivor_bedpetovcf": "Converts a bedpe file to a VCF file (beta version)", "regtools_junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.", "ctatsplicing_prepgenomelib": "Reference preparation for CTAT-splicing", "rmats_prep": "MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data."}}, "target": "ctatsplicing_prepgenomelib", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_0_20", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_10", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_cnvpytor_histogram_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculates read depth histograms (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dragonflye": null, "cnvpytor/partition": null, "sawfish/discover": null, "cnvpytor/histogram": null, "cellrangerarc/mkfastq": null}}, "target": "cnvpytor/histogram", "target_idx": 3}
{"id": "resource_assemblyscan_1", "category": "resource_profiling", "state": {"process": "ASSEMBLYSCAN", "tool": "assemblyscan", "description": "Assembly summary statistics in JSON format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASSEMBLYSCAN (Assembly summary statistics in JSON format) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_bam_impute_stitch_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_STITCH", "modules": ["stitch", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using STITCH software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_STITCH (stitch, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_impute_stitch": null, "Leave them out": null, "Local subworkflow BAM_IMPUTE_STITCH": null}}, "target": "Use nf-core subworkflow bam_impute_stitch", "target_idx": 1}
{"id": "pipe_all101_raredisease_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Call and score variants from WGS/WES of rare disease patients.. Topics: diagnostics, rare-disease, snv, structural-variants, variant-annotation, variant-calling. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c"}}, "target": "raredisease", "target_idx": 1}
{"id": "mod_plink_missing_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute sample-based and variant-based missing genotype rates and write a new PLINK binary fileset (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcflib_vcfbreakmulti": "If multiple alleles are specified in a single record, break the record into several lines preserving allele-sp", "sequali": "Sequence quality metrics for FASTQ and uBAM files.", "plink_missing": "Compute sample-based and variant-based missing genotype rates and write a new PLINK binary fileset", "plink_exclude": "Exclude variant identifiers from plink bfiles", "plink_genome": "Calculates identity-by-descent over autosomal SNPs"}}, "target": "plink_missing", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_3_2", "category": "samplesheet_schema", "state": {"technology": "Small RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Small RNA / miRNA sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,mirna_id": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "subworkflow_pkg_bam_create_som_pon_gatk_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CREATE_SOM_PON_GATK", "modules": ["gatk4/mutect2", "gatk4/genomicsdbimport", "gatk4/createsomaticpanelofnormals", "gatk4/mergevcfs", "gatk4/mergemutectstats"], "description": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a genomicsdbworkspace using genomicsdbimport, then use this to create a panel of normals using createsomaticpanelofnormals."}, "question": {"type": "choice", "instructions": "How should BAM_CREATE_SOM_PON_GATK (gatk4/mutect2, gatk4/genomicsdbimport, gatk4/createsomaticpanelofnormals, gatk4/mergevcfs, gatk4/mergemutectstats) be structured in DSL2?", "criteria": {"Local subworkflow BAM_CREATE_SOM_PON_GATK": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_create_som_pon_gatk": null}}, "target": "Use nf-core subworkflow bam_create_som_pon_gatk", "target_idx": 3}
{"id": "schema_std_mhcquant_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/mhcquant. Description: Identify and quantify MHC eluted peptides from mass spectrometry raw data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/mhcquant.", "criteria": {"sample,alleles,mhc_class,filename": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample_id,bam,vcf,library_id,lane": null, "sample,vcf,tbi": null}}, "target": "ID,Sample,Condition,ReplicateFileName,Fasta", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/smrnaseq --input samplesheet.csv (Assay: Small RNA / miRNA sequencing)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Small RNA / miRNA sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "field_constraint_phenotype_0_14", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "format: file-path": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_47", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_rpbp_extractorfprofiles_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each ORF, walks the spliced exons\nin 3-nucleotide codon steps and counts the P-site positions\n(read 5'-end coordinate plus the length-specific offset selected\nupstream) that fall in each codon. Counts are summed across all read\nlengths that passed the periodicity filter from\n`rpbp/getperiodiclengthsoffsets`.\n\nThe resulting per-ORF vectors are the input to Bayesian translation\nscoring in `rpbp/estimateorfbayesfactors`: a translated ORF should\nshow P-site density concentrated at codon-start positions, while a\nnon-translated region should look flat or noisy. Emitted as a sparse\nmatrix (one row per ORF, columns indexed by codon position). (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylph_profile": "Sylph profile command for taxonoming profiling", "rpbp_selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s", "rpbp_extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "ngscheckmate_fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "rpbp_estimateorfbayesfactors": "Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian "}}, "target": "rpbp_extractorfprofiles", "target_idx": 2}
{"id": "resource_bamclipper_5", "category": "resource_profiling", "state": {"process": "BAMCLIPPER", "tool": "bamclipper", "description": "This module is used to clip primer sequences from your alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCLIPPER (This module is used to clip primer sequences from your alignments.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_core10_chipseq_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Histone modification and TF ChIP-seq peak calling with MACS2, HOMER motif enrichment, and differential binding analysis.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "chipseq", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_2", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_2_28", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_oarfish_readprojectionmode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Spliced-align raw reads to the genome, project each read's genomic alignments onto the annotated transcripts via bramble, then quantify. (tools: oarfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "rhocall_viz": "Call regions of homozygosity and make tentative UPD calls", "oarfish_readprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Splic"}}, "target": "oarfish_readprojectionmode", "target_idx": 4}
{"id": "field_constraint_strandedness_1_7", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"format: file-path": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_quantmsutils_diann2mztab_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils (tools: quantms-utils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ensemblvep/filtervep": "Filter variants based on Ensembl Variant Effect Predictor (VEP) annotations.", "parsesdrf/convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration ", "quantmsutils/diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils", "mageck/count": "mageck count for functional genomics, reads are usually mapped to a specific sgRNA", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool"}}, "target": "quantmsutils/diann2mztab", "target_idx": 2}
{"id": "mod_plink_indep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"khmer/uniquekmers": "In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more", "plink/bcf": "Analyses binary variant call format (BCF) files using plink", "fastq_taxonomic_profile_metaphlan": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn", "plink/extract": "Subset plink bfiles with a text file of variant identifiers", "plink/indep": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other."}}, "target": "plink/indep", "target_idx": 4}
{"id": "pipe_all101_createtaxdb_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Parallelised and automated construction of metagenomic classifier databases of different tools. Topics: database, database-builder, metagenomic-profiling, metagenomics, profiling, taxonomic-profiling. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, "}}, "target": "createtaxdb", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_2_0", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_vcf_annotate_snpeff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform annotation with snpEff and bgzip + tabix index the resulting VCF file (tools: vcf_annotate_snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_markduplicates_picard": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file", "last/mafswap": "Reorder alignments in a MAF file", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "vcf_annotate_snpeff", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_45", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "field_constraint_phenotype_1_2", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "local_subworkflow_nextclade_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should NEXTCLADE (nextclade/run) be built?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow NEXTCLADE": null, "Use nf-core subworkflow nextclade": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 2}
{"id": "mod_proseg_proseg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics. (tools: proseg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell", "blast/updateblastdb": "Downloads a BLAST database from NCBI", "proseg/proseg": "Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics.", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "metacache/build": "Taxonomic profiling database building with MetaCache"}}, "target": "proseg/proseg", "target_idx": 2}
{"id": "mod_circularmapper_circulargenerator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A method to improve mappings on circular genomes, using the BWA mapper. (tools: circulargenerator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_sampe": "Convert paired-end bwa SA coordinate files to SAM format", "rattle_cluster": "Reference-free reconstruction and quantification of transcriptomes from long-read sequencing", "deeparg_predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "circularmapper_circulargenerator": "A method to improve mappings on circular genomes, using the BWA mapper.", "bwa_samse": "Convert bwa SA coordinate file to SAM format"}}, "target": "circularmapper_circulargenerator", "target_idx": 3}
{"id": "mod_mmseqs_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences using MMSeqs2 cluster. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_sampe": "Convert paired-end bwa SA coordinate files to SAM format", "mmseqs_easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "mmseqs_cluster": "Cluster sequences using MMSeqs2 cluster.", "freyja_variants": "call variant and sequencing depth information of the variant", "mmseqs_easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2"}}, "target": "mmseqs_cluster", "target_idx": 2}
{"id": "mod_bedops_convert2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert BAM/GFF/GTF/GVF/PSL files to bed (tools: bedops)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/tabulartogseachip": "Make a GSEA class file (.chip) from tabular inputs", "bio2zarr/vcf2zarrexplode": "Convert VCF(s) to intermediate columnar format (ICF)", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "minimac4/impute": "Imputation of genotypes using a reference panel", "xz/compress": "Compresses files with xz."}}, "target": "bedops/convert2bed", "target_idx": 2}
{"id": "samplesheet_arch_scrna_multiome_2_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,rna_fastq,atac_fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_0_12", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic cancer variant calling with tumor-normal pairs. Input files: Paired-end FASTQs for patient tumor and germline normal tissue.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic cancer variant calling with tumor-normal pairs with entry step BWA_MEM.", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bedtools_sort_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SORT", "tool": "bedtools/sort", "description": "Sorts a feature file by chromosome and other criteria."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SORT (Sorts a feature file by chromosome and other criteria.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_medium", "target_idx": 2}
{"id": "mod_snpsift_dbnsfp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The dbNSFP is an integrated database of functional predictions from multiple algorithms (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/consensus": "Compresses VCF files", "snpsift/dbnsfp": "The dbNSFP is an integrated database of functional predictions from multiple algorithms", "samtools/dict": "Create a sequence dictionary file from a FASTA file", "raven": "De novo genome assembler for long uncorrected reads.", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "snpsift/dbnsfp", "target_idx": 1}
{"id": "mod_telomerehunter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In silico estimation of telomere content and composition from cancer genomes (tools: telomerehunter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/pmd": null, "ascat": null, "telomerehunter": null, "trtools/mergestr": null, "deepmased/predict": null}}, "target": "telomerehunter", "target_idx": 2}
{"id": "mod_rtgtools_rocplot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI isn't possible for nextflow. (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"variantbam": null, "rtgtools_rocplot": null, "fastavalidator": null, "gffread": null, "sambamba_flagstat": null}}, "target": "rtgtools_rocplot", "target_idx": 1}
{"id": "resource_arriba_download_4", "category": "resource_profiling", "state": {"process": "ARRIBA_DOWNLOAD", "tool": "arriba/download", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_DOWNLOAD (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_immunedeconv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform immune cell deconvolution using RNA-seq data and various computational methods. (tools: immunedeconv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sortmerna": "Local sequence alignment tool for filtering, mapping and clustering.", "arriba/arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "ngsbits/updhunter": "UPD detection from trio variant data.", "deseq2/differential": "runs a differential expression analysis with DESeq2", "immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods."}}, "target": "immunedeconv", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_1_5", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bcftools_isec_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ISEC", "tool": "bcftools/isec", "description": "Apply set operations to VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ISEC (Apply set operations to VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_metaphlan_mergemetaphlantables_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges output abundance tables from MetaPhlAn4 (tools: metaphlan4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "slamdunk_all": "Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "metaphlan_mergemetaphlantables": "Merges output abundance tables from MetaPhlAn4", "vg_index": "write your description here"}}, "target": "metaphlan_mergemetaphlantables", "target_idx": 3}
{"id": "noul_workflow_completion_lifecycle_hook_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fastq_taxonomic_profile_metaphlan_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn (tools: fastq_taxonomic_profile_metaphlan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "sawfish/jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "fastq_taxonomic_profile_metaphlan": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn", "bedtools/maskfasta": "masks sequences in a FASTA file based on intervals defined in a feature file."}}, "target": "fastq_taxonomic_profile_metaphlan", "target_idx": 3}
{"id": "mod_bwameme_mem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA-MEME (tools: bwameme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA", "genmap_map": "create mappability files for a genome", "cnvpytor_partition": "Calculate segmentation for specified bin size (multiple bin sizes separate by space)", "bwameme_mem": "Performs fastq alignment to a fasta reference using BWA-MEME", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "bwameme_mem", "target_idx": 3}
{"id": "pipe_core10_rnaseq_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Total RNA-seq with ribosomal RNA depletion for bacterial gene expression profiling and transcriptome quantification.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": null, "chipseq": null, "atacseq": null, "viralrecon": null, "sarek": null, "ampliseq": null, "eager": null, "scrnaseq": null, "rnaseq": null, "mag": null}}, "target": "rnaseq", "target_idx": 8}
{"id": "samplesheet_arch_cancer_somatic_tn_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic cancer variant calling with tumor-normal pairs. Input files: Paired-end FASTQs for patient tumor and germline normal tissue.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic cancer variant calling with tumor-normal pairs.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_1_42", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bcftools_rohviz_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROHVIZ", "tool": "bcftools/rohviz", "description": "Visualise the output of bcftools roh"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROHVIZ (Visualise the output of bcftools roh) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_11", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "schema_std_methylarray_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylarray", "assay": "methylarray pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/methylarray (Process methylation data from Illumina arrays. Pre-processin)?", "criteria": {"sample,fastq_1,strandedness": null, "patient,sample,vcf,status,cna": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample_id,idat_red,idat_green,group": null}}, "target": "sample_id,idat_red,idat_green,group", "target_idx": 3}
{"id": "mod_seqkit_sample_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sample sequences from FASTA/FASTQ files by number or proportion (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "deepvariant/postprocessvariants": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "sentieon/tnfilter": "Filters the raw output of sentieon/tnhaplotyper2.", "seqkit/sample": "Sample sequences from FASTA/FASTQ files by number or proportion", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "seqkit/sample", "target_idx": 3}
{"id": "core_tool_quast_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Evaluate, compare, and compute quality metrics (N50, L50, misassemblies, completeness) for draft genome assemblies against reference genomes.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"mummer": "Alignment tool", "busco": "Benchmark universal single-copy orthologs", "checkm": "Metagenome quality", "quast": "Quality Assessment Tool for Genome Assemblies evaluating contigs metrics (N50, misassemblies)", "multiqc": "MultiQC report"}}, "target": "quast", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_24", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "intent_debug_error_21", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "ask_question": null, "prepare_data": null}}, "target": "debug_error", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_trimgalore_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_TRIMGALORE", "modules": ["fastqc", "umitools/extract", "trimgalore"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_TRIMGALORE (fastqc, umitools/extract, trimgalore) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_fastqc_umitools_trimgalore": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_FASTQC_UMITOOLS_TRIMGALORE": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_trimgalore", "target_idx": 0}
{"id": "mod_bbmap_filterbyname_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter out sequences by sequence header name(s) (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": null, "bbmap_filterbyname": null, "bamtofastq10x": null, "hypo": null, "centrifuger_centrifuger": null}}, "target": "bbmap_filterbyname", "target_idx": 1}
{"id": "resource_bwa_mem_1", "category": "resource_profiling", "state": {"process": "BWA_MEM", "tool": "bwa/mem", "description": "Performs fastq alignment to a fasta reference using BWA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_MEM (Performs fastq alignment to a fasta reference using BWA) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "noul_exit_code_137_cause_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_17", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "assay_type": "Ribosome profiling (Ribo-seq) footprint sequencing", "data_format": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end ribosome protected RNA fragments (RPFs) with strandedness?", "criteria": {"sample,bam": null, "sample,cdna_fasta": null, "sample,vcf": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_telescope_assign_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The telescope assign program finds overlapping reads between an alignment (SAM/BAM) and an annotation (GTF) then reassigns reads using a statistical model. (tools: telescope)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cpc2": "Coding Potential Calculator 2", "gappa_examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "vcf_impute_beagle5": "Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow\ntakes VCF files, phased reference pane", "proseg_proseg": "Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics.", "telescope_assign": "The telescope assign program finds overlapping reads between an alignment (SAM/BAM) and an annotation (GTF) th"}}, "target": "telescope_assign", "target_idx": 4}
{"id": "mod_rtgtools_format_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts the contents of sequence data files (FASTA/FASTQ/SAM/BAM) into the RTG Sequence Data File (SDF) format. (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"molkartgarage_clahe": "Contrast-limited adjusted histogram equalization (CLAHE) on single-channel tif images.", "rastair_methylkit": "Parses rastair call output and converts it into a MethylKit-compatible format.", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "rtgtools_format": "Converts the contents of sequence data files (FASTA/FASTQ/SAM/BAM) into the RTG Sequence Data File (SDF) forma"}}, "target": "rtgtools_format", "target_idx": 4}
{"id": "mod_sourmash_compare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare many FracMinHash signatures generated by sourmash sketch. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "gffcompare": "Compare, merge, annotate and estimate accuracy of generated gtf files", "instrain/compare": "Strain-level comparisons across multiple inStrain profiles", "picrust2/pipeline": "Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data", "snpeff/download": "Genetic variant annotation and functional effect prediction toolbox"}}, "target": "sourmash/compare", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_3_2", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "NANOPLOT", "library_inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral genome sequencing on Oxford Nanopore MinION / GridION with entry step NANOPLOT.", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_2_25", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_2_5", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_bakta_baktadbdownload_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads BAKTA database from Zenodo (tools: bakta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/ftxpy": "Somatic VCF Feature Extraction tool from hap.y.", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo", "summarizedexperiment/summarizedexperiment": "SummarizedExperiment container", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "bakta/baktadbdownload", "target_idx": 1}
{"id": "mod_biobambam_bammerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge a list of sorted bam files (tools: biobambam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct_mergecutupclustering": "Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py", "bcftools_merge": "Merge VCF files", "meryl_count": "A genomic k-mer counter (and sequence utility) with nice features.", "biobambam_bammerge": "Merge a list of sorted bam files", "parabricks_mutectcaller": "NVIDIA Clara Parabricks GPU-accelerated somatic variant calling, replicating GATK Mutect2."}}, "target": "biobambam_bammerge", "target_idx": 3}
{"id": "mod_ltrretriever_ltrretriever_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identifies LTR retrotransposons using LTR_retriever (tools: LTR_retriever)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm2_databasedownload": "CheckM2 database download", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "fusioncatcher_fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "ltrretriever_ltrretriever": "Identifies LTR retrotransposons using LTR_retriever"}}, "target": "ltrretriever_ltrretriever", "target_idx": 4}
{"id": "samplesheet_arch_ampliseq_its_fungal_0_0", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,primer_its1,primer_its2": null, "sample,unite_fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_pairix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates (tools: pairix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairix": "a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates", "sambamba/depth": "Outputs a coverage file from bam files", "bismark/coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bowtie/build": "Create bowtie index for reference genome"}}, "target": "pairix", "target_idx": 0}
{"id": "resource_braker3_5", "category": "resource_profiling", "state": {"process": "BRAKER3", "tool": "braker3", "description": "Gene prediction in novel genomes using RNA-seq and protein homology information"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRAKER3 (Gene prediction in novel genomes using RNA-seq and protein homology information) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_3_1", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "template": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hybrid bacterial assembly combining short Illumina and long Nanopore reads with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_vcfanno_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: quickly annotate your VCF with any number of INFO fields from any number of VCFs or BED files (tools: vcfanno)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "atlas_call": "generate VCF file from a BAM file using various calling methods", "bedtools_shuffle": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a gen", "vcfanno": "quickly annotate your VCF with any number of INFO fields from any number of VCFs or BED files", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "vcfanno", "target_idx": 3}
{"id": "samplesheet_arch_germline_lane_split_0_2", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"sample,bam": null, "lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_stecfinder_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotype STEC samples from paired-end reads or assemblies (tools: stecfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hicap": "Identify cap locus serotype and structure in your Haemophilus influenzae assemblies", "poolsnp": "PoolSNP is a heuristic SNP caller, which uses an MPILEUP file and a reference genome in FASTA format as inputs", "ectyper": "In silico prediction of E. coli serotype", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "stecfinder": "Serotype STEC samples from paired-end reads or assemblies"}}, "target": "stecfinder", "target_idx": 4}
{"id": "mod_msisensor_scan_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Scan a reference genome to get microsatellite & homopolymer information (tools: msisensor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensor_scan": "Scan a reference genome to get microsatellite & homopolymer information", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA", "gatk4_calculatecontamination": "Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummari", "msisensor_msi": "Evaluate microsattelite instability (MSI) using paired tumor-normal sequencing data", "msisensor2_msi": "msisensor2 detection of MSI regions."}}, "target": "msisensor_scan", "target_idx": 0}
{"id": "schema_std_sopa_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sopa", "description": "Nextflow version of Sopa - spatial omics pipeline and analysis", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/sopa?", "criteria": {"sample,fastq_1,fastq_2,genome": null, "sample,id,data_path,fastq_dir,cytaimage": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "sample,id,data_path,fastq_dir,cytaimage", "target_idx": 1}
{"id": "mod_resfinder_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteria (tools: resfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm/lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "kma/index": "This module wraps the index module of the KMA alignment tool.", "mat2json": "converst matlab .mat files into json or csv files.", "yara/mapper": "Align reads to a reference genome using YARA", "resfinder/run": "ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteri"}}, "target": "resfinder/run", "target_idx": 4}
{"id": "mod_datavzrd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables. (tools: datavzrd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"drep_compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "cellrangerarc_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma", "datavzrd": "Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables.", "fgumi_simplex": "Calls simplex consensus sequences from reads with the same unique molecular tag.\nThis is a high-performance re", "bcftools_rohviz": "Visualise the output of bcftools roh"}}, "target": "datavzrd", "target_idx": 2}
{"id": "intent_build_pipeline_15", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "ask_question": null, "prepare_data": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_3_2", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) with entry step FASTQC.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_ribowaltz_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data (tools: ribowaltz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anota2seq/anota2seqrun": null, "deeparg/downloaddata": null, "gedi/price": null, "crispresso2": null, "ribowaltz": null}}, "target": "ribowaltz", "target_idx": 4}
{"id": "mod_shapeit5_phasecommon_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to phase common sites, typically SNP array data, or the first step of WES/WGS data. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse2/phase": "Tool for imputation and phasing from vcf file or directly from bam files.", "pygenprop/build": "Generate a Micromeda file containing pathway annotations for one or more genomes.\nSupporting InterProScan and ", "hmmer/eslsfetch": "Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. T", "beagle5/beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "shapeit5/phasecommon": "Tool to phase common sites, typically SNP array data, or the first step of WES/WGS data."}}, "target": "shapeit5/phasecommon", "target_idx": 4}
{"id": "samplesheet_arch_methylseq_bisulfite_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/methylseq --input samplesheet.csv (Assay: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq))", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,cpg,methylation": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_sex_0_10", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "samplesheet_arch_spatial_visium_3_2", "category": "samplesheet_schema", "state": {"technology": "Spatial Transcriptomics", "workflow_entry": "FASTQC", "library_inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Visium spatial transcriptomics with histology image with entry step FASTQC.", "criteria": {"sample,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_1_2", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering", "pipeline": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,fastq_1,fastq_2,environment": null, "sample,rrna_fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 0}
{"id": "local_subworkflow_daisribosome_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should DAISRIBOSOME (dais) be built?", "criteria": {"Local subworkflow DAISRIBOSOME": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow daisribosome": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 0}
{"id": "mod_regenie_runl1_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Finish REGENIE step 1 from split level-0 prediction files (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie/runl1": null, "regenie/step1": null, "optitype": null, "hmmer/hmmfetch": null, "gcta/fastgwa": null}}, "target": "regenie/runl1", "target_idx": 0}
{"id": "noul_modular_subworkflow_composition_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_svtyper_svtyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SVTyper performs breakpoint genotyping of structural variants (SVs) using whole genome sequencing data (tools: svtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eigenstratdatabasetools_eigenstratsnpcoverage": null, "annotsv_installannotations": null, "svtyper_svtyper": null, "telescope_assign": null, "caddsv_get": null}}, "target": "svtyper_svtyper", "target_idx": 2}
{"id": "mod_vcflib_vcffilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Command line tools for parsing and manipulating VCF files. (tools: vcflib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani_sketch": null, "agat_spkeeplongestisoform": null, "vcflib_vcffilter": null, "celesta": null, "bamcmp": null}}, "target": "vcflib_vcffilter", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_2_43", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bcftools_index_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_INDEX", "tool": "bcftools/index", "description": "Index VCF tools"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_INDEX (Index VCF tools) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_provenancereport_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/provenancereport", "assay": "provenancereport pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/provenancereport (A simple provenance reporting pipeline)?", "criteria": {"sample,fastq_1,fastq_2,replicate,antibody": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,alleles,mhc_class,filename": null, "id,path": null}}, "target": "id,path", "target_idx": 3}
{"id": "field_constraint_fastq_2_1_7", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "core_tool_salmon_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Transcript-level abundance estimation and pseudo-alignment directly from raw paired-end RNA-seq FASTQ reads without full genome mapping.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"featurecounts": null, "kallisto": null, "salmon": null, "rsem": null, "samtools": null}}, "target": "salmon", "target_idx": 2}
{"id": "mod_lofreq_viterbi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are available (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "lofreq_viterbi": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl", "subread_featurecounts": "Count reads that map to genomic features", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "lofreq_viterbi", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_5_2", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control", "pipeline": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cutandrun, determine the input samplesheet column structure for: CUT&RUN / CUT&TAG chromatin profiling with IgG control.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "mod_gatk4_mergebamalignment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge unmapped with mapped BAM files (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"roary": "Calculate pan-genome from annotated bacterial assemblies in GFF3 format", "alignoth": "Creating alignment plots from bam files", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "gatk4/mergebamalignment": "Merge unmapped with mapped BAM files"}}, "target": "gatk4/mergebamalignment", "target_idx": 4}
{"id": "mod_bcftools_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Add or remove annotations. (tools: annotate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/call": null, "bcftools/annotate": null, "bcftools/convert": null, "shinyngs/app": null, "pridepy/downloadfile": null}}, "target": "bcftools/annotate", "target_idx": 1}
{"id": "mod_mitohifi_mitohifi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A python workflow that assembles mitogenomes from Pacbio HiFi reads (tools: mitohifi.py)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "hifiadapterfilt_hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "bwameme_index": "Create BWA-MEME index for reference genome", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "mitohifi_mitohifi": "A python workflow that assembles mitogenomes from Pacbio HiFi reads"}}, "target": "mitohifi_mitohifi", "target_idx": 4}
{"id": "subworkflow_pkg_homer_groseq_2", "category": "subworkflow_packaging", "state": {"subworkflow": "HOMER_GROSEQ", "modules": ["unzip", "homer/maketagdirectory", "homer/makeucscfile", "homer/findpeaks", "homer/pos2bed"], "description": "Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.ucsd.edu/homer/ngs/groseq/groseq.html)."}, "question": {"type": "choice", "instructions": "How should HOMER_GROSEQ (unzip, homer/maketagdirectory, homer/makeucscfile, homer/findpeaks, homer/pos2bed) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow HOMER_GROSEQ": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow homer_groseq": null}}, "target": "Use nf-core subworkflow homer_groseq", "target_idx": 3}
{"id": "mod_coreograph_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, to identify complete/incomplete tissue cores on a tissue microarray. It has been trained on 9 TMA slides of different sizes and tissue types. (tools: coreograph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepcell_mesmer": "Deepcell/mesmer segmentation for whole-cell", "cnvkit_segment": "Infer discrete copy number segments from the given coverage table.", "sylph_query": "Sylph query command for querying genome databases against reads/metagenomes", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "ilastik_multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells"}}, "target": "coreograph", "target_idx": 3}
{"id": "noul_dynamic_resource_allocation_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_spotiflow_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Spotiflow, accurate and efficient spot detection with stereographic flow. (tools: spotiflow)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scramble/clusteranalysis": "The Cluster Analysis tool of Scramble analyses and interprets the soft-clipped clusters found by `cluster_iden", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "methurator/gtestimator": "Run estimator for DNA methylation sequencing saturation.", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope", "imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op"}}, "target": "spotiflow", "target_idx": 1}
{"id": "mod_custom_dumpsoftwareversions_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Custom module used to dump software versions within the nf-core pipeline template (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_build_add_kraken2_bracken": null, "longphase/phase": null, "sratools/fasterqdump": null, "custom/dumpsoftwareversions": null, "hmmer/hmmpress": null}}, "target": "custom/dumpsoftwareversions", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,well,fastq": null, "sample,matrix": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_survivor_bedpetovcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a bedpe file to a VCF file (beta version) (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/generateponbedpe": null, "agat/convertspgff2tsv": null, "lofreq/viterbi": null, "pangolin/updatedata": null, "survivor/bedpetovcf": null}}, "target": "survivor/bedpetovcf", "target_idx": 4}
{"id": "resource_bedtools_groupby_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GROUPBY", "tool": "bedtools/groupby", "description": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another column."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GROUPBY (Groups features in a BED file by given column(s) and computes summary statistics) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_7_0", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "field_constraint_expected_cells_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "mod_custom_multiqccustombiotype_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate MultiQC-compatible biotype count summaries from featureCounts output (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rustqc": "All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, an", "kaiju/mergeoutputs": "Merge two tab-separated output files of Kaiju and Kraken in the column format", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "custom/multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output", "gens/preparecovandbaf": "Tools for preparing inputs for visualization in Gens"}}, "target": "custom/multiqccustombiotype", "target_idx": 3}
{"id": "resource_bwa_samse_5", "category": "resource_profiling", "state": {"process": "BWA_SAMSE", "tool": "bwa/samse", "description": "Convert bwa SA coordinate file to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMSE (Convert bwa SA coordinate file to SAM format) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_high", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_16", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_centrifuger_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build centrifuger database for taxonomic profiling (tools: centrifuger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": null, "centrifuger/build": null, "biomformat/convert": null, "wfmash": null, "binette": null}}, "target": "centrifuger/build", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_47", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "field_constraint_sample_1_13", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "mod_scvitools_scar_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use scAR to remove ambient RNA from single-cell RNA-seq data (tools: scvitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ska_fasta": "Create genome sketch using split k-mers", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "scvitools_scar": "Module to use scAR to remove ambient RNA from single-cell RNA-seq data", "cnvkit_coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}}, "target": "scvitools_scar", "target_idx": 2}
{"id": "resource_autocycler_compress_3", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMPRESS", "tool": "autocycler/compress", "description": "Package candidate assemblies for clustering by Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMPRESS (Package candidate assemblies for clustering by Autocycler.) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_fetch_clean_hostile_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FETCH_CLEAN_HOSTILE", "modules": ["hostile/fetch", "hostile/clean"], "description": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files"}, "question": {"type": "choice", "instructions": "How should FASTQ_FETCH_CLEAN_HOSTILE (hostile/fetch, hostile/clean) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_fetch_clean_hostile": null, "Local subworkflow FASTQ_FETCH_CLEAN_HOSTILE": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_fetch_clean_hostile", "target_idx": 0}
{"id": "local_subworkflow_prepontreads_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should PREPONTREADS (porechop, nanoplot) be built?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null, "Local subworkflow PREPONTREADS": null, "Leave them out": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_0_32", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/hic) for Hi-C chromosome conformation capture mapping. Input files: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification.", "question": {"type": "choice", "instructions": "Which columns are standard for Hi-C chromosome conformation capture mapping input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_single_hyphen_cli_params_error_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_gatk4_condensedepthevidence_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges adjacent DepthEvidence records (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "regenie/step2": "Run REGENIE step 2 association testing from precomputed step 1 predictions", "gatk4/condensedepthevidence": "Merges adjacent DepthEvidence records", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content"}}, "target": "gatk4/condensedepthevidence", "target_idx": 3}
{"id": "mod_anarcii_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A language model for antigen receptor numbering (tools: anarcii)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeparg_predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "gatk4_concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "bcftools_annotate": "Add or remove annotations.", "anarcii": "A language model for antigen receptor numbering"}}, "target": "anarcii", "target_idx": 4}
{"id": "mod_hmmer_hmmpress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: compress and index profile database for hmmscan (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "hmmer/hmmemit": "emit sequences from a profile HMM", "hmmer/hmmpress": "compress and index profile database for hmmscan", "bam_ngscheckmate": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set o", "hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment"}}, "target": "hmmer/hmmpress", "target_idx": 2}
{"id": "mod_wipertools_reportgather_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that merges wiping reports generated by wipertools_fastqwiper (tools: reportgather)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "ganon_report": "Generate a ganon report file from the output of ganon classify", "pharmcat_reporter": "The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescri", "tidk_explore": "`tidk explore` attempts to find the simple telomeric repeat unit in the genome provided.\nIt will report this r", "wipertools_reportgather": "A tool of the wipertools suite that merges wiping reports generated by wipertools_fastqwiper"}}, "target": "wipertools_reportgather", "target_idx": 4}
{"id": "mod_bff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generating cell hashing calls from a matrix of count data. (tools: bff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"multiseqdemux": "Identify singlets, doublets and negative cells from multiplexing experiments. Annotate singlets by tags.", "rsem_preparereference": "Prepare a reference genome for RSEM", "bff": "Generating cell hashing calls from a matrix of count data.", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "faqcs": "Perform adapter and quality trimming on sequencing reads with reporting"}}, "target": "bff", "target_idx": 2}
{"id": "local_subworkflow_checkirma_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should this step (custom/checkirma) be packaged: Custom validation of assembly output?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow checkirma": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "core_tool_minimap2_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Long-read mapping of Oxford Nanopore and PacBio HiFi sequencing reads against human and microbial reference assemblies.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bowtie2": "Short read aligner", "subread": "Alignment tool", "minimap2": "Versatile pairwise aligner for long reads, spliced transcripts, and assemblies", "star": "RNA aligner", "bwa_mem": "DNA aligner"}}, "target": "minimap2", "target_idx": 2}
{"id": "mod_glimpse2_splitreference_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to create a binary reference panel for quick reading time. (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_split": "Split a vcf file into files per chromosome", "glimpse2_splitreference": "Tool to create a binary reference panel for quick reading time.", "rpbp_selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "bedtools_split": "Split BED files into several smaller BED files"}}, "target": "glimpse2_splitreference", "target_idx": 1}
{"id": "mod_treerecs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Treerecs is an open-source (species- and gene-) tree reconciliation software distributed under the GNU AGPL licence. It can correct, rearrange and (re-)root gene trees with regard to a given species tree. It was designed to be both efficient and easy to install and to use. (tools: treerecs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever ", "transrate": "Reference-free and reference-based quality assessment of de novo transcriptome\nassemblies. Only sequence-based", "biscuit_pileup": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call so", "treerecs": "Treerecs is an open-source (species- and gene-) tree reconciliation software distributed under the GNU AGPL li", "merqury_merqury": "k-mer based assembly evaluation."}}, "target": "treerecs", "target_idx": 3}
{"id": "resource_bamtools_split_4", "category": "resource_profiling", "state": {"process": "BAMTOOLS_SPLIT", "tool": "bamtools/split", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_SPLIT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bases2fastq_2", "category": "resource_profiling", "state": {"process": "BASES2FASTQ", "tool": "bases2fastq", "description": "Demultiplex Element Biosciences bases files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASES2FASTQ (Demultiplex Element Biosciences bases files) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_star_indexversion_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Get the minimal allowed index version from STAR (tools: star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/idxstats": "Reports alignment summary statistics for a BAM/CRAM/SAM file", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "vcf2zarr/explode": "Convert VCF(s) to intermediate columnar format", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "star/indexversion": "Get the minimal allowed index version from STAR"}}, "target": "star/indexversion", "target_idx": 4}
{"id": "resource_agat_convertspgff2gtf_4", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2GTF", "tool": "agat/convertspgff2gtf", "description": "Converts a GFF/GTF file into a proper GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2GTF (Converts a GFF/GTF file into a proper GTF file) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_rnastructurome_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnastructurome", "assay": "rnastructurome pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnastructurome (a bioinformatics pipeline for analysing chemical high-throug)?", "criteria": {"sample,sample_id,fastq_1,fastq_2,method": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1,fastq_2,barcode_details": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "sample,sample_id,fastq_1,fastq_2,method", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/pacvar) for PacBio HiFi unaligned BAM variant calling. Input files: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_28", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_autocycler_cluster_3", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_CLUSTER", "tool": "autocycler/cluster", "description": "Cluster replicons in compressed assemblies with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_CLUSTER (Cluster replicons in compressed assemblies with Autocycler.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_differentialabundance_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq. Topics: atac-seq, chip-seq, deseq2, differential-abundance, differential-expression, gsea. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"slamseq": null, "rangeland": null, "fastquorum": null, "pairgenomealign": null, "proteinfamilies": null, "hgtseq": null, "differentialabundance": null, "demultiplex": null, "epitopeprediction": null, "createtaxdb": null}}, "target": "differentialabundance", "target_idx": 6}
{"id": "mod_traitar_pfamget_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download PFAM database for traitar phenotype prediction (tools: traitar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_makepaddedseqdb": null, "cat_fastq": null, "traitar_pfamget": null, "bigslice_downloaddb": null, "antismash_antismashdownloaddatabases": null}}, "target": "traitar_pfamget", "target_idx": 2}
{"id": "mod_purecn_coverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageInMode should be set to 'link'. (tools: purecn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purecn_coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI", "survivor_filter": "Filter a vcf file based on size and/or regions to ignore", "purecn_normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as", "purecn_run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "cellrangeratac_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkfastq com"}}, "target": "purecn_coverage", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: 10x Multiome single-cell joint RNA and ATAC chromatin)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: 10x Multiome single-cell joint RNA and ATAC chromatin.", "criteria": {"sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "resource_agat_spfilterbyorfsize_0", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERBYORFSIZE", "tool": "agat/spfilterbyorfsize", "description": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF passing the test, the other contains the rest. By default the test is \"> 100\" that means all gene models that have ORF longer than 100 Amino acids, will pass the test."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERBYORFSIZE (The script reads a gff annotation file, and create two output files, one contain) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_1_4", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,rrna_fasta": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "mod_minimac4_impute_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Imputation of genotypes using a reference panel (tools: minimac4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "krakenuniq_build": "Download and build (custom) KrakenUniq databases", "numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "minimac4_impute": "Imputation of genotypes using a reference panel"}}, "target": "minimac4_impute", "target_idx": 4}
{"id": "field_constraint_bai_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_22", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_custom_tabulartogseacls_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make a GSEA class file (.cls) from tabular inputs (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/tabulartogseacls": "Make a GSEA class file (.cls) from tabular inputs", "bcftools/convert": "Converts certain output formats to VCF", "csvtk/join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "gsea/gsea": "run the Broad Gene Set Enrichment tool in GSEA mode", "salmon/index": "Create index for salmon"}}, "target": "custom/tabulartogseacls", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents). Input files: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents).", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_provenancereport_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/provenancereport", "description": "A simple provenance reporting pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/provenancereport?", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq,cell_count": null, "id,path": null, "sample,fastq_1,fastq_2,strandedness,condition": null}}, "target": "id,path", "target_idx": 2}
{"id": "core_tool_cellranger_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Demultiplexing, barcode processing, alignment, and UMI counting for 10x Genomics single-cell RNA-seq libraries.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"seurat": null, "alevin": null, "starsolo": null, "cellranger": null, "kallisto_bustools": null}}, "target": "cellranger", "target_idx": 3}
{"id": "pipe_all101_imcyto_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Image Mass Cytometry analysis pipeline. Topics: cytometry, image-analysis, image-processing, image-segmentation. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples"}}, "target": "imcyto", "target_idx": 6}
{"id": "pipe_all101_sopa_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Nextflow version of Sopa - spatial omics pipeline and analysis. Topics: segmentation, spatial-omics, spatial-proteomics, spatial-transcriptomics, spatialdata. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": null, "hlatyping": null, "sopa": null, "diaproteomics": null, "epitopeprediction": null}}, "target": "sopa", "target_idx": 2}
{"id": "resource_bedtools_maskfasta_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MASKFASTA", "tool": "bedtools/maskfasta", "description": "masks sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MASKFASTA (masks sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_file_pairing_in_channel_tuples_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_19", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_nextclade_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation) (tools: nextclade)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clair3": "Clair3 is a germline small variant caller for long-reads", "nextclade/datasetget": "Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ impleme", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "nextclade/run": "SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation)", "krakentools/combinekreports": "Takes multiple kraken-style reports and combines them into a single report file"}}, "target": "nextclade/run", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_34", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_agat_spfilterfeaturefromkilllist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "ngmaster": "Serotyping Neisseria gonorrhoeae assemblies", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "popscle_dscpileup": "Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode."}}, "target": "agat_spfilterfeaturefromkilllist", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_44", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_22", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_backsub_5", "category": "resource_profiling", "state": {"process": "BACKSUB", "tool": "backsub", "description": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACKSUB (Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_rastair_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assess positive C->T conversion as a readout for methylation on a genome-wide basis (tools: rastair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lofreq/alnqual": "Lofreq subcommand to for insert base and indel alignment qualities", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "summarizedexperiment/summarizedexperiment": "SummarizedExperiment container", "rastair/call": "Assess positive C->T conversion as a readout for methylation on a genome-wide basis", "bismark/align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "rastair/call", "target_idx": 3}
{"id": "mod_tsebra_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extrisic evidence support (tools: tsebra)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "sourmash/index": "Create a database of sourmash signatures (a group of FracMinHash sketches) to be used as references.", "scimap/spatiallda": "SpatialLDA uses an LDA based approach for the identification of cellular neighborhoods, using cell type identi"}}, "target": "tsebra", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Single-end Illumina RNA-seq with strandedness. Input files: Single-end FASTQ reads per library.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "mod_bcftools_stats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates stats from VCF files (tools: stats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"viennarna_rnacofold": null, "igv_js": null, "bcftools_consensus": null, "bcftools_concat": null, "bcftools_stats": null}}, "target": "bcftools_stats", "target_idx": 4}
{"id": "mod_agat_spextractsequences_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This script extracts sequences in fasta format according to features described\nin a gff file. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd/dosaf": "Estimate site allele frequencies from BAM files.", "samtools/dict": "Create a sequence dictionary file from a FASTA file", "seqkit/seq": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID"}}, "target": "agat/spextractsequences", "target_idx": 3}
{"id": "pipe_all101_metatdenovo_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses.. Topics: eukaryotes, metagenomics, metatranscriptomics, prokaryotes, viruses. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "metapep": "From metagenomes to epitopes and beyond", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, "}}, "target": "metatdenovo", "target_idx": 7}
{"id": "mod_rastair_methylkit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parses rastair call output and converts it into a MethylKit-compatible format. (tools: rastair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rastair/methylkit": "Parses rastair call output and converts it into a MethylKit-compatible format.", "hostile/clean": "Removes host reads from short- and long-read FASTQ sequencing files", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bioformats2raw": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible ", "bismark/methylationextractor": "Extracts methylation information for individual cytosines from alignments."}}, "target": "rastair/methylkit", "target_idx": 0}
{"id": "mod_tagbam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool for tagging BAM files. (tools: tagbam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tagbam": "A tool for tagging BAM files.", "mirtrace/qc": "A tool for quality control and tracing taxonomic origins of microRNA sequencing data", "autocycler/cluster": "Cluster replicons in compressed assemblies with Autocycler.", "porechop/porechop": "Adapter removal and demultiplexing of Oxford Nanopore reads", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler."}}, "target": "tagbam", "target_idx": 0}
{"id": "noul_channel_collect_operator_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_sex_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "resource_bracken_combinebrackenoutputs_5", "category": "resource_profiling", "state": {"process": "BRACKEN_COMBINEBRACKENOUTPUTS", "tool": "bracken/combinebrackenoutputs", "description": "Combine output of metagenomic samples analyzed by bracken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_COMBINEBRACKENOUTPUTS (Combine output of metagenomic samples analyzed by bracken.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_bamtofastq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Converts bam or cram files to fastq format and does quality control.. Topics: bamtofastq, conversion, cramtofastq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "callingcards": "A pipeline for processing calling cards data", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i"}}, "target": "bamtofastq", "target_idx": 5}
{"id": "intent_ask_question_4", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "mod_sentieon_dedup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs the sentieon tool LocusCollector followed by Dedup. LocusCollector collects read information that is used by Dedup which in turn marks or removes duplicate reads. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwafastalign/mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "stadeniolib/scramble": "Advanced sequence file format conversions", "scimap/mcmicro": "SCIMAP is a suite of tools that enables spatial single-cell analyses", "bwa/mem": "Performs fastq alignment to a fasta reference using BWA", "sentieon/dedup": "Runs the sentieon tool LocusCollector followed by Dedup. LocusCollector collects read information that is used"}}, "target": "sentieon/dedup", "target_idx": 4}
{"id": "field_constraint_sample_0_12", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "mod_hmmer_hmmrank_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: R script that scores output from multiple runs of hmmer/hmmsearch (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmrank": "R script that scores output from multiple runs of hmmer/hmmsearch", "hmmer_eslalimask": "Mask multiple sequence alignments", "shasta": "The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using DNA reads g", "hmmer_hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile", "samtools_fasta": "Converts a SAM/BAM/CRAM file to FASTA"}}, "target": "hmmer_hmmrank", "target_idx": 0}
{"id": "resource_amrfinderplus_update_2", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_UPDATE", "tool": "amrfinderplus/update", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_UPDATE (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_bam_cnv_wisecondorx_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CNV_WISECONDORX", "modules": ["wisecondorx/convert", "wisecondorx/predict"], "description": "A subworkflow for calling CNVs using WisecondorX"}, "question": {"type": "choice", "instructions": "How should BAM_CNV_WISECONDORX (wisecondorx/convert, wisecondorx/predict) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_CNV_WISECONDORX": null, "Use nf-core subworkflow bam_cnv_wisecondorx": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_cnv_wisecondorx", "target_idx": 2}
{"id": "field_constraint_sex_1_9", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "noul_undeclared_process_file_inputs_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bcftools_reheader_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_REHEADER", "tool": "bcftools/reheader", "description": "Reheader a VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_REHEADER (Reheader a VCF file) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_bwa_mem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA", "bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "elprep_merge": "Merge split bam/sam chunks in one file", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline"}}, "target": "bwa_mem", "target_idx": 0}
{"id": "schema_std_readsimulator_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/readsimulator. Description: A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/readsimulator.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,seed": null, "id,fasta,reference,optional_data,template": null}}, "target": "sample,seed", "target_idx": 2}
{"id": "mod_metaeuk_easypredict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotation of eukaryotic metagenomes using MetaEuk (tools: metaeuk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lissero": null, "agat/spfilterbyorfsize": null, "metaeuk/easypredict": null, "agat/spextractsequences": null, "homer/annotatepeaks": null}}, "target": "metaeuk/easypredict", "target_idx": 2}
{"id": "mod_cellranger_mkfastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"geoquery_getgeo": null, "bowtie_align": null, "cellranger_mkfastq": null, "bbmap_bbsplit": null, "bbmap_bbduk": null}}, "target": "cellranger_mkfastq", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_1", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_named_process_output_emits_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "intent_debug_error_9", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "debug_error": null, "prepare_data": null}}, "target": "debug_error", "target_idx": 2}
{"id": "mod_bedtools_subtract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining portion of A. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/subtract": null, "rpbp/selectfinalpredictionset": null, "agat/convertbed2gff": null, "annotsv/annotsv": null, "vizgenpostprocessing/compiletilesegmentation": null}}, "target": "bedtools/subtract", "target_idx": 0}
{"id": "resource_angsd_soapsnpcalibration_0", "category": "resource_profiling", "state": {"process": "ANGSD_SOAPSNPCALIBRATION", "tool": "angsd/soapsnpcalibration", "description": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_SOAPSNPCALIBRATION (Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality mat) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_clippy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs the Clippy CLIP peak caller (tools: clippy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"icountmini/metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks.", "clippy": "Runs the Clippy CLIP peak caller", "folddisco/query": "Search a prebuilt folddisco index for a discontinuous residue motif in a query protein structure", "icountmini/summary": "Report proportion of cross-link events/sites on each region type.", "bio2zarr/vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}}, "target": "clippy", "target_idx": 1}
{"id": "pipe_all101_clipseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling options.. Topics: clip, clip-seq, peak-calling, rna-rbp-interactions. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"detaxizer": null, "longraredisease": null, "riboseq": null, "coproid": null, "clipseq": null}}, "target": "clipseq", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_2_15", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_strelka_germline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation (tools: strelka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strelka/germline": "Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation", "canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "isoseq/refine": "Remove polyA tail and artificial concatemers", "dragen/germline": "The DRAGEN DNA Germline Pipeline accelerates the secondary analysis of NGS data by harnessing the tremendous p"}}, "target": "strelka/germline", "target_idx": 0}
{"id": "mod_variancepartition_dream_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs a differential expression analysis with dream() from variancePartition R package (tools: dream)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "fastk_histex": "A fast K-mer counter for high-fidelity shotgun datasets", "variancepartition_dream": "Runs a differential expression analysis with dream() from variancePartition R package", "pbcpgtools_alignedbamtocpgscores": "Converts aligned BAM files into CpG methylation scores", "custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "variancepartition_dream", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_36", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_midas_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to estimate bacterial species abundance (tools: midas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch_sintax": "Taxonomic classification using the sintax algorithm.", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "mmseqs_easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2", "midas_run": "A tool to estimate bacterial species abundance"}}, "target": "midas_run", "target_idx": 4}
{"id": "resource_artic_aligntrim_0", "category": "resource_profiling", "state": {"process": "ARTIC_ALIGNTRIM", "tool": "artic/aligntrim", "description": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_ALIGNTRIM (Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_34", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "schema_std_pathogensurveillance_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pathogensurveillance. Description: Surveillance of pathogens using population genomics and sequencing.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pathogensurveillance.", "criteria": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample_id,bam,vcf,library_id,lane": null, "sample_id,name,description,path,path_2": null, "fastq_1,fastq_2,group,replicate,md5_1": null}}, "target": "sample_id,name,description,path,path_2", "target_idx": 2}
{"id": "mod_hmmcopy_generatemap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perl script (generateMap.pl) generates the mappability of a genome given a certain size of reads, for input to hmmcopy mapcounter. Takes a very long time on large genomes, is not parallelised at all. (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler_makebins": "Generate fixed-width genomic bins", "hmmcopy_mapcounter": "mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a big", "hmmcopy_generatemap": "Perl script (generateMap.pl) generates the mappability of a genome given a certain size of reads, for input to", "hmmcopy_gccounter": "gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta", "salmon_quant": "gene/transcript quantification with Salmon"}}, "target": "hmmcopy_generatemap", "target_idx": 2}
{"id": "noul_undeclared_process_file_inputs_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_39", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_gatk4_filtermutectcalls_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters the raw output of mutect2, can optionally use outputs of calculatecontamination and learnreadorientationmodel to improve filtering. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spkeeplongestisoform": null, "gatk4/filtermutectcalls": null, "infernal/cmsearch": null, "nacho/qc": null, "agat/spfilterbyorfsize": null}}, "target": "gatk4/filtermutectcalls", "target_idx": 1}
{"id": "field_constraint_expected_cells_1_8", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_20", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bedtools_maskfasta_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MASKFASTA", "tool": "bedtools/maskfasta", "description": "masks sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MASKFASTA (masks sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "ATAC-seq chromatin accessibility with biological replicates", "data_format": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,bam": null, "sample,bed": null, "sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_agat_convertgff2bed_3", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTGFF2BED", "tool": "agat/convertgff2bed", "description": "Takes a GFF3 file and converts to a bed12 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTGFF2BED (Takes a GFF3 file and converts to a bed12 file) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_racon_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Consensus module for raw de novo DNA assembly of long uncorrected reads (tools: racon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "bio2zarr/vcf2zarrexplode": "Convert VCF(s) to intermediate columnar format (ICF)", "ale": "ALE: assembly likelihood estimator.", "dastool/fastatocontig2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "racon": "Consensus module for raw de novo DNA assembly of long uncorrected reads"}}, "target": "racon", "target_idx": 4}
{"id": "mod_preseq_lcextrap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software for predicting library complexity and genome coverage in high-throughput sequencing (tools: preseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"preseq_ccurve": "Software for predicting library complexity and genome coverage in high-throughput sequencing", "vg_index": "write your description here", "krakentools_extractkrakenreads": "Extract reads classified at any user-specified taxonomy IDs.", "rustqc": "All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, an", "preseq_lcextrap": "Software for predicting library complexity and genome coverage in high-throughput sequencing"}}, "target": "preseq_lcextrap", "target_idx": 4}
{"id": "samplesheet_arch_scrna_multiome_2_5", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null, "sample,matrix": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_4_0", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted BAMs with index for tumor and normal samples?", "criteria": {"patient,sample,status,bam,bai": null, "sample,vcf": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "core_tool_fastqc_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Quality control metric evaluation including per-base sequence quality scores, GC content distributions, and k-mer overrepresentation for raw FASTQ data.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"fastqc": "Quality control tool for high throughput sequence data", "falco": "FastQC C++ drop-in", "qualimap": "BAM QC tool", "nanoplot": "Nanopore plotting", "multiqc": "Aggregate report tool"}}, "target": "fastqc", "target_idx": 0}
{"id": "resource_abricate_summary_5", "category": "resource_profiling", "state": {"process": "ABRICATE_SUMMARY", "tool": "abricate/summary", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_SUMMARY (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_phenotype_0_10", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "mod_octopusv_svcf2vcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts octopusv SVCF files to the standard VCF format (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mitorsaw/haplotype": "Mitorsaw analyses mitochondrial variants and identifies heteroplasmy and homoplasmy", "annotsv/installannotations": "Install the AnnotSV annotations", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "octopusv/svcf2vcf": "Converts octopusv SVCF files to the standard VCF format"}}, "target": "octopusv/svcf2vcf", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_1_34", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_happy_ftxpy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Somatic VCF Feature Extraction tool from hap.y. (tools: happy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/ftxpy": "Somatic VCF Feature Extraction tool from hap.y.", "happy/sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic ", "bedtools/map": "Allows one to screen for overlaps between two sets of genomic features.", "happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "fargene": "tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full"}}, "target": "happy/ftxpy", "target_idx": 0}
{"id": "resource_bbmap_clumpify_5", "category": "resource_profiling", "state": {"process": "BBMAP_CLUMPIFY", "tool": "bbmap/clumpify", "description": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_CLUMPIFY (Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_4_1", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end FASTQ reads per library?", "criteria": {"sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_0_2", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "subworkflow_pkg_bam_variant_calling_sort_freebayes_bcftools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS", "modules": ["freebayes", "bcftools/sort"], "description": "Call variants using freebayes, then sort and index"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS (freebayes, bcftools/sort) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools": null, "Leave them out": null, "Local subworkflow BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS": null}}, "target": "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Single-end Oxford Nanopore direct RNA)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fast5": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_3_0", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral genome sequencing on Oxford Nanopore MinION / GridION with entry step NANOPLOT.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "resource_angsd_contamination_4", "category": "resource_profiling", "state": {"process": "ANGSD_CONTAMINATION", "tool": "angsd/contamination", "description": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_CONTAMINATION (A tool to estimate nuclear contamination in males based on heterozygosity in the) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_dedup_bismark_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BISMARK", "modules": ["bismark/align", "samtools/sort", "samtools/index", "bismark/deduplicate", "bismark/methylationextractor", "bismark/coverage2cytosine", "bismark/report", "bismark/summary"], "description": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BISMARK (bismark/align, samtools/sort, samtools/index, bismark/deduplicate, bismark/methylationextractor, bismark/coverage2cytosine, bismark/report, bismark/summary) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_DEDUP_BISMARK": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_dedup_bismark": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bismark", "target_idx": 3}
{"id": "mod_finaletoolkit_delfi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the DELFI scores (Cristiano et al., 2019) from a BAM file. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "finaletoolkit/delfi": "Calculate the DELFI scores (Cristiano et al., 2019) from a BAM file.", "csvtk/split": "Splits CSV/TSV into multiple files according to column values", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID"}}, "target": "finaletoolkit/delfi", "target_idx": 1}
{"id": "mod_dastool_dastool_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DAS Tool binning step. (tools: dastool)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krona_ktimportkrona": "Collect multiple krona reports into a single html file", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "fasta_clean_fcs": "Foreign Contamination Screen (FCS) is a tool suite for identifying and removing contaminant sequences in genom", "dastool_dastool": "DAS Tool binning step.", "concoct_concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile"}}, "target": "dastool_dastool", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_9", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_cageseq_transcription_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/cageseq --input samplesheet.csv (Assay: CAGE-seq 5-prime capped transcript end sequencing)", "question": {"type": "choice", "instructions": "Which columns are standard for CAGE-seq 5-prime capped transcript end sequencing input samplesheet?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_molkartgarage_clahe_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Contrast-limited adjusted histogram equalization (CLAHE) on single-channel tif images. (tools: molkartgarage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr_propr": "Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coeff", "bioformats2raw": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible ", "fasta_bgzip_index_dict_samtools": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA f", "bftools_showinf": "Extract OME xml data from OME-tif", "molkartgarage_clahe": "Contrast-limited adjusted histogram equalization (CLAHE) on single-channel tif images."}}, "target": "molkartgarage_clahe", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay_type": "PacBio HiFi unaligned BAM variant calling", "data_format": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "mod_stainwarpy_transformsegmask_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy (tools: stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy_register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "stainwarpy_transformsegmask": "Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy", "mmseqs_tsv2exprofiledb": "Conversion of expandable profile to databases to the MMseqs2 databases format", "dshbio_exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "tif_registration_stainwarpy": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy"}}, "target": "stainwarpy_transformsegmask", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_star_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_STAR", "modules": ["star/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bowtie2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_STAR (star/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_ALIGN_STAR": null, "Use nf-core subworkflow fastq_align_star": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_star", "target_idx": 2}
{"id": "noul_modular_subworkflow_composition_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_bai_1_6", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Metagenomic MAG assembly with comparative groups", "data_format": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns are standard for Metagenomic MAG assembly with comparative groups input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "mod_pharokka_installdatabases_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Install databases necessary for Pharokka's functional analysis (tools: pharokka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"oarfish/alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "cobrameta": "A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining o", "survivor/filter": "Filter a vcf file based on size and/or regions to ignore", "genomad/download": "Download geNomad databases and related files", "pharokka/installdatabases": "Install databases necessary for Pharokka's functional analysis"}}, "target": "pharokka/installdatabases", "target_idx": 4}
{"id": "resource_ariba_getref_2", "category": "resource_profiling", "state": {"process": "ARIBA_GETREF", "tool": "ariba/getref", "description": "Download and prepare database for Ariba analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_GETREF (Download and prepare database for Ariba analysis) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_sex_2_10", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_14", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic tumor-normal calling from pre-aligned BAM files", "data_format": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Xenium in situ subcellular spatial RNA transcriptomics", "data_format": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Xenium output bundle with transcripts CSV, cell polygons, and morphology images?", "criteria": {"sample,vcf": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null, "sample,bam": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "mod_bigslice_downloaddb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module. (tools: bigslice)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "bigscape/bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters"}}, "target": "bigslice/downloaddb", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_tn_0_3", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metatdenovo", "assay_type": "Environmental community metatranscriptomics de novo assembly", "data_format": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns are standard for Environmental community metatranscriptomics de novo assembly input samplesheet?", "criteria": {"sample,bam": null, "sample,rrna_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "pipe_all101_stableexpression_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). The ideal use case is for determining the most suitable RT-qPCR reference genes for a given species.. Topics: expression, housekeeping-genes, qpcr-analysis. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"fastqrepair": null, "spatialaxe": null, "stableexpression": null, "hic": null, "reportho": null}}, "target": "stableexpression", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_6_5", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns are standard for Data-Independent Acquisition (DIA) quantitative mass spectrometry input samplesheet?", "criteria": {"sample,peptides_tsv": null, "sample,mzml": null, "sample,raw_file,condition": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "mod_vcf_annotate_snpeff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform annotation with snpEff and bgzip + tabix index the resulting VCF file (tools: vcf_annotate_snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mtmalign_align": "Aligns protein structures using mTM-align", "amplify_predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file", "atlas_call": "generate VCF file from a BAM file using various calling methods"}}, "target": "vcf_annotate_snpeff", "target_idx": 3}
{"id": "pipe_core10_viralrecon_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Assembly and intrahost low-frequency variant calling for viral isolates and SARS-CoV-2 samples.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)"}}, "target": "viralrecon", "target_idx": 8}
{"id": "noul_module_metadata_propagation_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_faa_seqfu_seqkit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that optionally preprocesses amino acid FASTA sequences\n(seqkit seq/replace/rmdup), computes sequence statistics before and\nafter preprocessing using seqfu stats, and exports MultiQC-compatible\nstatistics and software versions. (tools: faa_seqfu_seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"refsolver/identify": "Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver", "faa_seqfu_seqkit": "Subworkflow that optionally preprocesses amino acid FASTA sequences\n(seqkit seq/replace/rmdup), computes seque", "fasta_newick_epang_gappa": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in ", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "faa_seqfu_seqkit", "target_idx": 1}
{"id": "noul_single_hyphen_cli_params_error_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_crabs_import_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In-house generated or curated data can be imported into CRABS. (tools: crabs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crispresso2": "A software pipeline for the analysis of genome editing outcomes from deep sequencing data", "kraken2_buildstandard": "Downloads and builds Kraken2 standard database", "crabs_import": "In-house generated or curated data can be imported into CRABS.", "alignoth": "Creating alignment plots from bam files", "fastqutils_info": "Performs quality control of FASTQ files"}}, "target": "crabs_import", "target_idx": 2}
{"id": "resource_antismash_antismashdownloaddatabases_5", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHDOWNLOADDATABASES", "tool": "antismash/antismashdownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bcftools_roh_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROH", "tool": "bcftools/roh", "description": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROH (A program for detecting runs of homo/autozygosity. Only bi-allelic sites are con) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_stainwarpy_register_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Register H&E stained and Multiplexed tissue images using feature-based image registration (tools: stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy_extractchannel": "Extract a single channel image from multiplexed tissue images using stainwarpy", "gappa_examineheattree": "colours a phylogeny with placement densities", "tif_registration_stainwarpy": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy", "stainwarpy_register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "metamdbg_asm": "Metagenome assembler for long-read sequences (HiFi and ONT)."}}, "target": "stainwarpy_register", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_49", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "schema_std_lsmquant_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/lsmquant", "description": "A pipeline for processing and analysis of light-sheet microscopy images.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/lsmquant?", "criteria": {"sample_id,img_directory,parameter_file": null, "sample,bundle,image": null, "sample,fasta,protein,gbk,gff": null, "id,path": null}}, "target": "sample_id,img_directory,parameter_file", "target_idx": 0}
{"id": "mod_atlas_splitmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: split single end read groups by length and merge paired end reads (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools/split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "gridss/somaticfilter": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "csvtk/split": "Splits CSV/TSV into multiple files according to column values", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "somalier/relate": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/"}}, "target": "atlas/splitmerge", "target_idx": 3}
{"id": "noul_channel_filter_operator_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_paraphase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: HiFi-based caller for highly homologous genes (tools: paraphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_cluster": "Cluster replicons in compressed assemblies with Autocycler.", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "autocycler_resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "paraphase": "HiFi-based caller for highly homologous genes", "scimap_spatiallda": "SpatialLDA uses an LDA based approach for the identification of cellular neighborhoods, using cell type identi"}}, "target": "paraphase", "target_idx": 3}
{"id": "subworkflow_pkg_opt_flip_track_stat_0", "category": "subworkflow_packaging", "state": {"subworkflow": "OPT_FLIP_TRACK_STAT", "modules": ["opt/flip", "opt/track", "opt/stat"], "description": "Off-target probe detection"}, "question": {"type": "choice", "instructions": "How should OPT_FLIP_TRACK_STAT (opt/flip, opt/track, opt/stat) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow OPT_FLIP_TRACK_STAT": null, "Use nf-core subworkflow opt_flip_track_stat": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow opt_flip_track_stat", "target_idx": 2}
{"id": "mod_hmmer_eslsfetch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. The esl-sfetch utility is an Easel\nminiapp bundled with the HMMER package. This module only fetches: the SSI\nindex must be produced beforehand by the sibling module\n`hmmer/eslsfetchindex`. The keyfile is used to fetch the named sequences\n(-f), or, with ext.args = '-C', parsed as a subsequence coordinate file\n(-Cf) to extract and rename subsequences. (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/eslsfetch": "Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. T", "fastqscan": "FASTQ summary statistics in JSON format", "hmmer/eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi", "foldmason/createdb": "Creates a database for Foldmason.", "hmmer/hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile"}}, "target": "hmmer/eslsfetch", "target_idx": 0}
{"id": "noul_include_modular_process_syntax_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_ferrohgvs_parse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parse and validate HGVS variant descriptions with ferro (tools: ferrohgvs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jvarkit_vcffilterjdk": "Filtering VCF with dynamically-compiled java expressions", "ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro", "sentieon_collectvcmetrics": "Accelerated implementation of the Picard CollectVariantCallingMetrics tool.", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "ferrohgvs_parse", "target_idx": 1}
{"id": "mod_cleanifier_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a Cuckoo filter or Cuckoo hash table index from reference sequences (FASTA/FASTQ) for fast contamination removal. (tools: cleanifier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"opt_flip_track_stat": null, "mdust": null, "bowtie/build": null, "biscuit/qc": null, "cleanifier/index": null}}, "target": "cleanifier/index", "target_idx": 4}
{"id": "mod_icountmini_metagene_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot a metagene of cross-link events/sites around various transcriptomic landmarks. (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clippy": null, "bcl_demultiplex": null, "icountmini_segment": null, "icountmini_metagene": null, "sourmash_pairwise": null}}, "target": "icountmini_metagene", "target_idx": 3}
{"id": "mod_sylph_profile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sylph profile command for taxonoming profiling (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"savana/to": "Tumour-only somatic SV calling with optional copy-number analysis in SAVANA", "deeptools/plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "fastp": "Perform adapter/quality trimming on sequencing reads", "sylph/profile": "Sylph profile command for taxonoming profiling", "expansionhunterdenovo/profile": "Compute genome-wide STR profile"}}, "target": "sylph/profile", "target_idx": 3}
{"id": "mod_pbmarkdup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes one or multiple sequencing chips of an amplified library as HiFi reads and marks or removes\nduplicates. (tools: pbmarkdup)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbmarkdup": "Takes one or multiple sequencing chips of an amplified library as HiFi reads and marks or removes\nduplicates.", "bedtools/intersect": "Allows one to screen for overlaps between two sets of genomic features.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "bam_markduplicates_samtools": "Samtools markduplicate SAM/BAM/CRAM file", "staphscan": "staphscan is a tool to screen genome assemblies of Staphylococcus aureus"}}, "target": "pbmarkdup", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for VARIANTSOFINT (custom/variantsofint).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow variantsofint": null, "Local subworkflow VARIANTSOFINT": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 3}
{"id": "mod_samtools_dict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a sequence dictionary file from a FASTA file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "svdss_index": "Index a reference genome FASTA file using SVDSS (via ropebwt3), producing either an FMD or FMR index for use w", "atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "samtools_dict": "Create a sequence dictionary file from a FASTA file"}}, "target": "samtools_dict", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_0_35", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "local_subworkflow_positionsofint_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should POSITIONSOFINT (custom/positionsofint) be built?", "criteria": {"Use nf-core subworkflow positionsofint": null, "Leave them out": null, "Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 2}
{"id": "pipe_all101_dualrnaseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous RNA-seq.. Topics: dualrna-seq, host-pathogen, quantification, readmapping, rna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]"}}, "target": "dualrnaseq", "target_idx": 3}
{"id": "field_constraint_status_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_3_2", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "PBMM2_ALIGN", "library_inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for PacBio HiFi unaligned BAM variant calling with entry step PBMM2_ALIGN.", "criteria": {"sample,bam,bai": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "resource_autocycler_resolve_0", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_RESOLVE", "tool": "autocycler/resolve", "description": "Resolve trimmed assembly graphs into final contigs within Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_RESOLVE (Resolve trimmed assembly graphs into final contigs within Autocycler.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_createtaxdb_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for database analysis? Specific context: Parallelised and automated construction of metagenomic classifier databases of different tools. Topics: database, database-builder, metagenomic-profiling, metagenomics, profiling, taxonomic-profiling. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]"}}, "target": "createtaxdb", "target_idx": 0}
{"id": "mod_cmaple_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm (tools: cmaple)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "gappa/examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "eido/convert": "Convert any PEP project or Nextflow samplesheet to any format"}}, "target": "cmaple", "target_idx": 2}
{"id": "pipe_all101_seqinspector_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for genomics. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "seqsubmit": "nf-core pipeline for data submission to ENA"}}, "target": "seqinspector", "target_idx": 3}
{"id": "subworkflow_pkg_bam_methyldackel_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_METHYLDACKEL", "modules": ["methyldackel/extract", "methyldackel/mbias"], "description": "Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignments using Methyldackel."}, "question": {"type": "choice", "instructions": "How should BAM_METHYLDACKEL (methyldackel/extract, methyldackel/mbias) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_methyldackel": null, "Local subworkflow BAM_METHYLDACKEL": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_methyldackel", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_4", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "intent_ask_question_9", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "ask_question": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_snpsites_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rapidly extracts SNPs from a multi-FASTA alignment. (tools: snpsites)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler_merge": "Merge multiple coolers with identical axes", "snpsites": "Rapidly extracts SNPs from a multi-FASTA alignment.", "vt_decompose": "decomposes multiallelic variants into biallelic in a VCF file.", "eigenstratdatabasetools_eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset.", "umitools_extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place"}}, "target": "snpsites", "target_idx": 1}
{"id": "mod_purgedups_purgedups_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Purge haplotigs and overlaps for an assembly (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purgedups/purgedups": "Purge haplotigs and overlaps for an assembly", "oarfish/alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "purgedups/getseqs": "Separates out sequences purged of falsely duplicated sequences.", "cnvpytor/histogram": "calculates read depth histograms", "samtools/index": "Index SAM/BAM/CRAM file"}}, "target": "purgedups/purgedups", "target_idx": 0}
{"id": "resource_abricate_summary_1", "category": "resource_profiling", "state": {"process": "ABRICATE_SUMMARY", "tool": "abricate/summary", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_SUMMARY (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_hlatyping_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Precision HLA typing from next-generation sequencing data. Topics: dna, hla, hla-typing, immunology, optitype, personalized-medicine. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"reportho": null, "marsseq": null, "kmermaid": null, "drop": null, "funcprofiler": null, "slamseq": null, "taxprofiler": null, "hlatyping": null}}, "target": "hlatyping", "target_idx": 7}
{"id": "mod_fasta_hmmsearch_rank_fastas_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hmmsearch and output separate fasta files for top scoring hits to each profile (tools: fasta_hmmsearch_rank_fastas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_eslsfetch": "Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. T", "fusionreport_download": "Build DB for fusionreport", "fastq_align_mapad": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and index", "hmmer_eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi", "fasta_hmmsearch_rank_fastas": "Run hmmsearch and output separate fasta files for top scoring hits to each profile"}}, "target": "fasta_hmmsearch_rank_fastas", "target_idx": 4}
{"id": "mod_faqcs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform adapter and quality trimming on sequencing reads with reporting (tools: faqcs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequencetools_pileupcaller": null, "chromap_chromap": null, "dragmap_align": null, "chelae_trim": null, "faqcs": null}}, "target": "faqcs", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_removeadapters_merge_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_REMOVEADAPTERS_MERGE", "modules": ["trimmomatic", "cutadapt", "trimgalore", "bbmap/bbduk", "leehom", "fastp", "adapterremoval", "cat/fastq"], "description": "Remove adapters and merge reads based on various module choices"}, "question": {"type": "choice", "instructions": "How should FASTQ_REMOVEADAPTERS_MERGE (trimmomatic, cutadapt, trimgalore, bbmap/bbduk, leehom, fastp, adapterremoval, cat/fastq) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_removeadapters_merge": null, "Local subworkflow FASTQ_REMOVEADAPTERS_MERGE": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_removeadapters_merge", "target_idx": 0}
{"id": "field_constraint_bam_0_8", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "mod_annotsv_annotsv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotation and Ranking of Structural Variation (tools: annotsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/bam2fq": "The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "bakta/bakta": "Annotation of bacterial genomes (isolates, MAGs) and plasmids", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "gfatools/stat": "Summary statistics for GFA files"}}, "target": "annotsv/annotsv", "target_idx": 1}
{"id": "mod_dia_proteomics_analysis_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Complete DIA-NN proteomics analysis pipeline including in-silico library generation,\npreliminary analysis, empirical library assembly, individual analysis, and final quantification.\nThis subworkflow combines DIA-NN modules with quantms-utils for comprehensive\ndata-independent acquisition (DIA) proteomics data processing. (tools: dia_proteomics_analysis)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann/insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "samplesheetparser/info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "dia_proteomics_analysis": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,\npreliminary analysis, emp", "custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "quantmsutils/diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils"}}, "target": "dia_proteomics_analysis", "target_idx": 2}
{"id": "mod_multiqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregate results from bioinformatics analyses across many samples into a single report (tools: multiqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods.", "multiqc": "Aggregate results from bioinformatics analyses across many samples into a single report", "multiqcsav": "Aggregate results from bioinformatics analyses across many samples into a single report, with support for mult", "deacon/filter": "Filter DNA sequences using index of reference genome", "mmseqs/makepaddedseqdb": "Create an MMseqs padded database from an existing MMseqs database"}}, "target": "multiqc", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_6_0", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns are standard for Genome analysis from reference-compressed CRAM files input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cram,crai": null, "sample,bam,bai": null, "sample,cram": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "resource_baysor_preview_2", "category": "resource_profiling", "state": {"process": "BAYSOR_PREVIEW", "tool": "baysor/preview", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_PREVIEW (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_trust4_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run TRUST4 on RNA-seq data (tools: trust4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trust4": "Run TRUST4 on RNA-seq data", "anarcii": "A language model for antigen receptor numbering", "anndata/getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file", "bedtools/makewindows": "Makes adjacent or sliding windows across a genome or BED file.", "amulety/antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}}, "target": "trust4", "target_idx": 0}
{"id": "mod_regenie_step2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run REGENIE step 2 association testing from precomputed step 1 predictions (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepvariant_callvariants": null, "regenie_step2": null, "admixture": null, "gcta_fastgwa": null, "gatk4_asereadcounter": null}}, "target": "regenie_step2", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_trimgalore_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_TRIMGALORE", "modules": ["fastqc", "umitools/extract", "trimgalore"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_TRIMGALORE (fastqc, umitools/extract, trimgalore) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_fastqc_umitools_trimgalore": null, "Local subworkflow FASTQ_FASTQC_UMITOOLS_TRIMGALORE": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_trimgalore", "target_idx": 2}
{"id": "field_constraint_bam_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_0_0", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Single-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "resource_ale_3", "category": "resource_profiling", "state": {"process": "ALE", "tool": "ale", "description": "ALE: assembly likelihood estimator."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALE (ALE: assembly likelihood estimator.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_strandedness_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"type: boolean": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_custom_rsemmergecounts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge per-sample RSEM results into wide and long format TSV matrices (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "samtools/getrg": "filter/convert SAM/BAM/CRAM file", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs", "rsem/preparereference": "Prepare a reference genome for RSEM", "sentieon/rsemcalculateexpression": "Calculate expression with RSEM"}}, "target": "custom/rsemmergecounts", "target_idx": 0}
{"id": "mod_eautils_fastqstats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate general and per-base statistics from FASTQ files (tools: eautils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/getref": null, "abricate/summary": null, "adapterremoval": null, "bam_impute_quilt": null, "eautils/fastqstats": null}}, "target": "eautils/fastqstats", "target_idx": 4}
{"id": "mod_rmarkdownnotebook_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render an rmarkdown notebook. Supports parametrization. (tools: rmarkdown)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quarto/prerender": "Pre-render a Quarto document to markdown, including parametrization", "fastq_subsample_fq_salmon": "Subsample fastq", "vuegen": "The VueGen nf-core module is designed to automate report generation from outputs produced by other modules, su", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization.", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "rmarkdownnotebook", "target_idx": 3}
{"id": "samplesheet_arch_amplicon_16s_paired_0_3", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fasta": null, "sample,primer_fwd,primer_rev": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_0_4", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_gatk4_intervallisttobed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts an Picard IntervalList file to a BED file. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq3_tag": "Extract UMI and cell barcodes", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "catpack_addnames": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "gatk4_intervallisttobed": "Converts an Picard IntervalList file to a BED file."}}, "target": "gatk4_intervallisttobed", "target_idx": 4}
{"id": "noul_named_process_output_emits_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_bai_2_4", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "mod_gatk4_applyvqsr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a two-stage process called Variant Quality Score Recalibration (VQSR).\nSpecifically, it applies filtering to the input variants based on the recalibration table produced\nin the first step by VariantRecalibrator and a target sensitivity value. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "td2/longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "bam_tumor_normal_somatic_variant_calling_strelka": "Perform variant calling on a paired tumor normal set of samples using strelka somatic mode.\nf1r2 output of mut"}}, "target": "gatk4/applyvqsr", "target_idx": 0}
{"id": "mod_biohansel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use k-mers to rapidly subtype S. enterica genomes (tools: biohansel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash_gather": "Search a metagenome sourmash signature against one or many reference databases and return the minimum set of g", "gunc_mergecheckm": "Merging of CheckM and GUNC results in one summary table", "bismark_methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "biohansel": "Use k-mers to rapidly subtype S. enterica genomes", "gunc_downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes"}}, "target": "biohansel", "target_idx": 3}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_6_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns are standard for Dual RNA-seq simultaneous host and pathogen transcriptomics input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "noul_executor_support_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_consensus_autocycler_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CONSENSUS_AUTOCYCLER", "modules": ["autocycler/compress", "autocycler/cluster", "autocycler/trim", "autocycler/resolve", "autocycler/combine"], "description": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler"}, "question": {"type": "choice", "instructions": "How should FASTA_CONSENSUS_AUTOCYCLER (autocycler/compress, autocycler/cluster, autocycler/trim, autocycler/resolve, autocycler/combine) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_consensus_autocycler": null, "Local subworkflow FASTA_CONSENSUS_AUTOCYCLER": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_consensus_autocycler", "target_idx": 1}
{"id": "mod_tidk_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search` (tools: tidk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star_align": "Align reads to a reference genome using STAR", "purgedups_histplot": "Plots the read coverage from a purge dups statistics file and cutoffs.", "alignoth": "Creating alignment plots from bam files", "tidk_plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "tidk_plot", "target_idx": 3}
{"id": "field_constraint_fastq_1_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "assay_type": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "data_format": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-taxonomic profiling of complex metagenomic shotgun reads with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_cnvkit_access_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the sequence-accessible coordinates in chromosomes from the given reference genome, output as a BED file. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "rundbcan_database": "command from run_dbcan to prepare the database for dbCAN annotation.", "cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions.", "cnvkit_access": "Calculate the sequence-accessible coordinates in chromosomes from the given reference genome, output as a BED ", "bedtools_jaccard": "Calculate Jaccard statistic b/w two feature files."}}, "target": "cnvkit_access", "target_idx": 3}
{"id": "schema_std_callingcards_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/callingcards", "assay": "callingcards pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/callingcards (A pipeline for processing calling cards data)?", "criteria": {"sample,fastq_1,fastq_2,barcode_details": null, "sample,vcf,tbi": null, "patient,sample,vcf,status,cna": null, "id,fasta,sequence": null}}, "target": "sample,fastq_1,fastq_2,barcode_details", "target_idx": 0}
{"id": "mod_picard_meanqualitybycycle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics about the mean quality by cycle of a paired-end library. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"perbase": null, "custom/clustermetrics": null, "gatk4/collectsvevidence": null, "kmcp/search": null, "picard/meanqualitybycycle": null}}, "target": "picard/meanqualitybycycle", "target_idx": 4}
{"id": "samplesheet_arch_singlecell_parse_splitseq_3_0", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Parse Biosciences Split-seq combinatorial barcoding with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,subpool,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bedtools_split_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SPLIT", "tool": "bedtools/split", "description": "Split BED files into several smaller BED files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SPLIT (Split BED files into several smaller BED files) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_ascat_3", "category": "resource_profiling", "state": {"process": "ASCAT", "tool": "ascat", "description": "copy number profiles of tumour cells."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASCAT (copy number profiles of tumour cells.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "core_tool_samtools_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Coordinate-sorting, indexing, and statistics generation for genome-aligned BAM binary alignment files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bamtools": null, "samtools": null, "sambamba": null, "picard": null, "bedtools": null}}, "target": "samtools", "target_idx": 1}
{"id": "mod_macrel_contigs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provided as contigs) and outputs all the predicted anti-microbial peptides found. (tools: macrel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampir": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ", "integronfinder": "Detect integrons in DNA sequences", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "lofreq/viterbi": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl", "macrel/contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid"}}, "target": "macrel/contigs", "target_idx": 4}
{"id": "samplesheet_arch_metatranscriptome_denovo_1_5", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "template": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 2}
{"id": "schema_std_diseasemodulediscovery_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/diseasemodulediscovery. Description: A pipeline for network-based disease module identification..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/diseasemodulediscovery.", "criteria": {"seeds,network,perturbed_networks": null, "family_id,sample,file_path,hpo_terms,sex": null, "sample,fastq_1,fastq_2,replicate,antibody": null, "sample,fastq_1,fastq_2,umi_barcodes": null}}, "target": "seeds,network,perturbed_networks", "target_idx": 0}
{"id": "resource_bcftools_pluginfilltags_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFILLTAGS", "tool": "bcftools/pluginfilltags", "description": "Compute and fill various INFO tags"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFILLTAGS (Compute and fill various INFO tags) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bamutil_clipoverlap_5", "category": "resource_profiling", "state": {"process": "BAMUTIL_CLIPOVERLAP", "tool": "bamutil/clipoverlap", "description": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_CLIPOVERLAP (clips overlapping read pairs. When two mates overlap, this tool will clip the re) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_channel_collect_operator_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_proteinfamilies_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Generation and updating of protein families. Topics: metagenomics, protein-families. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mag": null, "bactmap": null, "rnavar": null, "proteinfamilies": null, "callingcards": null}}, "target": "proteinfamilies", "target_idx": 3}
{"id": "mod_galah_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster genome FASTA files by average nucleotide identity (tools: galah)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "varlociraptor_preprocess": "Obtains per-sample observations for the actual calling process with varlociraptor calls", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "galah": "Cluster genome FASTA files by average nucleotide identity", "hlala_typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align "}}, "target": "galah", "target_idx": 3}
{"id": "mod_samclip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters SAM/BAM/CRAM files for soft and hard clipped alignments (tools: samclip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamutil_clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo", "samclip": "Filters SAM/BAM/CRAM files for soft and hard clipped alignments", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "picard_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT"}}, "target": "samclip", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_38", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_quant_tximport_summarizedexperiment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedExperiment objects (tools: quant_tximport_summarizedexperiment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/multiqccustombiotype": null, "samtools/consensus": null, "gt/stat": null, "quant_tximport_summarizedexperiment": null, "ctatsplicing/startocancerintrons": null}}, "target": "quant_tximport_summarizedexperiment", "target_idx": 3}
{"id": "resource_bismark_methylationextractor_1", "category": "resource_profiling", "state": {"process": "BISMARK_METHYLATIONEXTRACTOR", "tool": "bismark/methylationextractor", "description": "Extracts methylation information for individual cytosines from alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_METHYLATIONEXTRACTOR (Extracts methylation information for individual cytosines from alignments.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_manta_germline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. (tools: manta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec_freec2bed": null, "gcta_makegrm": null, "hmmcopy_gccounter": null, "controlfreec_freec": null, "manta_germline": null}}, "target": "manta_germline", "target_idx": 4}
{"id": "mod_gatk4_combinegvcfs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine per-sample gVCF files produced by HaplotypeCaller into a multi-sample gVCF file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_combinegvcfs": "Combine per-sample gVCF files produced by HaplotypeCaller into a multi-sample gVCF file", "tiara_tiara": "Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle", "gatk4_reblockgvcf": "Condenses homRef blocks in a single-sample GVCF", "parabricks_genotypegvcf": "NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs", "apbs": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Bol"}}, "target": "gatk4_combinegvcfs", "target_idx": 0}
{"id": "resource_arcashla_extract_4", "category": "resource_profiling", "state": {"process": "ARCASHLA_EXTRACT", "tool": "arcashla/extract", "description": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCASHLA_EXTRACT (Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alterna) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_cobiontid_kmercounter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written with downstream processing with Tensorflow\nor numpy in mind. (tools: kmer-counter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plotsr": "Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes.", "holodeck_eval": "Evaluate alignment accuracy of holodeck-simulated reads", "concoct_concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "genometester4_glistmaker": "Create and count k-mer lists from nucelotide sequences.", "cobiontid_kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written"}}, "target": "cobiontid_kmercounter", "target_idx": 4}
{"id": "mod_bamreadcount_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads. (tools: bamreadcount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "bamreadcount": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencin", "nextgenmap": "Performs fastq alignment to a fasta reference using NextGenMap", "custom/orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom"}}, "target": "bamreadcount", "target_idx": 2}
{"id": "intent_prepare_data_17", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "build_pipeline": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 0}
{"id": "field_constraint_strandedness_1_12", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_4", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_paftools_sam2paf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program to convert bam into paf. (tools: paftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"miniprot_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "paftools_sam2paf": "A program to convert bam into paf.", "seqkit_sliding": "Use seqkit to generate sliding windows of input fasta", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "lissero": "Serogrouping Listeria monocytogenes assemblies"}}, "target": "paftools_sam2paf", "target_idx": 1}
{"id": "resource_bcftools_isec_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ISEC", "tool": "bcftools/isec", "description": "Apply set operations to VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ISEC (Apply set operations to VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "intent_prepare_data_12", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "prepare_data", "target_idx": 2}
{"id": "mod_numorph_resample_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: performs resampling of light-sheet microscopy images (tools: numorph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"numorph/3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "biobambam/bamsormadup": "Parallel sorting and duplicate marking", "cellrangeratac/count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "numorph/resample": "performs resampling of light-sheet microscopy images", "numorph/intensity": "performs shading correction and intensity normalization between tile stacks"}}, "target": "numorph/resample", "target_idx": 3}
{"id": "mod_fastqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run FastQC on sequenced reads (tools: fastqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqc": "Run FastQC on sequenced reads", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "sentieon_staralign": "Align reads to a reference genome using Sentieon STAR", "busco_plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "pypgx_runngspipeline": "PyPGx pharmacogenomics genotyping pipeline for NGS data."}}, "target": "fastqc", "target_idx": 0}
{"id": "mod_centrifuger_centrifuger_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classification of sequencing reads using the Centrifuger tool. (tools: centrifuger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freebayes": "A haplotype-based variant detector", "hificnv": "Copy number variant calling from PacBio HiFi reads", "centrifuger_centrifuger": "Classification of sequencing reads using the Centrifuger tool.", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}}, "target": "centrifuger_centrifuger", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_18", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_popscle_dscpileup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode. (tools: popscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "popscle_dscpileup": "Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode.", "popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "samtools_cramsize": "List CRAM Content-ID and Data-Series sizes"}}, "target": "popscle_dscpileup", "target_idx": 1}
{"id": "samplesheet_arch_mira_influenza_sc2_0_1", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_bam_0_13", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "mod_gt_suffixerator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes enhanced suffix array using GenomeTools gt-suffixerator utility (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "parsesdrf_convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration ", "gt_suffixerator": "Computes enhanced suffix array using GenomeTools gt-suffixerator utility", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "parsnp": "Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection."}}, "target": "gt_suffixerator", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_23", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_fastq_1_0_13", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "mod_deeptools_bamcompare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the log2 ratio, ratio, difference or other operations. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec/assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "deeptools/bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "ascat": "copy number profiles of tumour cells.", "bamclipper": "This module is used to clip primer sequences from your alignments.", "smncopynumbercaller": "tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion "}}, "target": "deeptools/bamcompare", "target_idx": 1}
{"id": "core_tool_star_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Splice-aware alignment of paired-end RNA-seq reads against human genome GRCh38 generating coordinate-sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"salmon": null, "minimap2": null, "bowtie2": null, "bwa_mem": null, "star": null}}, "target": "star", "target_idx": 4}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bwafastalign_index_2", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_INDEX", "tool": "bwafastalign/index", "description": "Create BWA-FASTALIGN index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_INDEX (Create BWA-FASTALIGN index for reference genome) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_high", "target_idx": 2}
{"id": "mod_qualimap_bamqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment data (tools: qualimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qualimap/bamqc": null, "busco/download": null, "ismapper": null, "snpeff/snpeff": null, "busco/generateplot": null}}, "target": "qualimap/bamqc", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_32", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_picard_sortvcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts vcf files (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_sortvcf": null, "bedtools_sort": null, "biscuit_vcf2bed": null, "crisprcleanr_normalize": null, "vireo": null}}, "target": "picard_sortvcf", "target_idx": 0}
{"id": "mod_vcflib_vcfuniq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: List unique genotypes. Like GNU uniq, but for VCF records. Remove records which have the same position, ref, and alt as the previous record. (tools: vcflib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_call": "generate VCF file from a BAM file using various calling methods", "ucsc_wigtobigwig": "Convert ascii format wig file to binary big wig format", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "optitype": "Perform HLA-I typing of sequencing data", "vcflib_vcfuniq": "List unique genotypes. Like GNU uniq, but for VCF records. Remove records which have the same position, ref, a"}}, "target": "vcflib_vcfuniq", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_0_13", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_31", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_biobambam_bammerge_4", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMERGE", "tool": "biobambam/bammerge", "description": "Merge a list of sorted bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMERGE (Merge a list of sorted bam files) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_status_1_6", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "local_subworkflow_prepilluminareads_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPILLUMINAREADS (trimmomatic).", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow PREPILLUMINAREADS": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_47", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_all101_mnaseseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: MNase-seq analysis pipeline using BWA and DANPOS2.. Topics: mnase-seq, nucleosome, nucleosome-maps, nucleosome-positioning. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": null, "pixelator": null, "variantbenchmarking": null, "airrflow": null, "dualrnaseq": null, "readsimulator": null, "smrnaseq": null, "mnaseseq": null}}, "target": "mnaseseq", "target_idx": 7}
{"id": "mod_bwa_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA index for reference genome (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_index": null, "bwa_index": null, "bismark_genomepreparation": null, "odgi_layout": null, "refsolver_identify": null}}, "target": "bwa_index", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_0_1", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_parabricks_deepvariant_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating deepvariant. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ferrohgvs/normalize": null, "parabricks/deepvariant": null, "cache_download_ensemblvep_snpeff": null, "graphtyper/genotype": null, "igvreports": null}}, "target": "parabricks/deepvariant", "target_idx": 1}
{"id": "mod_gatk4_concordance_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate concordance of an input VCF against a validated truth VCF (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "gatk4_concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "pypgx_preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "sourmash_pairwise": "Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch."}}, "target": "gatk4_concordance", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_26", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "field_constraint_expected_cells_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "schema_std_rnaseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnaseq. Description: RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnaseq.", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "fastq_1,fastq_2,group,replicate,control": null, "id,fasta,sequence": null}}, "target": "sample,fastq_1,fastq_2,strandedness,seq_platform", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_8", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "field_constraint_expected_cells_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "mod_hhsuite_hhblits_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast and sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs) (tools: hhsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultraplex": "Ultraplex is an all-in-one software package for processing and demultiplexing fastq files.", "hhsuite_hhblits": "Fast and sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "suppa_diffsplice": "Perform differential splicing analysis using SUPPA.", "hmmer_hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "hhsuite_hhsearch": "Sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)"}}, "target": "hhsuite_hhblits", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Long-read Oxford Nanopore environmental metagenomic sequencing)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Oxford Nanopore environmental metagenomic sequencing with entry step NANOPLOT.", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_1_5", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Tumor-only somatic variant calling without matched normal?", "criteria": {"patient,normal,tumor": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_longraredisease_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders. Topics: nanopore, pacbio. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]"}}, "target": "longraredisease", "target_idx": 2}
{"id": "mod_iphop_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download, extract, and check md5 of iPHoP databases (tools: iphop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_flagstat": "Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "iphop_download": "Download, extract, and check md5 of iPHoP databases", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "pairix": "a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates"}}, "target": "iphop_download", "target_idx": 2}
{"id": "resource_bwa_mem_3", "category": "resource_profiling", "state": {"process": "BWA_MEM", "tool": "bwa/mem", "description": "Performs fastq alignment to a fasta reference using BWA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_MEM (Performs fastq alignment to a fasta reference using BWA) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_high", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_35", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_30", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_4", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_8", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_amulety_antiberty_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety/antiberty": null, "amulety/esm2": null, "goat/taxonsearch": null, "staphopiasccmec": null, "amulety/balmpaired": null}}, "target": "amulety/antiberty", "target_idx": 0}
{"id": "field_constraint_phenotype_2_10", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"format: file-path": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "pipe_all101_drugresponseeval_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for cell-lines. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"callingcards": "A pipeline for processing calling cards data", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]"}}, "target": "drugresponseeval", "target_idx": 8}
{"id": "qc_adapt_pe_illumina_fastqc_1_46", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_annotsv_installannotations_3", "category": "resource_profiling", "state": {"process": "ANNOTSV_INSTALLANNOTATIONS", "tool": "annotsv/installannotations", "description": "Install the AnnotSV annotations"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_INSTALLANNOTATIONS (Install the AnnotSV annotations) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_40", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_hmmer_eslalipid_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellranger/count": null, "hmmer/eslalipid": null, "angsd/realsfs": null, "abra2": null, "ashlar": null}}, "target": "hmmer/eslalipid", "target_idx": 1}
{"id": "mod_custom_addmostsevereconsequence_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate a VEP annotated VCF with the most severe consequence field (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldmason/createdb": "Creates a database for Foldmason.", "custom/addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field", "atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "custom/matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass."}}, "target": "custom/addmostsevereconsequence", "target_idx": 1}
{"id": "mod_samtools_view_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: filter/convert SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "samtools_convert": "convert and then index CRAM -> BAM or BAM -> CRAM file", "samtools_view": "filter/convert SAM/BAM/CRAM file", "hackgap_count": "Fast, JIT-compiled k-mer counter supporting both contiguous and gapped k-mers using multi-way bucketed Cuckoo ", "ucsc_bedtobigbed": "Convert file from bed to bigBed format"}}, "target": "samtools_view", "target_idx": 2}
{"id": "pipe_all101_drugresponseeval_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for testing drug response prediction models in a statistically and biologically sound way.. Topics: cell-lines, cross-validation, deep-learning, drug-response, drug-response-prediction, drugs. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]"}}, "target": "drugresponseeval", "target_idx": 1}
{"id": "noul_modular_subworkflow_composition_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bclconvert_1", "category": "resource_profiling", "state": {"process": "BCLCONVERT", "tool": "bclconvert", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCLCONVERT (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_strandedness_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"pattern: ^[0-9]+$": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "noul_include_modular_process_syntax_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_15", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_nanolyse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DNA contaminant removal using NanoLyse (tools: nanolyse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_removeadapters_merge": "Remove adapters and merge reads based on various module choices", "grabix/check": "Checks if the input file is bgzip compressed or not", "interproscan": "Produces protein annotations and predictions from an amino acids FASTA file", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "nanolyse": "DNA contaminant removal using NanoLyse"}}, "target": "nanolyse", "target_idx": 4}
{"id": "subworkflow_pkg_dia_proteomics_analysis_3", "category": "subworkflow_packaging", "state": {"subworkflow": "DIA_PROTEOMICS_ANALYSIS", "modules": ["diann", "quantmsutils/dianncfg", "quantmsutils/mzmlstatistics", "quantmsutils/diann2mztab"], "description": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,"}, "question": {"type": "choice", "instructions": "How should DIA_PROTEOMICS_ANALYSIS (diann, quantmsutils/dianncfg, quantmsutils/mzmlstatistics, quantmsutils/diann2mztab) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow DIA_PROTEOMICS_ANALYSIS": null, "Use nf-core subworkflow dia_proteomics_analysis": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow dia_proteomics_analysis", "target_idx": 2}
{"id": "mod_checkm_qa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. (tools: checkm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan_cazymeannotation": "CAZyme annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (", "snpsift_annmem": "Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-opt", "checkm_qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "checkv_downloaddatabase": "Construct the database necessary for checkv's quality assessment", "checkm_lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or "}}, "target": "checkm_qa", "target_idx": 2}
{"id": "field_constraint_expected_cells_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "mod_pypgx_preparedepthofcoverage_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare a depth of coverage file for all target genes with SV from BAM files. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx/preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "pypgx/runngspipeline": "PyPGx pharmacogenomics genotyping pipeline for NGS data.", "vclust/align": "The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like", "cnvkit/target": "Transform bait intervals into targets more suitable for CNVkit.", "pypgx/computecontrolstatistics": "Compute summary statistics for control gene from BAM files."}}, "target": "pypgx/preparedepthofcoverage", "target_idx": 0}
{"id": "resource_blobtk_plot_1", "category": "resource_profiling", "state": {"process": "BLOBTK_PLOT", "tool": "blobtk/plot", "description": "Creates differing styles of blobplots depending on provided arguments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_PLOT (Creates differing styles of blobplots depending on provided arguments.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bcftools_view_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_VIEW", "tool": "bcftools/view", "description": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_VIEW (View, subset and filter VCF or BCF files by position and filtering expression. C) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_11", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bedtools_getfasta_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GETFASTA", "tool": "bedtools/getfasta", "description": "extract sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GETFASTA (extract sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_bam_stats_samtools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STATS_SAMTOOLS", "modules": ["samtools/stats", "samtools/idxstats", "samtools/flagstat"], "description": "Produces comprehensive statistics from SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_STATS_SAMTOOLS (samtools/stats, samtools/idxstats, samtools/flagstat) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_STATS_SAMTOOLS": null, "Use nf-core subworkflow bam_stats_samtools": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_stats_samtools", "target_idx": 2}
{"id": "field_constraint_fastq_1_1_13", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "mod_krakenuniq_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download and build (custom) KrakenUniq databases (tools: krakenuniq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbbam_pbmerge": "The pbbam software package provides components to create, query, & edit PacBio BAM files and associated indice", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "krakenuniq_build": "Download and build (custom) KrakenUniq databases", "archive_extract": "Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "krakenuniq_build", "target_idx": 2}
{"id": "samplesheet_arch_taxprofiler_shotgun_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/taxprofiler) for Multi-taxonomic profiling of complex metagenomic shotgun reads. Input files: Short or long reads with run accession and library instrument platform.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/taxprofiler, determine the input samplesheet column structure for: Multi-taxonomic profiling of complex metagenomic shotgun reads.", "criteria": {"sample,bam": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_variantbenchmarking_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/variantbenchmarking. Description: Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/variantbenchmarking.", "criteria": {"id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "id,fasta,query": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "id,test_vcf,test_regions,caller,subsample", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_6", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_ariba_getref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download and prepare database for Ariba analysis (tools: ariba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_seqreformat": "Reformats files with t-coffee", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "scramble_clusteridentifier": "The cluster_identifier tool of Scramble identifies soft clipped clusters", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "ariba_getref": "Download and prepare database for Ariba analysis"}}, "target": "ariba_getref", "target_idx": 4}
{"id": "samplesheet_arch_germline_lane_split_1_3", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "local_subworkflow_irma_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should this step (irma) be packaged: Iterative assembly step for influenza and coronavirus?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow irma": null, "Local subworkflow IRMA": null, "Leave them out": null}}, "target": "Local subworkflow IRMA", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_20", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_18", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_3_2", "category": "samplesheet_schema", "state": {"technology": "Microbial Assembly", "workflow_entry": "FASTQC", "library_inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hybrid bacterial assembly combining short Illumina and long Nanopore reads with entry step FASTQC.", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "field_constraint_sample_1_1", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"format: file-path": null, "enum: [0, 1]": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "noul_channel_collect_operator_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_biobambam_bamsormadup_2", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMSORMADUP", "tool": "biobambam/bamsormadup", "description": "Parallel sorting and duplicate marking"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMSORMADUP (Parallel sorting and duplicate marking) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_pairtools_restrict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assign restriction fragments to pairs (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools/restrict": null, "pairtools/flip": null, "pairtools/sort": null, "paftools/sam2paf": null, "bedtools/genomecov": null}}, "target": "pairtools/restrict", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Long-read Oxford Nanopore environmental metagenomic sequencing)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Long-read Oxford Nanopore environmental metagenomic sequencing.", "criteria": {"sample,fasta": null, "sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "mod_windowmasker_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Masks out highly repetitive DNA sequences with low complexity in a genome (tools: windowmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": null, "amrfinderplus_update": null, "pharmcat_phenotyper": null, "windowmasker_convert": null, "metabuli_build": null}}, "target": "windowmasker_convert", "target_idx": 3}
{"id": "mod_multivcfanalyzer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SNP table generator from GATK UnifiedGenotyper with functionality geared for aDNA (tools: multivcfanalyzer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scvitools_solo": "Detect doublets in single-cell RNA-Seq data", "deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "multivcfanalyzer": "SNP table generator from GATK UnifiedGenotyper with functionality geared for aDNA", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "multivcfanalyzer", "target_idx": 3}
{"id": "mod_homer_groseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.ucsd.edu/homer/ngs/groseq/groseq.html). (tools: homer_groseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star/align": "Align reads to a reference genome using STAR", "cooler/dump": "Dump a cooler’s data to a text stream.", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "homer_groseq": "Basic process of trying to analyze GRO-Seq data with HOMER. From the [GRO-Seq Analysis Tutorial](http://homer.", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate"}}, "target": "homer_groseq", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/taxprofiler --input samplesheet.csv (Assay: Multi-taxonomic profiling of complex metagenomic shotgun reads)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_cutadapt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes adapter sequences from sequencing reads (tools: cutadapt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt_hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "cutadapt": "Removes adapter sequences from sequencing reads", "chopper": "Filter and trim long read data.", "freyja_boot": "Bootstrap sample demixing by resampling each site based on a multinomial distribution of read depth across all", "hifiadapterfilt_downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database"}}, "target": "cutadapt", "target_idx": 1}
{"id": "mod_yara_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a YARA index for a reference genome (tools: yara)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trtools_mergestr": "MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file.", "bowtie2_build": "Builds bowtie index for reference genome", "plink_indep": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other.", "hisat2_build": "Builds HISAT2 index for reference genome", "yara_index": "Builds a YARA index for a reference genome"}}, "target": "yara_index", "target_idx": 4}
{"id": "samplesheet_arch_metagenome_mag_grouped_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Metagenomic MAG assembly with comparative groups)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Metagenomic MAG assembly with comparative groups.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "mod_wipertools_fastqgather_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that merges FASTQ chunks produced by wipertools_fastqscatter (tools: fastqgather)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "sageproteomics/sage": "sage is a search software for proteomics data", "apbs": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Bol", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "wipertools/fastqgather": "A tool of the wipertools suite that merges FASTQ chunks produced by wipertools_fastqscatter"}}, "target": "wipertools/fastqgather", "target_idx": 4}
{"id": "mod_gridss_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmasker. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/annotate": null, "shinyngs/app": null, "gridss/assemble": null, "gridss/extractoverlappingfragments": null, "leehom": null}}, "target": "gridss/annotate", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_22", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_8", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_19", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_controlfreec_makegraph2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot Freec output (tools: controlfreec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvpytor/importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file.", "controlfreec/assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "busco/generateplot": "BUSCO plot generation tool", "controlfreec/makegraph2": "Plot Freec output", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file"}}, "target": "controlfreec/makegraph2", "target_idx": 3}
{"id": "resource_bwa_samse_4", "category": "resource_profiling", "state": {"process": "BWA_SAMSE", "tool": "bwa/samse", "description": "Convert bwa SA coordinate file to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMSE (Convert bwa SA coordinate file to SAM format) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_high", "target_idx": 2}
{"id": "mod_savana_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify and cluster SV breakpoints from long-read alignments. (tools: savana)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "savana/run": "Identify and cluster SV breakpoints from long-read alignments.", "openms/peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)", "seqtk/rename": "Rename sequence names in FASTQ or FASTA files.", "gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont"}}, "target": "savana/run", "target_idx": 1}
{"id": "resource_bioformats2raw_3", "category": "resource_profiling", "state": {"process": "BIOFORMATS2RAW", "tool": "bioformats2raw", "description": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOFORMATS2RAW (Java application to convert image file formats, including .mrxs, to an intermedi) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gatk4_filtermutectcalls_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters the raw output of mutect2, can optionally use outputs of calculatecontamination and learnreadorientationmodel to improve filtering. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mako": "Sort SAM/BAM files by coordinate, queryname or template-coordinate using a fast external merge-sort", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "gatk4_filtermutectcalls": "Filters the raw output of mutect2, can optionally use outputs of calculatecontamination and learnreadorientati", "expansionhunter": "Estimate repeat sizes using NGS data", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "gatk4_filtermutectcalls", "target_idx": 2}
{"id": "mod_vsearch_dereplicate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same length and the same string of nucleotides (case insensitive, T and U are considered the same). (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch_cluster": null, "genomad_endtoend": null, "vsearch_dereplicate": null, "expansionhunterdenovo_merge": null, "vsearch_usearchglobal": null}}, "target": "vsearch_dereplicate", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/eager) for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment. Input files: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/eager, determine the input samplesheet column structure for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment.", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_busco_busco_5", "category": "resource_profiling", "state": {"process": "BUSCO_BUSCO", "tool": "busco/busco", "description": "Benchmarking Universal Single Copy Orthologs"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_BUSCO (Benchmarking Universal Single Copy Orthologs) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_strandedness_1_11", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"type: boolean": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_1_4", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "field_constraint_bai_1_14", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "noul_modular_subworkflow_composition_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bcftools_stats_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_STATS", "tool": "bcftools/stats", "description": "Generates stats from VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_STATS (Generates stats from VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_36", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_46", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_1_4", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_circularmapper_realignsamfile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Realign reads mapped with BWA to elongated reference genome (tools: circularmapper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/align": "Performs alignment of BS-Seq reads using bismark", "ribotricer/prepareorfs": "Accurate detection of short and long active ORFs using Ribo-seq data", "circularmapper/realignsamfile": "Realign reads mapped with BWA to elongated reference genome", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "merqury/hapmers": "A script to generate hap-mer dbs for trios"}}, "target": "circularmapper/realignsamfile", "target_idx": 2}
{"id": "noul_exit_code_137_cause_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "data_format": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bam2fastx_bam2fastq_2", "category": "resource_profiling", "state": {"process": "BAM2FASTX_BAM2FASTQ", "tool": "bam2fastx/bam2fastq", "description": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAM2FASTX_BAM2FASTQ (Conversion of PacBio BAM files into gzipped fastq files, including splitting of ) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_2_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_fibertoolsrs_predictm6a_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict m6A positions using HiFi kinetics data and encode the results in the MM and ML bam tags. Also adds nucleosome (nl, ns) and MTase sensitive patches (al, as) (tools: fibertoolsrs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/eslalimask": "Mask multiple sequence alignments", "seqkit/tab2fx": "Convert tabular format (first two/three columns) to FASTA/Q format.", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "fibertoolsrs/predictm6a": "Predict m6A positions using HiFi kinetics data and encode the results in the MM and ML bam tags. Also adds nuc", "bismark/align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "fibertoolsrs/predictm6a", "target_idx": 3}
{"id": "field_constraint_fastq_1_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_21", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_multiseqdemux_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify singlets, doublets and negative cells from multiplexing experiments. Annotate singlets by tags. (tools: multiseqdemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_splitmerge": "split single end read groups by length and merge paired end reads", "htodemux": "Demultiplex samples based on data from cell hashing.", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "samtools_faidx": "Index FASTA file, and optionally generate a file of chromosome sizes", "multiseqdemux": "Identify singlets, doublets and negative cells from multiplexing experiments. Annotate singlets by tags."}}, "target": "multiseqdemux", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_1_7", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_refsolver_compare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare two sequence dictionaries (headers/references) using ref-solver (tools: refsolver)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"refsolver_compare": "Compare two sequence dictionaries (headers/references) using ref-solver", "meningotype": "Serotyping of Neisseria meningitidis assemblies", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "qualimap_bamqc": "Evaluate alignment data"}}, "target": "refsolver_compare", "target_idx": 0}
{"id": "field_constraint_fastq_2_1_10", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "type: required string": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "mod_bowtie_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create bowtie index for reference genome (tools: bowtie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/somaticfilter": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "bowtie/build": "Create bowtie index for reference genome", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "quilt/quilt2": "QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased re", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali"}}, "target": "bowtie/build", "target_idx": 1}
{"id": "mod_odgi_squeeze_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Squeezes multiple graphs in ODGI format into the same file in ODGI format. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_blastn": null, "odgi_squeeze": null, "odgi_build": null, "gfatools_gfa2fa": null, "hifitrimmer_trim": null}}, "target": "odgi_squeeze", "target_idx": 1}
{"id": "local_subworkflow_positionsofint_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should POSITIONSOFINT (custom/positionsofint) be built?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null, "Local subworkflow POSITIONSOFINT": null, "Leave them out": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_1_1", "category": "samplesheet_schema", "state": "nextflow run custom/mira-nf --input samplesheet.csv (Assay: Custom MIRA-NF Influenza / SC2 pipeline)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_eager_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for adna. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "metapep": "From metagenomes to epitopes and beyond"}}, "target": "eager", "target_idx": 6}
{"id": "mod_custom_pcaclustering_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddings) (tools: scikit-learn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "bedtools/jaccard": "Calculate Jaccard statistic b/w two feature files.", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "quant_tximport_summarizedexperiment": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedEx", "custom/pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi"}}, "target": "custom/pcaclustering", "target_idx": 4}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_6_0", "category": "samplesheet_schema", "state": {"technology": "Microbial Assembly", "workflow_entry": "FASTQC", "library_inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns are standard for Hybrid bacterial assembly combining short Illumina and long Nanopore reads input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 1}
{"id": "noul_confusing_combine_with_mix_semantics_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_annosine_4", "category": "resource_profiling", "state": {"process": "ANNOSINE", "tool": "annosine", "description": "Accelerating de novo SINE annotation in plant and animal genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOSINE (Accelerating de novo SINE annotation in plant and animal genomes) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_6_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "field_constraint_fastq_2_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "type: required string": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "mod_deacon_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create deacon index for reference genome (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon_index": "Create deacon index for reference genome", "fasta_vclust_prefilter_align_cluster": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter\nof candidate sequence pairs with `v", "bcftools_index": "Index VCF tools", "sentieon_tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali"}}, "target": "deacon_index", "target_idx": 0}
{"id": "mod_mindagap_mindagap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes a single panorama image and fills the empty grid lines with neighbour-weighted values. (tools: mindagap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"baysor_run": null, "nanofilt": null, "cnvkit_batch": null, "mindagap_mindagap": null, "basicpy": null}}, "target": "mindagap_mindagap", "target_idx": 3}
{"id": "mod_sourmash_gather_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search a metagenome sourmash signature against one or many reference databases and return the minimum set of genomes that contain the k-mers in the metagenome. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/roh": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered.", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "finaletoolkit/mds": "Comnpute the Motif Diversity Score using normalized Shannon entropy\n(Jiang et al., 2020).", "sourmash/gather": "Search a metagenome sourmash signature against one or many reference databases and return the minimum set of g", "cobiontid/kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written"}}, "target": "sourmash/gather", "target_idx": 3}
{"id": "mod_bioawk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats. (tools: bioawk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"art_illumina": null, "chopper": null, "bracken_bracken": null, "ariba_run": null, "bioawk": null}}, "target": "bioawk", "target_idx": 4}
{"id": "samplesheet_arch_viral_amplicon_artic_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral amplicon sequencing with primers)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_cobs_compactconstruct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a compact bloom filter COBS index (tools: cobs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_index": null, "busco_phylogenomics": null, "biscuit_qc": null, "cobs_compactconstruct": null, "velocyto": null}}, "target": "cobs_compactconstruct", "target_idx": 3}
{"id": "noul_exit_code_137_cause_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_7_0", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "pipe_all101_drop_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hicar": null, "coproid": null, "rnavar": null, "longraredisease": null, "drop": null, "viralmetagenome": null, "callingcards": null, "rnastructurome": null}}, "target": "drop", "target_idx": 4}
{"id": "schema_std_viralrecon_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay": "viralrecon pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/viralrecon (Assembly and intrahost/low-frequency variant calling for vir)?", "criteria": {"sample,fastq_1,fastq_2,barcode": null, "sample_id,img_directory,parameter_file": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,fastq_1,fastq_2,barcode_details": null}}, "target": "sample,fastq_1,fastq_2,barcode", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_0_1", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_samtools_bam2fq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser_diff": "Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff cove", "samtools_bam2fq": "The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format", "samtools_ampliconclip": "Clips read alignments where they match BED file defined regions", "rustqc": "All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, an", "snpsift_annotate": "Annotate a VCF file with another VCF file"}}, "target": "samtools_bam2fq", "target_idx": 1}
{"id": "mod_gatk4_mergemutectstats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges mutect2 stats generated on different intervals/regions (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/mergemutectstats": null, "gatk4/baserecalibrator": null, "centrifuge/centrifuge": null, "gatk4/asereadcounter": null, "anarcii": null}}, "target": "gatk4/mergemutectstats", "target_idx": 0}
{"id": "mod_samtools_bedcov_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: reports coverage over regions in a supplied BED file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/coverage": "produces a histogram or table of coverage per chromosome", "samtools/bedcov": "reports coverage over regions in a supplied BED file", "stacks/refmap": "ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available.", "proteus/readproteingroups": "reads a maxQuant proteinGroups file with Proteus", "samtools/depth": "Computes the depth at each position or region."}}, "target": "samtools/bedcov", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_49", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_remove_rrna_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_REMOVE_RRNA", "modules": ["bowtie2/align", "bowtie2/build", "ribodetector", "samtools/fastq", "samtools/view", "seqkit/replace", "seqkit/stats", "sortmerna"], "description": "Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2"}, "question": {"type": "choice", "instructions": "How should FASTQ_REMOVE_RRNA (bowtie2/align, bowtie2/build, ribodetector, samtools/fastq, samtools/view, seqkit/replace, seqkit/stats, sortmerna) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_REMOVE_RRNA": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_remove_rrna": null}}, "target": "Use nf-core subworkflow fastq_remove_rrna", "target_idx": 3}
{"id": "resource_bakta_bakta_4", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTA", "tool": "bakta/bakta", "description": "Annotation of bacterial genomes (isolates, MAGs) and plasmids"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTA (Annotation of bacterial genomes (isolates, MAGs) and plasmids) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_tidk_search_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Searches a genome for a telomere string such as TTAGGG (tools: tidk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "tidk/search": "Searches a genome for a telomere string such as TTAGGG", "dupradar": "Assessment of duplication rates in RNA-Seq datasets"}}, "target": "tidk/search", "target_idx": 3}
{"id": "noul_dynamic_resource_allocation_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_drop_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "callingcards": "A pipeline for processing calling cards data", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi"}}, "target": "drop", "target_idx": 2}
{"id": "mod_samtools_cramsize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: List CRAM Content-ID and Data-Series sizes (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "samtools_cramsize": "List CRAM Content-ID and Data-Series sizes", "gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "biobambam_bamsormadup": "Parallel sorting and duplicate marking"}}, "target": "samtools_cramsize", "target_idx": 1}
{"id": "mod_sigprofiler_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mutational signature deconvolution of cancer cells (tools: sigprofilermatrixgenerator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsift_annotate": "Annotate a VCF file with another VCF file", "snpsift_dbnsfp": "The dbNSFP is an integrated database of functional predictions from multiple algorithms", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "sigprofiler": "mutational signature deconvolution of cancer cells", "numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit."}}, "target": "sigprofiler", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_6_5", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,matrix,barcodes,features": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "resource_adapterremovalfixprefix_5", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVALFIXPREFIX", "tool": "adapterremovalfixprefix", "description": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with DeDup."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVALFIXPREFIX (Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names a) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_channel_mix_operator_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_bedtools_bamtobed_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_BAMTOBED", "tool": "bedtools/bamtobed", "description": "Converts a bam file to a bed12 file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_BAMTOBED (Converts a bam file to a bed12 file.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_18", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_blast_tblastn_5", "category": "resource_profiling", "state": {"process": "BLAST_TBLASTN", "tool": "blast/tblastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_TBLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedtools_map_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAP", "tool": "bedtools/map", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAP (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_ltrretriever_ltrretriever_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identifies LTR retrotransposons using LTR_retriever (tools: LTR_retriever)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fairy/coverage": null, "ltrretriever/ltrretriever": null, "agat/spfilterfeaturefromkilllist": null, "agat/spflagshortintrons": null, "humann3/regroup": null}}, "target": "ltrretriever/ltrretriever", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_4_0", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted CRAM alignments with companion CRAI indexes?", "criteria": {"sample,cram": null, "sample,cram,crai": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "core_tool_gatk_haplotypecaller_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Germline SNP and Indel variant calling via local de novo haplotype assembly across active genomic regions.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"gatk_haplotypecaller": "Call germline SNPs and indels via local de-novo assembly of haplotypes", "freebayes": "Bayesian genetic variant detector", "mutect2": "Somatic variant caller", "deepvariant": "Deep learning-based variant caller", "strelka2": "Fast variant caller"}}, "target": "gatk_haplotypecaller", "target_idx": 0}
{"id": "pipe_all101_mag_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Assembly and binning of metagenomes. Topics: annotation, assembly, binning, long-read-sequencing, metagenomes, metagenomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "metapep": "From metagenomes to epitopes and beyond", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]"}}, "target": "mag", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Metagenomic MAG assembly with comparative groups", "data_format": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "resource_bio2zarr_vcf2zarrexplode_5", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARREXPLODE", "tool": "bio2zarr/vcf2zarrexplode", "description": "Convert VCF(s) to intermediate columnar format (ICF)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARREXPLODE (Convert VCF(s) to intermediate columnar format (ICF)) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bcftools_index_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_INDEX", "tool": "bcftools/index", "description": "Index VCF tools"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_INDEX (Index VCF tools) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_complexity_filter_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_COMPLEXITY_FILTER", "modules": ["prinseqplusplus", "bbmap/bbduk", "fastp"], "description": "Perform low-complexity filtering of FASTQ reads using a selectable tool."}, "question": {"type": "choice", "instructions": "How should FASTQ_COMPLEXITY_FILTER (prinseqplusplus, bbmap/bbduk, fastp) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_COMPLEXITY_FILTER": null, "Use nf-core subworkflow fastq_complexity_filter": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_complexity_filter", "target_idx": 2}
{"id": "mod_elprep_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge split bam/sam chunks in one file (tools: elprep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamclipper": "This module is used to clip primer sequences from your alignments.", "elprep/merge": "Merge split bam/sam chunks in one file", "ascat": "copy number profiles of tumour cells.", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "custom/multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "elprep/merge", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_37", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_bismark_report_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects bismark alignment reports (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_report": "Collects bismark alignment reports", "paragraph_vcf2paragraph": "Convert a VCF file to a JSON graph", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bismark_methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "rseqc_junctionsaturation": "compare detected splice junctions to reference gene model"}}, "target": "bismark_report", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_1_5", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "template": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "mod_bam_telomere_estimation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter (tools: bam_telomere_estimation)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"telomerehunter": "In silico estimation of telomere content and composition from cancer genomes", "bam_telomere_estimation": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter", "custom/summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a", "bracken/build": "Extends a Kraken2 database to be compatible with Bracken", "methbat/profile": "Runs methbat profile command to create methylation profiles for regions of interest from CpG metrics."}}, "target": "bam_telomere_estimation", "target_idx": 1}
{"id": "mod_slimfastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, efficient, lossless compression of FASTQ files. (tools: slimfastq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"slimfastq": "Fast, efficient, lossless compression of FASTQ files.", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "vclust/align": "The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "samtools/splitheader": "Extract header lines from a SAM/BAM/CRAM file into separate files depending on type"}}, "target": "slimfastq", "target_idx": 0}
{"id": "mod_spaceranger_mkref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command. (tools: spaceranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/datametrics": "Collects multiple quality metrics from a bam file", "bowtie/build": "Create bowtie index for reference genome", "spaceranger/mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command", "gridss/annotate": "Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmaske", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}}, "target": "spaceranger/mkref", "target_idx": 2}
{"id": "noul_channel_join_operator_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_stableexpression_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). The ideal use case is for determining the most suitable RT-qPCR reference genes for a given species.. Topics: expression, housekeeping-genes, qpcr-analysis. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sarek": null, "oncoanalyser": null, "callingcards": null, "cageseq": null, "longraredisease": null, "magmap": null, "ribomsqc": null, "funcprofiler": null, "reportho": null, "stableexpression": null}}, "target": "stableexpression", "target_idx": 9}
{"id": "qc_adapt_ont_ultra_long_2_0", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_juicertools_pre_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a multi-resolution .hic contact matrix for analysis with Juicer (tools: juicertools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_chromap": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with s", "juicertools_pre": "Create a multi-resolution .hic contact matrix for analysis with Juicer", "coptr_estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "metator_pipeline": "Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing an", "cnvpytor_view": "view function to generate vcfs"}}, "target": "juicertools_pre", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_align_bwa_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWA", "modules": ["bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bwa then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWA (bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_bwa": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_BWA": null}}, "target": "Use nf-core subworkflow fastq_align_bwa", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "noul_channel_filter_operator_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_vsearch_usearchglobal_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare target sequences to fasta-formatted query sequences using global pairwise alignment. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": null, "vsearch_cluster": null, "vsearch_usearchglobal": null, "deacon_indexdiff": null, "controlfreec_freec2circos": null}}, "target": "vsearch_usearchglobal", "target_idx": 2}
{"id": "resource_bedtools_flank_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_FLANK", "tool": "bedtools/flank", "description": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_FLANK (Creates two new flanking intervals for each interval in a BED/GFF/VCF file.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_process_conditional_execution_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_ensemblvep_vep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`. (tools: ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsift/annotate": "Annotate a VCF file with another VCF file", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "ensemblvep/vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`.", "wipertools/fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files", "atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files"}}, "target": "ensemblvep/vep", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_15", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "field_constraint_strandedness_1_3", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "mod_bam_ngscheckmate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs. (tools: bam_ngscheckmate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngscheckmate/ncm": "Determining whether sequencing data comes from the same individual by using SNP matching. Designed for humans ", "bam_ngscheckmate": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set o", "ngscheckmate/vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "bcftools/query": "Extracts fields from VCF or BCF files and outputs them in user-defined format.", "cleanifier/download": "Download human reference index"}}, "target": "bam_ngscheckmate", "target_idx": 1}
{"id": "mod_td2_longorfs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Seq transcript assembly (tools: td2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"td2/longorfs": null, "nucmer": null, "gffcompare": null, "agat/sqstatbasic": null, "opt/stat": null}}, "target": "td2/longorfs", "target_idx": 0}
{"id": "samplesheet_arch_faire_seq_chromatin_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "FAIRE-seq / DNAse-seq open chromatin profiling", "data_format": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for FAIRE-seq / DNAse-seq open chromatin profiling with entry step FASTQC.", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_nascent_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for gro-seq analysis? Specific context: Nascent Transcription Processing Pipeline. Topics: gro-seq, nascent, pro-seq, rna, transcription, tss. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]"}}, "target": "nascent", "target_idx": 7}
{"id": "resource_bwa_index_3", "category": "resource_profiling", "state": {"process": "BWA_INDEX", "tool": "bwa/index", "description": "Create BWA index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_INDEX (Create BWA index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_high", "target_idx": 0}
{"id": "schema_std_scnanoseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scnanoseq", "description": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/scnanoseq?", "criteria": {"sample,bam,bai": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,type,level,msfile": null, "sample,fastq,cell_count": null}}, "target": "sample,fastq,cell_count", "target_idx": 3}
{"id": "noul_channel_join_operator_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_fastq_1_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_0_3", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "template": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,peptides_tsv": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_3_1", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Metagenomic MAG assembly with comparative groups with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "samplesheet_arch_germline_lane_split_4_0", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_glimpse_concordance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the high-coverage dataset. (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse/phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods", "glimpse2/chunk": "Defines chunks where to run imputation", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "seroba/run": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the "}}, "target": "glimpse/concordance", "target_idx": 4}
{"id": "resource_bedtools_jaccard_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_JACCARD", "tool": "bedtools/jaccard", "description": "Calculate Jaccard statistic b/w two feature files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_JACCARD (Calculate Jaccard statistic b/w two feature files.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_33", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/hic) for Hi-C chromosome conformation capture mapping. Input files: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/hic, determine the input samplesheet column structure for: Hi-C chromosome conformation capture mapping.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bcftools_query_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_QUERY", "tool": "bcftools/query", "description": "Extracts fields from VCF or BCF files and outputs them in user-defined format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_QUERY (Extracts fields from VCF or BCF files and outputs them in user-defined format.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_5_3", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry).", "criteria": {"sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "local_subworkflow_prepontreads_1_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should this step (porechop, nanoplot) be packaged: Nanopore adapter trimming and read quality visualization?", "criteria": {"Leave them out": null, "Local subworkflow PREPONTREADS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/methylseq) for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq). Input files: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bamstats_generalstats_4", "category": "resource_profiling", "state": {"process": "BAMSTATS_GENERALSTATS", "tool": "bamstats/generalstats", "description": "write your description here"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMSTATS_GENERALSTATS (write your description here) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "intent_build_pipeline_7", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "ask_question": null, "prepare_data": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_fusioncatcher_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build references for fusioncatcher (tools: fusioncatcher)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl_index": "Generate genome indices for segemehl align", "fusioncatcher_build": "Build references for fusioncatcher", "leviosam2_lift": "Converting aligned short and long reads records from one reference to another", "xz_decompress": "Decompresses files with xz.", "segemehl_align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection"}}, "target": "fusioncatcher_build", "target_idx": 1}
{"id": "pipe_all101_dualrnaseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous RNA-seq.. Topics: dualrna-seq, host-pathogen, quantification, readmapping, rna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": null, "proteinannotator": null, "dualrnaseq": null, "scnanoseq": null, "rnasplice": null, "cageseq": null, "metapep": null, "smrnaseq": null, "kmermaid": null, "slamseq": null}}, "target": "dualrnaseq", "target_idx": 2}
{"id": "resource_aardvark_merge_5", "category": "resource_profiling", "state": {"process": "AARDVARK_MERGE", "tool": "aardvark/merge", "description": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_MERGE (A tool to evaluate and merge multiple variant calls into a consensus VCF.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_scvitools_solo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect doublets in single-cell RNA-Seq data (tools: scvitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcflib_vcffilter": "Command line tools for parsing and manipulating VCF files.", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "doubletdetection": "Doublet detection in single-cell RNA-seq data", "hlala_typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "scvitools_solo": "Detect doublets in single-cell RNA-Seq data"}}, "target": "scvitools_solo", "target_idx": 4}
{"id": "noul_channel_factory_inside_process_body_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bioformats2raw_0", "category": "resource_profiling", "state": {"process": "BIOFORMATS2RAW", "tool": "bioformats2raw", "description": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOFORMATS2RAW (Java application to convert image file formats, including .mrxs, to an intermedi) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_7_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_bcftools_pluginvcf2table_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output as one row, with INFO and FORMAT fields as columns. (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/convert": null, "hmmcopy/readcounter": null, "bcftools/pluginvcf2table": null, "bcftools/index": null, "truvari/consistency": null}}, "target": "bcftools/pluginvcf2table", "target_idx": 2}
{"id": "mod_kaiju_kaiju_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of metagenomic sequence data using a protein reference database (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"conifer": null, "ganon/classify": null, "mageck/count": null, "kaiju/kaiju": null, "svtyper/svtypersso": null}}, "target": "kaiju/kaiju", "target_idx": 3}
{"id": "resource_argnorm_0", "category": "resource_profiling", "state": {"process": "ARGNORM", "tool": "argnorm", "description": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARGNORM (Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed b) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_hamronization_amrfinderplus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification. (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "hamronization/fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "hamronization/deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "phenoimager2mc": "Formatting PhenoImager TIFF output files into stacked and normalized OME-TIFF files per cycle, compatible as A"}}, "target": "hamronization/amrfinderplus", "target_idx": 0}
{"id": "mod_rseqc_readdistribution_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate how mapped reads are distributed over genomic features (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc_readdistribution": null, "agat_spextractsequences": null, "alignoth": null, "picard_collectalignmentsummarymetrics": null, "propr_propd": null}}, "target": "rseqc_readdistribution", "target_idx": 0}
{"id": "resource_bracken_bracken_4", "category": "resource_profiling", "state": {"process": "BRACKEN_BRACKEN", "tool": "bracken/bracken", "description": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BRACKEN (Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_suppa_psiperisoform_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate PSI values for transcript isoforms using SUPPA (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kmcp/compute": "Generate k-mers (sketches) from FASTA/Q sequences", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "samtools/dict": "Create a sequence dictionary file from a FASTA file", "suppa/psiperisoform": "Calculate PSI values for transcript isoforms using SUPPA", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "suppa/psiperisoform", "target_idx": 3}
{"id": "samplesheet_arch_ont_direct_rna_se_4_3", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single fastq per sample?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fast5": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "pipe_all101_pathogensurveillance_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Surveillance of pathogens using population genomics and sequencing. Topics: biosurveillance, pathogen-identification. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "pathogensurveillance", "target_idx": 1}
{"id": "field_constraint_sex_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "core_tool_salmon_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Transcript-level abundance estimation and pseudo-alignment directly from raw paired-end RNA-seq FASTQ reads without full genome mapping.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"featurecounts": "Count mapped reads for genomic features", "salmon": "Highly accurate and fast transcript-level quantification from RNA-seq reads", "kallisto": "Near-optimal RNA-seq quantification", "rsem": "Quantification of transcript abundances", "samtools": "Utilities for manipulating SAM/BAM files"}}, "target": "salmon", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "data_format": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Which columns are standard for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking input samplesheet?", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "core_tool_macs2_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Model-based analysis of ChIP-Seq data to identify statistically significant transcription factor binding sites and histone mark enrichment peaks.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"genrich": null, "seacr": null, "homer": null, "epic2": null, "macs2": null}}, "target": "macs2", "target_idx": 4}
{"id": "mod_fasta_consensus_autocycler_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler (tools: fasta_consensus_autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/resolve": null, "varscan/processsomatic": null, "mtnucratio": null, "fasta_consensus_autocycler": null, "autocycler/subsample": null}}, "target": "fasta_consensus_autocycler", "target_idx": 3}
{"id": "mod_plink_gwas_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate GWAS association studies (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output", "plink/gwas": "Generate GWAS association studies", "regenie/step2": "Run REGENIE step 2 association testing from precomputed step 1 predictions", "regenie/runl1": "Finish REGENIE step 1 from split level-0 prediction files", "plink2/indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium"}}, "target": "plink/gwas", "target_idx": 1}
{"id": "noul_named_output_channel_access_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_4_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "HIFIADAPTERFILT", "library_inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single HiFi BAM or FastQ?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_tiddit_cov_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the coverage of different regions from the bam file. (tools: tiddit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiddit_cov": "Computes the coverage of different regions from the bam file.", "scvitools_scar": "Module to use scAR to remove ambient RNA from single-cell RNA-seq data", "bbmap_bbnorm": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result i", "pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "allelecounter": "Generates a count of coverage of alleles"}}, "target": "tiddit_cov", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_1_4", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hi-C chromosome conformation capture mapping?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_sopa_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/sopa. Description: Nextflow version of Sopa - spatial omics pipeline and analysis.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/sopa.", "criteria": {"sample,fastq_1,fastq_2,library_id,lane": null, "sample_id,bam,vcf,library_id,lane": null, "sample,id,data_path,fastq_dir,cytaimage": null, "condition,type,microbiome_path,alleles,weights_path": null}}, "target": "sample,id,data_path,fastq_dir,cytaimage", "target_idx": 2}
{"id": "field_constraint_sex_1_11", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "format: file-path": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_4_1", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single fastq per sample?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fast5": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Multiplexed Oxford Nanopore run with barcode demultiplexing. Input files: Nanopore sequencing run with sample to barcode assignment and flowcell type.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,barcode,flowcell,kit,fastq": null, "sample,bam": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/riboseq) for Ribosome profiling (Ribo-seq) footprint sequencing. Input files: Single-end ribosome protected RNA fragments (RPFs) with strandedness.", "question": {"type": "choice", "instructions": "Which columns are standard for Ribosome profiling (Ribo-seq) footprint sequencing input samplesheet?", "criteria": {"sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,cdna_fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "schema_std_scrnaseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay": "scrnaseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/scrnaseq (Single-cell RNA-Seq pipeline for barcode-based protocols suc)?", "criteria": {"id,fasta,query": null, "sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "seeds,network,perturbed_networks": null}}, "target": "sample,fastq_1,fastq_2,fastq_barcode,expected_cells", "target_idx": 2}
{"id": "mod_ensemblvep_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ensembl Variant Effect Predictor (VEP). The cache downloading options are controlled through `task.ext.args`. (tools: ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "trust4": "Run TRUST4 on RNA-seq data", "annotsv/installannotations": "Install the AnnotSV annotations", "ensemblvep/download": "Ensembl Variant Effect Predictor (VEP). The cache downloading options are controlled through `task.ext.args`.", "cooler/balance": "Run matrix balancing on a cool file"}}, "target": "ensemblvep/download", "target_idx": 3}
{"id": "mod_gatk4_leftalignandtrimvariants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Left align and trim variants using GATK4 LeftAlignAndTrimVariants. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "quartonotebook": "Render a Quarto notebook, including parametrization.", "samtools/ampliconclip": "Clips read alignments where they match BED file defined regions", "gatk4/leftalignandtrimvariants": "Left align and trim variants using GATK4 LeftAlignAndTrimVariants."}}, "target": "gatk4/leftalignandtrimvariants", "target_idx": 4}
{"id": "pipe_all101_denovotranscript_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq. Topics: denovo-assembly, rna-seq, transcriptome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": null, "magmap": null, "seqinspector": null, "kmermaid": null, "denovotranscript": null}}, "target": "denovotranscript", "target_idx": 4}
{"id": "mod_shinyngs_staticdifferential_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make plots for interpretation of differential abundance statistics (tools: shinyngs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shinyngs_staticdifferential": "Make plots for interpretation of differential abundance statistics", "ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "bwameme_mem": "Performs fastq alignment to a fasta reference using BWA-MEME", "mobsuite_recon": "A tool to reconstruct plasmids in bacterial assemblies", "custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "shinyngs_staticdifferential", "target_idx": 0}
{"id": "mod_checkm2_databasedownload_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM2 database download (tools: checkm2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm2/databasedownload": "CheckM2 database download", "krona/ktimporttaxonomy": "KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot.", "checkm2/predict": "CheckM2 bin quality prediction", "checkv/downloaddatabase": "Construct the database necessary for checkv's quality assessment", "checkm/qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or "}}, "target": "checkm2/databasedownload", "target_idx": 0}
{"id": "mod_catpack_addnames_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/summarise": "Summarises results from CAT/BAT/RAT classification steps", "catpack/bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "catpack/addnames": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "vsearch/sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).", "angsd/docounts": "Calculates base frequency statistics across reference positions from BAM."}}, "target": "catpack/addnames", "target_idx": 2}
{"id": "mod_rpbp_extractorfprofiles_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each ORF, walks the spliced exons\nin 3-nucleotide codon steps and counts the P-site positions\n(read 5'-end coordinate plus the length-specific offset selected\nupstream) that fall in each codon. Counts are summed across all read\nlengths that passed the periodicity filter from\n`rpbp/getperiodiclengthsoffsets`.\n\nThe resulting per-ORF vectors are the input to Bayesian translation\nscoring in `rpbp/estimateorfbayesfactors`: a translated ORF should\nshow P-site density concentrated at codon-start positions, while a\nnon-translated region should look flat or noisy. Emitted as a sparse\nmatrix (one row per ORF, columns indexed by codon position). (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "rpbp/estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "jellyfish/count": "Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm", "panacus/visualize": "Create visualizations from a tsv coverage histogram created with panacus.", "rpbp/extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR"}}, "target": "rpbp/extractorfprofiles", "target_idx": 4}
{"id": "mod_kmcp_search_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search sequences against database (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "utils_nfschema_plugin": "Run nf-schema to validate parameters and create a summary of changed parameters", "kmcp_search": "Search sequences against database", "picard_positionbaseddownsamplesam": "Samples a SAM/BAM/CRAM file using flowcell position information for the best approximation of having sequenced"}}, "target": "kmcp_search", "target_idx": 3}
{"id": "resource_bcftools_mpileup_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MPILEUP", "tool": "bcftools/mpileup", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MPILEUP (Compresses VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_26", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_autocycler_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster replicons in compressed assemblies with Autocycler. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/cluster": null, "bismark/report": null, "pbccs": null, "autocycler/resolve": null, "autocycler/subsample": null}}, "target": "autocycler/cluster", "target_idx": 0}
{"id": "mod_biscuit_mergecg_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges methylation information for opposite-strand C's in a CpG context (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_bsconv": null, "sequenzautils_gcwiggle": null, "biscuit_align": null, "rhocall_viz": null, "biscuit_mergecg": null}}, "target": "biscuit_mergecg", "target_idx": 4}
{"id": "mod_gt_gff3validator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GenomeTools gt-gff3validator utility to strictly validate a GFF3 file (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nanoplot": "Run NanoPlot on nanopore-sequenced reads", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "gt/gff3validator": "GenomeTools gt-gff3validator utility to strictly validate a GFF3 file", "hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment"}}, "target": "gt/gff3validator", "target_idx": 3}
{"id": "samplesheet_arch_amplicon_16s_paired_0_0", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fastq_1": null, "sample,otu_table": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_dedup_bwameth_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BWAMETH", "modules": ["bwameth/align", "parabricks/fq2bammeth", "samtools/sort", "samtools/index", "samtools/flagstat", "samtools/stats", "picard/markduplicates"], "description": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BWAMETH (bwameth/align, parabricks/fq2bammeth, samtools/sort, samtools/index, samtools/flagstat, samtools/stats, picard/markduplicates) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_DEDUP_BWAMETH": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_dedup_bwameth": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwameth", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_3_1", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_19", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_cramino_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality assessment of long-read bam files using cramino. (tools: cramino)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "rbt/vcfsplit": "A tool for splitting VCF/BCF files into N equal chunks, including BND support", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "scramble/clusteranalysis": "The Cluster Analysis tool of Scramble analyses and interprets the soft-clipped clusters found by `cluster_iden", "cramino": "Quality assessment of long-read bam files using cramino."}}, "target": "cramino", "target_idx": 4}
{"id": "mod_ngsbits_bedannotategc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates GC content fraction to regions in a BED file. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngsbits/bedannotategc": "Annotates GC content fraction to regions in a BED file.", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "ichorcna/createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti"}}, "target": "ngsbits/bedannotategc", "target_idx": 0}
{"id": "field_constraint_phenotype_1_6", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "mod_fibertoolsrs_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract Fiber-seq information (such as m6A, CpG, nucleosomes, and MSPs) from BAM file into BED file (tools: fibertoolsrs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/genomepreparation": null, "dshbio/filtergff3": null, "ultra/index": null, "fibertoolsrs/extract": null, "bismark/methylationextractor": null}}, "target": "fibertoolsrs/extract", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_1_4", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,bam": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "mod_cooltools_insulation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the diamond insulation scores and call insulating boundaries (tools: cooltools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_plotheatmap": "plots values produced by deeptools_computematrix as a heatmap", "calder2": "Hierarchical Hi-C compartment computation", "cooltools_insulation": "Calculate the diamond insulation scores and call insulating boundaries", "llamacpppython_run": "Python wrapper for running locally-hosted LLM with llama.cpp", "cooler_cload": "Create a cooler from genomic pairs and bins"}}, "target": "cooltools_insulation", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_1_2", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen", "pipeline": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "mod_refsolver_compare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare two sequence dictionaries (headers/references) using ref-solver (tools: refsolver)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/index": null, "deeptools/plotpca": null, "refsolver/compare": null, "bowtie/align": null, "seqkit/sliding": null}}, "target": "refsolver/compare", "target_idx": 2}
{"id": "field_constraint_sample_0_8", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "samplesheet_arch_scrna_10x_v3_0_0", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 2}
{"id": "resource_agat_sqstatbasic_4", "category": "resource_profiling", "state": {"process": "AGAT_SQSTATBASIC", "tool": "agat/sqstatbasic", "description": "Provides basic statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SQSTATBASIC (Provides basic statistics in text format from a GFF/GTF annotation file) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_4_0", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions", "pipeline": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions?", "criteria": {"sample,raw_file,condition": null, "sample,mzml": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "pipe_all101_dualrnaseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous RNA-seq.. Topics: dualrna-seq, host-pathogen, quantification, readmapping, rna-seq. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "callingcards": "A pipeline for processing calling cards data", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]"}}, "target": "dualrnaseq", "target_idx": 1}
{"id": "mod_antismash_antismashdownloaddatabases_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs. (tools: antismash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk/concat": "Concatenate two or more CSV (or TSV) tables into a single table", "antismash/antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "samtools/merge": "Merge BAM or CRAM file", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "antismash/antismashlite": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "antismash/antismashdownloaddatabases", "target_idx": 1}
{"id": "resource_bbmap_bbmerge_2", "category": "resource_profiling", "state": {"process": "BBMAP_BBMERGE", "tool": "bbmap/bbmerge", "description": "Merging overlapping paired reads into a single read."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBMERGE (Merging overlapping paired reads into a single read.) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_vcf_annotation_pipeline_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Downstream functional annotation of pre-called VCF files)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Downstream functional annotation of pre-called VCF files with entry step ENSEMBLVEP.", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,vcf,tbi": null, "sample,bed": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "pipe_all101_genomeqc_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for genome-assembly-evaluation analysis? Specific context: Compare the quality of multiple genomes, along with their annotations.. Topics: genome-assembly-evaluation, genomics, phylogenetic-trees, quality-control. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqsubmit": "nf-core pipeline for data submission to ENA", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet"}}, "target": "genomeqc", "target_idx": 9}
{"id": "mod_ataqv_mkarv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mkarv function of a corresponding ataqv tool (tools: ataqv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ataqv_ataqv": "ataqv function of a corresponding ataqv tool", "qcat": "Demultiplexer for Nanopore samples", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "ataqv_mkarv": "mkarv function of a corresponding ataqv tool", "idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)"}}, "target": "ataqv_mkarv", "target_idx": 3}
{"id": "noul_modular_subworkflow_composition_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay_type": "Long-read Pacific Biosciences HiFi sequencing", "data_format": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Pacific Biosciences HiFi sequencing with entry step HIFIADAPTERFILT.", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_bedtools_slop_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds a specified number of bases in each direction (unique values may be specified for either -l or -r) (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mudskipper/bulk": "Convert genomic BAM/SAM files to transcriptomic BAM/RAD files.", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "multiqc": "Aggregate results from bioinformatics analyses across many samples into a single report", "bedtools/slop": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)"}}, "target": "bedtools/slop", "target_idx": 4}
{"id": "mod_mako_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort SAM/BAM files by coordinate, queryname or template-coordinate using a fast external merge-sort (tools: mako)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "csvtk/sort": "Sort  CSV (or TSV) tables", "ascat": "copy number profiles of tumour cells.", "mako": "Sort SAM/BAM files by coordinate, queryname or template-coordinate using a fast external merge-sort", "pints/caller": "Main caller script for peak calling"}}, "target": "mako", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_18", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "pipe_all101_genomeqc_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Compare the quality of multiple genomes, along with their annotations.. Topics: genome-assembly-evaluation, genomics, phylogenetic-trees, quality-control. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnadnavar": null, "seqinspector": null, "genomeqc": null, "coproid": null, "fastqrepair": null, "mhcquant": null, "createpanelrefs": null, "nanoseq": null, "variantbenchmarking": null, "detaxizer": null}}, "target": "genomeqc", "target_idx": 2}
{"id": "resource_bedtools_intersect_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_INTERSECT", "tool": "bedtools/intersect", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_INTERSECT (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_cnvpytor_importreaddepth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file. (tools: cnvpytor -rd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "cnvpytor/histogram": "calculates read depth histograms", "canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "picard/extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at", "cnvpytor/importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file."}}, "target": "cnvpytor/importreaddepth", "target_idx": 4}
{"id": "pipe_all101_rangeland_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for earth-observation. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]"}}, "target": "rangeland", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_5_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Long-read Oxford Nanopore environmental metagenomic sequencing.", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "samplesheet_arch_singlecell_parse_splitseq_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Parse Biosciences Split-seq combinatorial barcoding. Input files: Combinatorial split-pool barcoded FASTQs with subpool annotations.", "question": {"type": "choice", "instructions": "Which columns are standard for Parse Biosciences Split-seq combinatorial barcoding input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_fastq_1_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "mod_sentieon_tnhaplotyper2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/bwaindex": "Create BWA index for reference genome", "sentieon/tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.", "hmmer/eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie", "sentieon/applyvarcal": "Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the sec", "cellrangeratac/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkref"}}, "target": "sentieon/tnhaplotyper2", "target_idx": 1}
{"id": "field_constraint_status_1_3", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "samplesheet_arch_germline_lane_split_2_5", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_0_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "mod_fastawindows_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly compute statistics over a fasta file in windows. (tools: fastawindows)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "samblaster": "This module combines samtools and samblaster in order to use\nsamblaster capability to filter or tag SAM files,", "fastawindows": "Quickly compute statistics over a fasta file in windows.", "bases2fastq": "Demultiplex Element Biosciences bases files", "abacas": "Contiguate draft genome assembly"}}, "target": "fastawindows", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_1_45", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "schema_std_metapep_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metapep", "assay": "metapep pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/metapep (From metagenomes to epitopes and beyond)?", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,fasta": null, "sample,fastq_1": null, "id,fasta,reference,optional_data,template": null}}, "target": "condition,type,microbiome_path,alleles,weights_path", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_2_0", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_biscuit_biscuitblaster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd_realsfs": null, "biscuit_biscuitblaster": null, "biscuit_bsconv": null, "echtvar_encode": null, "biscuit_epiread": null}}, "target": "biscuit_biscuitblaster", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_0_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cdna_fasta": null, "sample,bam": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_44", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "subworkflow_pkg_bam_stringtie_merge_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STRINGTIE_MERGE", "modules": ["stringtie/stringtie", "stringtie/merge"], "description": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a unified annotation."}, "question": {"type": "choice", "instructions": "How should BAM_STRINGTIE_MERGE (stringtie/stringtie, stringtie/merge) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_stringtie_merge": null, "Leave them out": null, "Local subworkflow BAM_STRINGTIE_MERGE": null}}, "target": "Use nf-core subworkflow bam_stringtie_merge", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_4_1", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed single-end long reads from tiled viral amplicons?", "criteria": {"sample,vcf": null, "sample,fasta": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "pipe_core10_ampliseq_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? 16S and 18S rRNA amplicon sequencing analysis workflow using DADA2, QIIME2, and taxonomic classification.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": null, "sarek": null, "chipseq": null, "viralrecon": null, "taxprofiler": null, "atacseq": null, "mag": null, "rnaseq": null, "eager": null, "scrnaseq": null}}, "target": "ampliseq", "target_idx": 0}
{"id": "mod_bcftools_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts VCF files (tools: sort)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "bcftools/sort": "Sorts VCF files", "bcftools/annotate": "Add or remove annotations."}}, "target": "bcftools/sort", "target_idx": 3}
{"id": "mod_variancepartition_dream_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs a differential expression analysis with dream() from variancePartition R package (tools: dream)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lofreq/viterbi": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl", "variancepartition/dream": "Runs a differential expression analysis with dream() from variancePartition R package", "primerprospector/analyzeprimers": "Score PCR primers for binding to target sequences", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with"}}, "target": "variancepartition/dream", "target_idx": 1}
{"id": "mod_samtools_collatefastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma", "samtools/depth": "Computes the depth at each position or region.", "pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g", "samtools/bedcov": "reports coverage over regions in a supplied BED file", "sequali": "Sequence quality metrics for FASTQ and uBAM files."}}, "target": "samtools/collatefastq", "target_idx": 0}
{"id": "mod_vcf2cytosure_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF with structural variations to CytoSure format (tools: vcf2cytosure)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/call": "generate VCF file from a BAM file using various calling methods", "archive_extract": "Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "vcf2cytosure": "Convert VCF with structural variations to CytoSure format", "rmats/prep": "MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data."}}, "target": "vcf2cytosure", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_41", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_force_tileextent_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute valid tiles for a given datacube definition and area of interest.\nThis list can be used by downstream analysis tasks to limit processing to the area of interest when satellite data covers a larger region. (tools: force)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"force/tileextent": "Compute valid tiles for a given datacube definition and area of interest.\nThis list can be used by downstream ", "grimer": "Generates an interactive HTML dashboard integrating taxonomy,\nannotation, and metadata to detect contamination", "sentieon/bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "gt/gff3validator": "GenomeTools gt-gff3validator utility to strictly validate a GFF3 file", "force/cube": "Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spat"}}, "target": "force/tileextent", "target_idx": 0}
{"id": "mod_fusioncatcher_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build references for fusioncatcher (tools: fusioncatcher)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl/index": "Generate genome indices for segemehl align", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "fusioncatcher/build": "Build references for fusioncatcher", "manta/tumoronly": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile"}}, "target": "fusioncatcher/build", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/metatdenovo --input samplesheet.csv (Assay: Environmental community metatranscriptomics de novo assembly)", "question": {"type": "choice", "instructions": "Which columns are standard for Environmental community metatranscriptomics de novo assembly input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_11", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_13", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_36", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_1_3", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "local_subworkflow_prepilluminareads_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should PREPILLUMINAREADS (trimmomatic) be built?", "criteria": {"Local subworkflow PREPILLUMINAREADS": null, "Use nf-core subworkflow prepilluminareads": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 0}
{"id": "resource_biomformat_convert_0", "category": "resource_profiling", "state": {"process": "BIOMFORMAT_CONVERT", "tool": "biomformat/convert", "description": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HDF5) formats are supported"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOMFORMAT_CONVERT (Convert biom table to different format.\nConversion between text tab-delimited, B) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_6", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_plink_genome_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates identity-by-descent over autosomal SNPs (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proteus/readproteingroups": null, "plink/genome": null, "plink/exclude": null, "elprep/fastatoelfasta": null, "plink/extract": null}}, "target": "plink/genome", "target_idx": 1}
{"id": "pipe_all101_hadge_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for cell-hashing analysis? Specific context: Comprehensive pipeline for donor demultiplexing in single cell. Topics: cell-hashing, deconvolution, demultiplexing, donor-assignment, donor-deconvolution, genetic-demultiplexing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d"}}, "target": "hadge", "target_idx": 5}
{"id": "samplesheet_arch_viral_amplicon_artic_0_4", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "FASTQC", "library_inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral amplicon sequencing with primers?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "16S rRNA / ITS microbiome amplicon profiling", "data_format": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,primer_fwd,primer_rev": null, "sample,otu_table": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bcftools_pluginsplit_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSPLIT", "tool": "bcftools/pluginsplit", "description": "Split VCF by sample, creating single- or multi-sample VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSPLIT (Split VCF by sample, creating single- or multi-sample VCFs.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_48", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_4_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single HiFi BAM or FastQ?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_manta_tumoronly_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. (tools: manta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec/freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "fgumi/duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data", "manta/tumoronly": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "tinc": "TINC is a package to determine the contamination of tumour DNA in a matched normal sample. The approach uses e", "controlfreec/makegraph2": "Plot Freec output"}}, "target": "manta/tumoronly", "target_idx": 2}
{"id": "mod_proseg_proseg_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics. (tools: proseg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "proseg_proseg": "Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics.", "merqury_hapmers": "A script to generate hap-mer dbs for trios", "manta_germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for "}}, "target": "proseg_proseg", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/chipseq --input samplesheet.csv (Assay: ChIP-seq with IP and input control design)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ChIP-seq with IP and input control design with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "field_constraint_strandedness_2_4", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"pattern: ^[0-9]+$": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "subworkflow_pkg_h5ad_removebackground_barcodes_cellbender_anndata_3", "category": "subworkflow_packaging", "state": {"subworkflow": "H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA", "modules": ["cellbender/removebackground", "anndata/barcodes"], "description": "Use cellbender for empty droplet removal"}, "question": {"type": "choice", "instructions": "How should H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA (cellbender/removebackground, anndata/barcodes) be structured in DSL2?", "criteria": {"Use nf-core subworkflow h5ad_removebackground_barcodes_cellbender_anndata": null, "Keep the modules in the main workflow": null, "Local subworkflow H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA": null, "Leave them out": null}}, "target": "Use nf-core subworkflow h5ad_removebackground_barcodes_cellbender_anndata", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_11", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_chewbbaca_allelecall_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine the allelic profiles of a genome using a pre-defined schema (tools: chewbbaca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ichorcna/createpon": null, "cnvpytor/callcnvs": null, "chewbbaca/allelecall": null, "plink/extract": null, "taxpasta/standardise": null}}, "target": "chewbbaca/allelecall", "target_idx": 2}
{"id": "mod_deepvariant_callvariants_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call variants from the examples produced by make_examples (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepvariant_callvariants": "Call variants from the examples produced by make_examples", "tidk_search": "Searches a genome for a telomere string such as TTAGGG", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bcftools_consensus": "Compresses VCF files", "popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s"}}, "target": "deepvariant_callvariants", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/cageseq --input samplesheet.csv (Assay: CAGE-seq 5-prime capped transcript end sequencing)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_rseqc_bamstat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate statistics from a bam file (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc_bamstat": "Generate statistics from a bam file", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "regenie_splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s"}}, "target": "rseqc_bamstat", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_5_5", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: 16S rRNA / ITS microbiome amplicon profiling.", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_leviosam2_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index chain files for lift over (tools: leviosam2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "rasusa": "Randomly subsample sequencing reads to a specified coverage", "leviosam2_lift": "Converting aligned short and long reads records from one reference to another", "leviosam2_index": "Index chain files for lift over", "bcftools_index": "Index VCF tools"}}, "target": "leviosam2_index", "target_idx": 3}
{"id": "samplesheet_arch_bulk_small_rna_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/smrnaseq --input samplesheet.csv (Assay: Small RNA / miRNA sequencing)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "schema_std_seqinspector_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/seqinspector", "assay": "seqinspector pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/seqinspector (Dedicated QC-only pipeline for sequencing data. The pipeline)?", "criteria": {"sample,id,data_path,fastq_dir,cytaimage": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,rundir,tags", "target_idx": 2}
{"id": "mod_finaletoolkit_fraglengthbins_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a binned fragment profile and a fragment distribution histogram (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunc/downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "biobambam/bamsormadup": "Parallel sorting and duplicate marking", "finaletoolkit/fraglengthbins": "Generate a binned fragment profile and a fragment distribution histogram", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast "}}, "target": "finaletoolkit/fraglengthbins", "target_idx": 2}
{"id": "noul_invalid_process_communication_via_globals_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bracken_combinebrackenoutputs_2", "category": "resource_profiling", "state": {"process": "BRACKEN_COMBINEBRACKENOUTPUTS", "tool": "bracken/combinebrackenoutputs", "description": "Combine output of metagenomic samples analyzed by bracken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_COMBINEBRACKENOUTPUTS (Combine output of metagenomic samples analyzed by bracken.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_publishdir_directive_usage_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_35", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "local_subworkflow_checkirma_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should this step (custom/checkirma) be packaged: Custom validation of assembly output?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow checkirma": null, "Leave them out": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "mod_pear_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger. (tools: pear)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gecco/run": "GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomi", "concoct/extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "pear": "PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger.", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "samclip": "Filters SAM/BAM/CRAM files for soft and hard clipped alignments"}}, "target": "pear", "target_idx": 2}
{"id": "local_subworkflow_irma_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should IRMA (irma) be built?", "criteria": {"Use nf-core subworkflow irma": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow IRMA": null}}, "target": "Local subworkflow IRMA", "target_idx": 3}
{"id": "field_constraint_expected_cells_1_1", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pre-aligned BAM variant calling pipeline", "data_format": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pre-aligned BAM variant calling pipeline with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/taxprofiler) for Multi-taxonomic profiling of complex metagenomic shotgun reads. Input files: Short or long reads with run accession and library instrument platform.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-taxonomic profiling of complex metagenomic shotgun reads with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,bam": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_fastk_histex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast K-mer counter for high-fidelity shotgun datasets (tools: fastk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastk_histex": "A fast K-mer counter for high-fidelity shotgun datasets", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "ganon_classify": "Classify FASTQ files against ganon database", "fastk_merge": "A tool to merge FastK histograms"}}, "target": "fastk_histex", "target_idx": 0}
{"id": "mod_ncbigenomedownload_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to quickly download assemblies from NCBI's Assembly database (tools: ncbigenomedownload)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "ncbigenomedownload": "A tool to quickly download assemblies from NCBI's Assembly database", "krona_ktupdatetaxonomy": "KronaTools Update Taxonomy downloads a taxonomy database", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "nucmer": "NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences."}}, "target": "ncbigenomedownload", "target_idx": 1}
{"id": "mod_metaphlan3_metaphlan3_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing data. (tools: metaphlan3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": null, "bracken/combinebrackenoutputs": null, "mcstaging/macsima2mc": null, "fasta_binning_concoct": null, "metaphlan3/metaphlan3": null}}, "target": "metaphlan3/metaphlan3", "target_idx": 4}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_centrifuge_kreport_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates Kraken-style reports from centrifuge out files (tools: centrifuge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge_kreport": null, "centrifuge_centrifuge": null, "limma_differential": null, "plink_hwe": null, "ganon_classify": null}}, "target": "centrifuge_kreport", "target_idx": 0}
{"id": "mod_bedtools_shuffle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a genome file (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_cluster": "Cluster replicons in compressed assemblies with Autocycler.", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bedtools_shuffle": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a gen", "gemmi_cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "bedtools_shuffle", "target_idx": 2}
{"id": "mod_eigenstratdatabasetools_eigenstratsnpcoverage_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provide the SNP coverage of each individual in an eigenstrat formatted dataset. (tools: eigenstratdatabasetools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/coverage": "computes both the depth and breadth of coverage of features in file B on the features in file A", "openmsthirdparty/cometadapter": "Annotates MS/MS spectra using Comet.", "cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "sentieon/dnascope": "DNAscope algorithm performs an improved version of Haplotype variant calling.", "eigenstratdatabasetools/eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset."}}, "target": "eigenstratdatabasetools/eigenstratsnpcoverage", "target_idx": 4}
{"id": "field_constraint_sample_2_10", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"format: file-path": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_tcoffee_consensus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes a consensus alignment using T_COFFEE (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"virusrecom": "Information-theory-based method for recombination detection of viral lineages using weighted information conte", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "gemmi_cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "tcoffee_consensus": "Computes a consensus alignment using T_COFFEE"}}, "target": "tcoffee_consensus", "target_idx": 4}
{"id": "mod_fastqdl_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download FASTQ files from SRA or ENA repositories. (tools: fastqdl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aria2": "CLI Download utility", "fastqdl": "Download FASTQ files from SRA or ENA repositories.", "rseqc/innerdistance": "Calculate inner distance between read pairs.", "rundbcan/easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "blast/updateblastdb": "Downloads a BLAST database from NCBI"}}, "target": "fastqdl", "target_idx": 1}
{"id": "schema_std_pairgenomealign_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pairgenomealign. Description: Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pairgenomealign.", "criteria": {"sample,fastq,cell_count": null, "sample,fasta": null, "id,fasta,query": null, "vcf,fasta,genome,site,source": null}}, "target": "sample,fasta", "target_idx": 1}
{"id": "mod_tcoffee_consensus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes a consensus alignment using T_COFFEE (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "hhsuite/hhsearch": "Sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "tcoffee/consensus": "Computes a consensus alignment using T_COFFEE", "umicollapse": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "tcoffee/consensus", "target_idx": 2}
{"id": "pipe_all101_pixelator_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB). Topics: molecular-pixelation, pixelator, pixelgen-technologies, proteins, single-cell, single-cell-omics. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]"}}, "target": "pixelator", "target_idx": 4}
{"id": "samplesheet_arch_cutandrun_pe_4_3", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "template": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end low-input fragment FASTQs with target antibody and IgG negative control?", "criteria": {"sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,fastq_1,fastq_2": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_7_0", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "mod_gfatools_gfa2fa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts GFA or rGFA files to FASTA (tools: gfatools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "mirtop/counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns ", "gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA", "dshbio/exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "gfatools/stat": "Summary statistics for GFA files"}}, "target": "gfatools/gfa2fa", "target_idx": 2}
{"id": "pipe_all101_cutandrun_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis.. Topics: cutandrun, cutandrun-seq, cutandtag, cutandtag-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phaseimpute": null, "metatdenovo": null, "readsimulator": null, "callingcards": null, "chipseq": null, "taxprofiler": null, "cutandrun": null, "scnanoseq": null, "atacseq": null, "demo": null}}, "target": "cutandrun", "target_idx": 6}
{"id": "intent_build_pipeline_11", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "ask_question": null, "debug_error": null, "prepare_data": null}}, "target": "build_pipeline", "target_idx": 0}
{"id": "local_subworkflow_positionsofint_2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for POSITIONSOFINT (custom/positionsofint).", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow positionsofint": null, "Local subworkflow POSITIONSOFINT": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnafusion) for RNA gene fusion detection (Arriba, STAR-Fusion). Input files: Paired-end oncology RNA-seq reads for chimeric transcript discovery.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fusion_bed": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_5_2", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Standard Paired-end Whole Genome Sequencing (WGS).", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_gvcftools_extractvariants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes all non-variant blocks from a gVCF file to produce a smaller variant-only VCF file. (tools: gvcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "gvcftools/extractvariants": "Removes all non-variant blocks from a gVCF file to produce a smaller variant-only VCF file.", "gatk4/combinegvcfs": "Combine per-sample gVCF files produced by HaplotypeCaller into a multi-sample gVCF file", "glnexus": "merge gVCF files and perform joint variant calling", "malt/build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h"}}, "target": "gvcftools/extractvariants", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_40", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_6_0", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "NANOPLOT", "library_inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Oxford Nanopore environmental metagenomic sequencing input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "mod_tidk_search_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Searches a genome for a telomere string such as TTAGGG (tools: tidk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "tidk_search": "Searches a genome for a telomere string such as TTAGGG", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "odgi_squeeze": "Squeezes multiple graphs in ODGI format into the same file in ODGI format.", "slimfastq": "Fast, efficient, lossless compression of FASTQ files."}}, "target": "tidk_search", "target_idx": 1}
{"id": "core_tool_interproscan_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Scan protein and nucleotide sequences against multiple member databases to identify structural domains, functional sites, and protein families.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"hmmer": "HMM protein search", "eggnog": "Orthology mapper", "interproscan": "Scans protein sequences against InterPro member databases (Pfam, PRINTS, PROSITE)", "diamond": "Fast protein aligner", "blastp": "Protein blast"}}, "target": "interproscan", "target_idx": 2}
{"id": "resource_arriba_arriba_1", "category": "resource_profiling", "state": {"process": "ARRIBA_ARRIBA", "tool": "arriba/arriba", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_ARRIBA (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_22", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_methylseq_bisulfite_2_5", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_variantprioritization_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/variantprioritization", "assay": "variantprioritization pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/variantprioritization (Bioinformatics analysis pipeline for the functional annotati)?", "criteria": {"sample,bam,bai": null, "sample,alleles,mhc_class,filename": null, "patient,sample,vcf,status,cna": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "patient,sample,vcf,status,cna", "target_idx": 2}
{"id": "intent_prepare_data_18", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "prepare_data", "target_idx": 1}
{"id": "mod_cdhit_cdhitest_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster nucleotide sequences using sequence similarity (tools: cdhit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity", "paraclu": "Paraclu finds clusters in data attached to sequences.", "mobsuite_recon": "A tool to reconstruct plasmids in bacterial assemblies", "msisensor_msi": "Evaluate microsattelite instability (MSI) using paired tumor-normal sequencing data", "tmb_pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool."}}, "target": "cdhit_cdhitest", "target_idx": 0}
{"id": "mod_samtools_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leafcutter/differentialsplicing": "Perform differential splicing analysis to identify junctions with significant changes in splicing between cond", "samtools/sort": "Sort SAM/BAM/CRAM file", "somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "csvtk/sort": "Sort  CSV (or TSV) tables", "bedtools/sort": "Sorts a feature file by chromosome and other criteria."}}, "target": "samtools/sort", "target_idx": 1}
{"id": "resource_agat_sqstatbasic_1", "category": "resource_profiling", "state": {"process": "AGAT_SQSTATBASIC", "tool": "agat/sqstatbasic", "description": "Provides basic statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SQSTATBASIC (Provides basic statistics in text format from a GFF/GTF annotation file) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_phenotype_1_3", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_0_0", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "mod_sentieon_rsemcalculateexpression_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate expression with RSEM (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "bam_telomere_estimation": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter", "sentieon_rsemcalculateexpression": "Calculate expression with RSEM", "tximeta_tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages", "utils_references": "Functionality for dealing with references that may be useful for any Nextflow pipeline"}}, "target": "sentieon_rsemcalculateexpression", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_2_5", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fast5": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_sushie_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to perform multi-ancestry SNP fine-mapping on molecular data (tools: sushie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/gwas": "Generate GWAS association studies", "ldak/kvikstep1": "Run LDAK-KVIK step 1 to fit the genome-wide model and emit the minimal prediction artifact tuple consumed by l", "seqtk/subseq": "Select only sequences that match the filtering condition", "umitools/extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "sushie": "Software to perform multi-ancestry SNP fine-mapping on molecular data"}}, "target": "sushie", "target_idx": 4}
{"id": "noul_single_hyphen_cli_params_error_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_fastq_1_0_3", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "field_constraint_bai_0_1", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_49", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "schema_std_airrflow_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/airrflow", "assay": "airrflow pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/airrflow (B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR))?", "criteria": {"sample,fastq_1,fastq_2,genome": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2,group": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "sample_id,subject_id,species,pcr_target_locus,tissue", "target_idx": 3}
{"id": "noul_module_metadata_propagation_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "local_subworkflow_preparereports_2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPAREREPORTS (custom/preparereports, multiqc).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPAREREPORTS": null, "Use nf-core subworkflow preparereports": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 2}
{"id": "mod_opt_flip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse complementing them (tools: opt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_annotate_ensemblvep_snpeff": "Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkf", "opt_flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple", "opt_track": "track aligns query probe sequences to any target transcriptome", "td2_longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "ribotish_quality": "Quality control of riboseq bam data"}}, "target": "opt_flip", "target_idx": 1}
{"id": "mod_portello_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transfer HiFi read mappings from their own assembly contigs to a standard reference (tools: portello)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "portello": "Transfer HiFi read mappings from their own assembly contigs to a standard reference", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "smoothxg": "Linearize and simplify variation graph in GFA format using blocked partial order alignment", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "portello", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_34", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_all101_proteinfold_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for alphafold2 analysis? Specific context: Protein 3D structure prediction pipeline. Topics: alphafold2, colabfold, esmfold, protein-fold-prediction, protein-folding, protein-sequences. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "seqsubmit": "nf-core pipeline for data submission to ENA", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]"}}, "target": "proteinfold", "target_idx": 2}
{"id": "mod_raw2ometiff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: raw2ometiff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bftools_showinf": "Extract OME xml data from OME-tif", "raw2ometiff": "write your description here", "bam_create_som_pon_gatk": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a geno", "humann3_regroup": "Regrouping genes to other functional categories", "deepcell_mesmer": "Deepcell/mesmer segmentation for whole-cell"}}, "target": "raw2ometiff", "target_idx": 1}
{"id": "resource_bismark_summary_1", "category": "resource_profiling", "state": {"process": "BISMARK_SUMMARY", "tool": "bismark/summary", "description": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_SUMMARY (Uses Bismark report files of several samples in a run folder to generate a graph) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_index_bismark_bwameth_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_BISMARK_BWAMETH", "modules": ["untar", "gunzip", "bismark/genomepreparation", "bwameth/index", "samtools/faidx"], "description": "Generate index files from reference fasta for bismark and bwameth"}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_BISMARK_BWAMETH (untar, gunzip, bismark/genomepreparation, bwameth/index, samtools/faidx) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_index_bismark_bwameth": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_INDEX_BISMARK_BWAMETH": null}}, "target": "Use nf-core subworkflow fasta_index_bismark_bwameth", "target_idx": 0}
{"id": "mod_srst2_srst2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLST database and/or a database of gene sequences (e.g. resistance genes, virulence genes, etc)\nand report the presence of STs and/or reference genes. (tools: srst2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"srst2/srst2": "Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLS", "last/train": "Find suitable score parameters for sequence alignment", "nanomonsv/parse": "Parse all the supporting reads of putative somatic SVs using nanomonsv.\nAfter successful completion, you will ", "mobsuite/typer": "Bacterial plasmid typing and mobility prediction", "seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA"}}, "target": "srst2/srst2", "target_idx": 0}
{"id": "pipe_all101_detaxizer_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.. Topics: de-identification, decontamination, edna, fastq, filter, long-reads. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom"}}, "target": "detaxizer", "target_idx": 7}
{"id": "qc_adapt_ffpe_wes_0_18", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_22", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "pipe_all101_demultiplex_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for bases2fastq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "callingcards": "A pipeline for processing calling cards data", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "demultiplex", "target_idx": 8}
{"id": "field_constraint_sample_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"enum: [0, 1]": null, "format: file-path": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_2_5", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_pediatric_trio_somatic_6_4", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) input samplesheet?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Long-read Oxford Nanopore environmental metagenomic sequencing)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pre-aligned BAM variant calling pipeline)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "resource_bismark_deduplicate_0", "category": "resource_profiling", "state": {"process": "BISMARK_DEDUPLICATE", "tool": "bismark/deduplicate", "description": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_DEDUPLICATE (Removes alignments to the same position in the genome\nfrom the Bismark mapping o) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_fastq_download_prefetch_fasterqdump_sratools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA). (tools: fastq_download_prefetch_fasterqdump_sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA.", "entrezdirect_esearch": "Searches a term in a public NCBI database", "fastq_download_prefetch_fasterqdump_sratools": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA).", "gatk4_variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo", "rgi_bwt": "Predict antibiotic resistance from protein or nucleotide data"}}, "target": "fastq_download_prefetch_fasterqdump_sratools", "target_idx": 2}
{"id": "field_constraint_strandedness_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null, "pattern: ^[0-9]+$": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "mod_hmmer_hmmemit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: emit sequences from a profile HMM (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "hmmer/hmmemit": "emit sequences from a profile HMM", "hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "hmmer/hmmfetch": "extract hmm from hmm database file or create index for hmm database", "emboss/seqret": "Reads in one or more sequences, converts, filters, or transforms them and writes them out again"}}, "target": "hmmer/hmmemit", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/chipseq) for ChIP-seq with IP and input control design. Input files: Paired-end FASTQ reads for immunoprecipitation and input chromatin.", "question": {"type": "choice", "instructions": "Which columns are standard for ChIP-seq with IP and input control design input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 0}
{"id": "mod_picard_extractfingerprint_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at the fingerprinting sites. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at", "nextgenmap": "Performs fastq alignment to a fasta reference using NextGenMap", "picard_filtersamreads": "Filters SAM/BAM files to include/exclude either aligned/unaligned reads or based on a read list", "samplesheetparser_diff": "Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff cove", "picard_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r"}}, "target": "picard_extractfingerprint", "target_idx": 0}
{"id": "mod_crabz_compress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compress files with crabz (tools: crabz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crabz/compress": "Compress files with crabz", "pypgx/createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "grabix/check": "Checks if the input file is bgzip compressed or not", "samtools/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "syri": "Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearran"}}, "target": "crabz/compress", "target_idx": 0}
{"id": "noul_retry_errorstrategy_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_build_pipeline_3", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "debug_error": null, "ask_question": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_1_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_4_0", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "noul_channel_mix_operator_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_pbmm2_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Alignment with PacBio's minimap2 frontend (tools: pbmm2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "fgumi_sort": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate,\nqueryname, and template-coor", "picard_setnmmdanduqtags": "This tool takes in a coordinate-sorted SAM or BAM and calculatesthe NM, MD, and UQ tags by comparing with the ", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "pbmm2_align": "Alignment with PacBio's minimap2 frontend"}}, "target": "pbmm2_align", "target_idx": 4}
{"id": "samplesheet_arch_cancer_longitudinal_2_4", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_agat_convertbed2gff_5", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTBED2GFF", "tool": "agat/convertbed2gff", "description": "Takes a bed12 file and converts to a GFF3 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTBED2GFF (Takes a bed12 file and converts to a GFF3 file) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_hgtseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline to investigate horizontal gene transfer from NGS data. Topics: bwa-mem, bwa-mem2, fastqc, genomics-visualization, ggbio, horizontal-gene-transfer. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet"}}, "target": "hgtseq", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Long-read Oxford Nanopore environmental metagenomic sequencing. Input files: High molecular weight environmental metagenomic long reads per sampling site.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Long-read Oxford Nanopore environmental metagenomic sequencing.", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_impute_beagle5_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_BEAGLE5", "modules": ["beagle5/beagle", "bcftools/index", "bcftools/view", "glimpse2/ligate"], "description": "Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_BEAGLE5 (beagle5/beagle, bcftools/index, bcftools/view, glimpse2/ligate) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_impute_beagle5": null, "Leave them out": null, "Local subworkflow VCF_IMPUTE_BEAGLE5": null}}, "target": "Use nf-core subworkflow vcf_impute_beagle5", "target_idx": 1}
{"id": "schema_std_epitopeprediction_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/epitopeprediction", "assay": "epitopeprediction pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/epitopeprediction (A bioinformatics best-practice analysis pipeline for epitope)?", "criteria": {"sample,id,data_path,fastq_dir,cytaimage": null, "sample,bam,bai,cram,crai": null, "sample_id,name,description,path,path_2": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,alleles,mhc_class,filename", "target_idx": 3}
{"id": "mod_ltrharvest_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts LTR retrotransposons using the parallel version of GenomeTools gt-ltrharvest\nutility included in the EDTA toolchain (tools: LTR_HARVEST_parallel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ltrharvest": "Predicts LTR retrotransposons using the parallel version of GenomeTools gt-ltrharvest\nutility included in the ", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "mmseqs/linclust": "Cluster sequences in linear time using MMSeqs2 linclust.", "svtk/vcf2bed": "Converts VCFs containing structural variants to BED format", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "ltrharvest", "target_idx": 0}
{"id": "mod_rundbcan_easycgc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZymes) from genomic data using the dbCAN annotation tool. (tools: dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan/cazymeannotation": "CAZyme annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo", "cnvpytor/partition": "Calculate segmentation for specified bin size (multiple bin sizes separate by space)", "rundbcan/easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt"}}, "target": "rundbcan/easycgc", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Longitudinal cancer monitoring across multiple timepoints)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_41", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_4_3", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end Tn5 transposed FASTQs across conditions and replicates?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "mod_mako_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort SAM/BAM files by coordinate, queryname or template-coordinate using a fast external merge-sort (tools: mako)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metaphlan_makedb": "Build MetaPhlAn database for taxonomic profiling.", "crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs", "lofreq_call": "Lofreq subcommand to call low frequency variants from alignments", "mako": "Sort SAM/BAM files by coordinate, queryname or template-coordinate using a fast external merge-sort", "biobambam_bamsormadup": "Parallel sorting and duplicate marking"}}, "target": "mako", "target_idx": 3}
{"id": "schema_std_pacvar_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pacvar. Description: Longread PacBio sequencing processing for WGS and PureTarget.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pacvar.", "criteria": {"sample,fastq_1,strandedness": null, "id,fasta,sequence": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "sample,bam,pbi,fail,repeat_id", "target_idx": 3}
{"id": "resource_ale_0", "category": "resource_profiling", "state": {"process": "ALE", "tool": "ale", "description": "ALE: assembly likelihood estimator."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALE (ALE: assembly likelihood estimator.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_bam_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_bracken_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2_BRACKEN", "modules": ["kraken2/add", "kraken2/build", "bracken/build"], "description": "KRAKEN2 and BRACKEN build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2_BRACKEN (kraken2/add, kraken2/build, bracken/build) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_BUILD_ADD_KRAKEN2_BRACKEN": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_build_add_kraken2_bracken": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2_bracken", "target_idx": 2}
{"id": "mod_seqcluster_collapse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file. (tools: seqcluster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqcluster/collapse": "Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file.", "isoseq/cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences", "deepvariant/rundeepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "mirtrace/qc": "A tool for quality control and tracing taxonomic origins of microRNA sequencing data", "rclone/checksum": "Check files in a destination path against a checksum SUM file"}}, "target": "seqcluster/collapse", "target_idx": 0}
{"id": "mod_odgi_view_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Project a graph into other formats. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi_draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "odgi_view": "Project a graph into other formats.", "foldseek_easysearch": "Search for protein structural hits against a foldseek database of protein structures", "odgi_layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "ea-utils_gtf2bed": "Convert a GTF/GFF annotation file to BED12 format"}}, "target": "odgi_view", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_14", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_gatk4_germlinecnvcaller_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPloidy. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "bedtools/map": "Allows one to screen for overlaps between two sets of genomic features.", "xeniumranger/resegment": "The xeniumranger resegment module allows you to generate a new segmentation of the morphology image space by r", "gatk4/germlinecnvcaller": "Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPlo", "gatk4/cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r"}}, "target": "gatk4/germlinecnvcaller", "target_idx": 3}
{"id": "samplesheet_arch_ont_direct_rna_se_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Single-end Oxford Nanopore direct RNA", "data_format": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fast5": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_38", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "noul_channel_join_operator_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_shortreads_preprocess_qc_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SHORTREADS_PREPROCESS_QC", "modules": ["fastq_qc_stats", "fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp", "fastq_preprocess_seqkit", "fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup", "umitools/extract", "fastq_removeadapters_merge", "trimmomatic", "cutadapt", "trimgalore", "bbmap/bbduk", "leehom", "fastp", "adapterremoval", "cat/fastq", "fastq_complexity_filter", "prinseqplusplus", "bbmap/clumpify", "fastq_decontaminate_deacon_hostile", "fastq_index_filter_deacon", "fastq_fetch_clean_hostile", "hostile/fetch", "hostile/clean", "bowtie2/build", "deacon/filter", "deacon/index"], "description": "Quality check and preprocessing subworkflow of Illumina short reads"}, "question": {"type": "choice", "instructions": "How should FASTQ_SHORTREADS_PREPROCESS_QC (fastq_qc_stats, fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp, fastq_preprocess_seqkit, fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup, umitools/extract, fastq_removeadapters_merge, trimmomatic, cutadapt, trimgalore, bbmap/bbduk, leehom, fastp, adapterremoval, cat/fastq, fastq_complexity_filter, prinseqplusplus, bbmap/clumpify, fastq_decontaminate_deacon_hostile, fastq_index_filter_deacon, fastq_fetch_clean_hostile, hostile/fetch, hostile/clean, bowtie2/build, deacon/filter, deacon/index) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_SHORTREADS_PREPROCESS_QC": null, "Use nf-core subworkflow fastq_shortreads_preprocess_qc": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_shortreads_preprocess_qc", "target_idx": 2}
{"id": "mod_varlociraptor_preprocess_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Obtains per-sample observations for the actual calling process with varlociraptor calls (tools: varlociraptor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"varlociraptor_preprocess": null, "tiddit_cov": null, "bedgovcf": null, "bcftools_consensus": null, "freyja_boot": null}}, "target": "varlociraptor_preprocess", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_6", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_diann_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary analysis, empirical library assembly, individual analysis, and final quantification (tools: diann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtyper_svtyper": "SVTyper performs breakpoint genotyping of structural variants (SVs) using whole genome sequencing data", "maxquant_lfq": "Run standard proteomics data analysis with MaxQuant, mostly dedicated to label-free. Paths to fasta and raw fi", "elprep_fastatoelfasta": "Convert a file in FASTA format to the ELFASTA format", "diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "diamond_deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust"}}, "target": "diann", "target_idx": 3}
{"id": "mod_toulligqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A post sequencing QC tool for Oxford Nanopore sequencers (tools: toulligqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "toulligqc": "A post sequencing QC tool for Oxford Nanopore sequencers", "freyja_update": "downloads new versions of the curated SARS-CoV-2 lineage file and barcodes", "msisensor_msi": "Evaluate microsattelite instability (MSI) using paired tumor-normal sequencing data", "busco_busco": "Benchmarking Universal Single Copy Orthologs"}}, "target": "toulligqc", "target_idx": 1}
{"id": "mod_fungtion_downloadmodels_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads the pretrained ESM-1b weights (esm1b_t33_650M_UR50S.pt) that fungtion\nuses for fungal effector prediction into a local models/ directory via\n`fungtion setup-models`. The downloaded directory is used as input to the\nFUNGTION_FUNGTION prediction module. (tools: fungtion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "paraphase": "HiFi-based caller for highly homologous genes", "variancepartition/dream": "Runs a differential expression analysis with dream() from variancePartition R package", "cdhit/cdhit": "Cluster protein sequences using sequence similarity", "fungtion/downloadmodels": "Downloads the pretrained ESM-1b weights (esm1b_t33_650M_UR50S.pt) that fungtion\nuses for fungal effector predi"}}, "target": "fungtion/downloadmodels", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/pacvar --input samplesheet.csv (Assay: PacBio HiFi unaligned BAM variant calling)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "mod_tif_registration_stainwarpy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy (tools: tif_registration_stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pcne": "Estimates plasmid copy number from assembled genome", "tif_registration_stainwarpy": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy", "crabs/import": "In-house generated or curated data can be imported into CRABS.", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "stainwarpy/transformsegmask": "Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy"}}, "target": "tif_registration_stainwarpy", "target_idx": 1}
{"id": "schema_std_multiplesequencealign_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/multiplesequencealign. Description: A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/multiplesequencealign.", "criteria": {"sample,tools,file,index": null, "id,fasta": null, "id,fasta,reference,optional_data,template": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null}}, "target": "id,fasta,reference,optional_data,template", "target_idx": 2}
{"id": "mod_vg_construct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Constructs a graph from a reference and variant calls or a multiple sequence alignment file (tools: vg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cobrameta": "A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining o", "vg_construct": "Constructs a graph from a reference and variant calls or a multiple sequence alignment file", "gfatools_stat": "Summary statistics for GFA files", "gridss_somaticfilter": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "magus_guidetree": "Multiple Sequence Alignment using Graph Clustering"}}, "target": "vg_construct", "target_idx": 1}
{"id": "mod_vireo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use vireo to perform donor deconvolution for multiplexed scRNA-seq data (tools: vireo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx_computecontrolstatistics": "Compute summary statistics for control gene from BAM files.", "megan_rma2info": "Analyses an RMA file and exports information in text format", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples).", "ngscheckmate_vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "vireo": "Use vireo to perform donor deconvolution for multiplexed scRNA-seq data"}}, "target": "vireo", "target_idx": 4}
{"id": "intent_prepare_data_0", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "prepare_data", "target_idx": 2}
{"id": "mod_chromap_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexes a fasta reference genome ready for chromatin profiling. (tools: chromap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rtgtools/format": null, "eido/convert": null, "bowtie/build": null, "bbmap/index": null, "chromap/index": null}}, "target": "chromap/index", "target_idx": 4}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_snapaligner_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a SNAP index for reference genome (tools: snapaligner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "pangolin_run": "Phylogenetic Assignment of Named Global Outbreak LINeages", "bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "snapaligner_index": "Create a SNAP index for reference genome", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "snapaligner_index", "target_idx": 3}
{"id": "pipe_all101_circdna_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for ampliconarchitect analysis? Specific context: Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that were generated from cancer and other eukaryotic cells.. Topics: ampliconarchitect, ampliconsuite, circle-seq, circular, dna, eccdna. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we"}}, "target": "circdna", "target_idx": 9}
{"id": "mod_bedtools_getfasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: extract sequences in a FASTA file based on intervals defined in a feature file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "bedtools/getfasta": "extract sequences in a FASTA file based on intervals defined in a feature file.", "gget/gget": "gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic da", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "bedtools/intersect": "Allows one to screen for overlaps between two sets of genomic features."}}, "target": "bedtools/getfasta", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_4_2", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: BGZF-compressed VCF files with companion Tabix index files?", "criteria": {"sample,vcf": null, "sample,vcf,tbi": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_3", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_rnaquast_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assess the quality of an RNAseq assembly with or without a reference genome (tools: rnaquast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "skesa": "Assemble microbial genomes from short-read FASTQ files into contigs in FASTA format using SKESA.", "gcta_grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`"}}, "target": "rnaquast", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_49", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_5", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_3_1", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "template": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Custom MIRA-NF Influenza / SC2 pipeline with entry step INPUT_CHECK.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Tumor-only somatic variant calling without matched normal", "data_format": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Tumor-only somatic variant calling without matched normal with entry step FASTQC.", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_channel_operator_map_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "assay_type": "Ribosome profiling (Ribo-seq) footprint sequencing", "data_format": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "mod_smncopynumbercaller_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion of Exon7-8) from a whole-genome sequencing (WGS) BAM file. (tools: smncopynumbercaller)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mafft/align": null, "cnvkit/access": null, "smncopynumbercaller": null, "cnvkit/batch": null, "deacon/filter": null}}, "target": "smncopynumbercaller", "target_idx": 2}
{"id": "resource_bedtools_complement_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COMPLEMENT", "tool": "bedtools/complement", "description": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COMPLEMENT (Returns all intervals in a genome that are not covered by at least one interval ) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for ATAC-seq chromatin accessibility with biological replicates. Input files: Paired-end Tn5 transposed FASTQs across conditions and replicates.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bam": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_21", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_ultra_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Map reads on genome (tools: ultra)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra/pipeline": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection", "vrhyme/vrhyme": "Binning virus genomes from metagenomes", "ultra/align": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Map reads on genome", "bftools/showinf": "Extract OME xml data from OME-tif", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}}, "target": "ultra/align", "target_idx": 2}
{"id": "resource_bakta_bakta_2", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTA", "tool": "bakta/bakta", "description": "Annotation of bacterial genomes (isolates, MAGs) and plasmids"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTA (Annotation of bacterial genomes (isolates, MAGs) and plasmids) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_bam_vcf_impute_glimpse2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VCF_IMPUTE_GLIMPSE2", "modules": ["glimpse2/chunk", "glimpse2/phase", "glimpse2/ligate", "glimpse2/splitreference", "bcftools/index"], "description": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should BAM_VCF_IMPUTE_GLIMPSE2 (glimpse2/chunk, glimpse2/phase, glimpse2/ligate, glimpse2/splitreference, bcftools/index) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VCF_IMPUTE_GLIMPSE2": null, "Leave them out": null, "Use nf-core subworkflow bam_vcf_impute_glimpse2": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_vcf_impute_glimpse2", "target_idx": 2}
{"id": "mod_authentict_deam2cont_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use deamination patterns to estimate contamination in single-stranded libraries (tools: authentict)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_bwa": "Align reads to a reference genome using bwa then sort with samtools", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "snpsift/annmem": "Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-opt", "mapad/map": "Map short-reads to an indexed reference genome", "authentict/deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries"}}, "target": "authentict/deam2cont", "target_idx": 4}
{"id": "mod_xeniumranger_rename_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all the Xenium Onboard Analysis output files that contain this information. (tools: xeniumranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scimap_mcmicro": "SCIMAP is a suite of tools that enables spatial single-cell analyses", "gatk4_cnnscorevariants": "Apply a Convolutional Neural Net to filter annotated variants", "xeniumranger_rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "proseg_proseg": "Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics.", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs"}}, "target": "xeniumranger_rename", "target_idx": 2}
{"id": "mod_bbmap_sendsketch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compares query sketches to reference sketches hosted on a remote server via the Internet. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_makeblastdb": null, "ganon_buildcustom": null, "ganon_report": null, "gem2_gemmappability": null, "bbmap_sendsketch": null}}, "target": "bbmap_sendsketch", "target_idx": 4}
{"id": "field_constraint_bai_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_0", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_ectyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In silico prediction of E. coli serotype (tools: ectyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mgikit_demultiplex": null, "abritamr_run": null, "star_align": null, "stecfinder": null, "ectyper": null}}, "target": "ectyper", "target_idx": 4}
{"id": "mod_hipstr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genotype and phase short tandem repeats using Illumina whole-genome sequencing data (tools: hipstr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/eslsfetch": "Retrieves one or more complete sequences or subsequences from a sequence\nfile using its pre-built SSI index. T", "metaphlan/makedb": "Build MetaPhlAn database for taxonomic profiling.", "gangstr": "GangSTR is a tool for genome-wide profiling tandem repeats from short reads.", "expansionhunterdenovo/profile": "Compute genome-wide STR profile", "hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data"}}, "target": "hipstr", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_0_22", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_omicsgenetraitassociation_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/omicsgenetraitassociation", "description": "A nextflow pipeline which integrates multiple omic data streams and performs coordinated analysis", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/omicsgenetraitassociation?", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,bam,pbi,fail,repeat_id": null, "sample,bam,vcf,rna_matrix,hto_matrix": null}}, "target": "sample,trait,pascal,twas,additional_sources", "target_idx": 0}
{"id": "mod_gunc_mergecheckm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merging of CheckM and GUNC results in one summary table (tools: gunc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"graphtyper/genotype": "Tools for population-scale genotyping using pangenome graphs.", "checkm2/predict": "CheckM2 bin quality prediction", "varscan/processsomatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "checkv/endtoend": "Assess the quality of metagenome-assembled viral genomes.", "gunc/mergecheckm": "Merging of CheckM and GUNC results in one summary table"}}, "target": "gunc/mergecheckm", "target_idx": 4}
{"id": "noul_deprecated_file_output_syntax_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_msisensor2_msi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: msisensor2 detection of MSI regions. (tools: msisensor2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ichorcna_run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "msisensor_scan": "Scan a reference genome to get microsatellite & homopolymer information", "eggnogmapper": "Fast genome-wide functional annotation through orthology assignment.", "untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives", "msisensor2_msi": "msisensor2 detection of MSI regions."}}, "target": "msisensor2_msi", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_1_20", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_expansionhunter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate repeat sizes using NGS data (tools: expansionhunter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja/demix": "specify the relative abundance of each known haplotype", "krakenuniq/preloadedkrakenuniq": "Classifies metagenomic sequence data using unique k-mer counts", "expansionhunterdenovo/profile": "Compute genome-wide STR profile", "hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data", "expansionhunter": "Estimate repeat sizes using NGS data"}}, "target": "expansionhunter", "target_idx": 4}
{"id": "mod_varlociraptor_callvariants_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlociraptor preprocessing (tools: varlociraptor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"popscle_demuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "estsfs": "estimation of the unfolded site frequency spectrum", "varlociraptor_preprocess": "Obtains per-sample observations for the actual calling process with varlociraptor calls", "varlociraptor_callvariants": "Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlocira", "freyja_boot": "Bootstrap sample demixing by resampling each site based on a multinomial distribution of read depth across all"}}, "target": "varlociraptor_callvariants", "target_idx": 3}
{"id": "pipe_all101_rnafusion_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for fusion analysis? Specific context: RNA-seq analysis pipeline for detection of gene-fusions. Topics: fusion, fusion-genes, gene-fusion, rna, rna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous"}}, "target": "rnafusion", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_1_6", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_23", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_portcullis_full_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run all Portcullis steps in one go (tools: portcullis)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"portcullis/full": "Run all Portcullis steps in one go", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "popscle/dscpileup": "Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode.", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "mmseqs/tsv2exprofiledb": "Conversion of expandable profile to databases to the MMseqs2 databases format"}}, "target": "portcullis/full", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_47", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_multiplesequencealign_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/multiplesequencealign", "description": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/multiplesequencealign?", "criteria": {"id,fasta,reference,optional_data,template": null, "id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "id,fasta,reference,optional_data,template", "target_idx": 0}
{"id": "field_constraint_status_2_4", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "pipe_all101_differentialabundance_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq. Topics: atac-seq, chip-seq, deseq2, differential-abundance, differential-expression, gsea. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]"}}, "target": "differentialabundance", "target_idx": 3}
{"id": "resource_bbmap_bbduk_1", "category": "resource_profiling", "state": {"process": "BBMAP_BBDUK", "tool": "bbmap/bbduk", "description": "Adapter and quality trimming of sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBDUK (Adapter and quality trimming of sequencing reads) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_2_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "mod_fgbio_fastqtobam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI barcode into the RX field of the reads (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_splitmerge": "split single end read groups by length and merge paired end reads", "fgbio_fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "traitar_pfamget": "Download PFAM database for traitar phenotype prediction", "caddsv_run": "Score structural variants with CADD-SV."}}, "target": "fgbio_fastqtobam", "target_idx": 1}
{"id": "intent_prepare_data_21", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "debug_error": null, "build_pipeline": null, "prepare_data": null}}, "target": "prepare_data", "target_idx": 3}
{"id": "field_constraint_sex_1_10", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "subworkflow_pkg_abundance_differential_filter_3", "category": "subworkflow_packaging", "state": {"subworkflow": "ABUNDANCE_DIFFERENTIAL_FILTER", "modules": ["limma/differential", "deseq2/differential", "propr/propd", "custom/filterdifferentialtable", "variancepartition/dream"], "description": "A subworkflow for filtering differential abundance results"}, "question": {"type": "choice", "instructions": "How should ABUNDANCE_DIFFERENTIAL_FILTER (limma/differential, deseq2/differential, propr/propd, custom/filterdifferentialtable, variancepartition/dream) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow abundance_differential_filter": null, "Keep the modules in the main workflow": null, "Local subworkflow ABUNDANCE_DIFFERENTIAL_FILTER": null}}, "target": "Use nf-core subworkflow abundance_differential_filter", "target_idx": 1}
{"id": "resource_bedtools_slop_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SLOP", "tool": "bedtools/slop", "description": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SLOP (Adds a specified number of bases in each direction (unique values may be specifi) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gt_ltrharvest_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts LTR retrotransposons using GenomeTools gt-ltrharvest utility (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"humid": "HUMID is a tool to quickly and easily remove duplicate reads from FASTQ files, with or without UMIs.", "star/genomegenerate": "Create index for STAR", "gt/ltrharvest": "Predicts LTR retrotransposons using GenomeTools gt-ltrharvest utility", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "alignoth": "Creating alignment plots from bam files"}}, "target": "gt/ltrharvest", "target_idx": 2}
{"id": "resource_argnorm_3", "category": "resource_profiling", "state": {"process": "ARGNORM", "tool": "argnorm", "description": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARGNORM (Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed b) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_snpeff_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "ensemblvep/vep", "snpeff/download", "snpeff/snpeff", "htslib/bgziptabix", "bcftools/pluginscatter", "bcftools/concat", "bcftools/sort"], "description": "Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkflow uses the scatter-gather method to run VEP/snpEff in parallel to increase throughput. The input VCF is split into multiple smaller VCFs of fixed size, which are annotated separately and concatenated back together to a single output file per sample. Only VCF/BCF outputs are currently supported."}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP_SNPEFF (ensemblvep/download, ensemblvep/vep, snpeff/download, snpeff/snpeff, htslib/bgziptabix, bcftools/pluginscatter, bcftools/concat, bcftools/sort) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff": null, "Local subworkflow VCF_ANNOTATE_ENSEMBLVEP_SNPEFF": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff", "target_idx": 1}
{"id": "mod_openms_idfilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters peptide/protein identification results by different criteria. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "gatk4_intervallisttools": "Splits the interval list file into unique, equally-sized interval files and place it under a directory", "gatk4_getpileupsummaries": "Summarizes counts of reads that support reference, alternate and other alleles for given sites. Results can be", "openms_idfilter": "Filters peptide/protein identification results by different criteria.", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "openms_idfilter", "target_idx": 3}
{"id": "mod_cutesv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: structural-variant calling with cutesv (tools: cutesv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sawfish_discover": null, "saltshaker_plot": null, "iphop_download": null, "cutesv": null, "xeniumranger_relabel": null}}, "target": "cutesv", "target_idx": 3}
{"id": "pipe_all101_stableexpression_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for expression. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]"}}, "target": "stableexpression", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_explore_search_plot_tidk_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_EXPLORE_SEARCH_PLOT_TIDK", "modules": ["seqkit/seq", "seqkit/sort", "tidk/explore", "tidk/plot", "tidk/search"], "description": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats"}, "question": {"type": "choice", "instructions": "How should FASTA_EXPLORE_SEARCH_PLOT_TIDK (seqkit/seq, seqkit/sort, tidk/explore, tidk/plot, tidk/search) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_EXPLORE_SEARCH_PLOT_TIDK": null, "Use nf-core subworkflow fasta_explore_search_plot_tidk": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_explore_search_plot_tidk", "target_idx": 1}
{"id": "field_constraint_fastq_1_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "mod_sentieon_staralign_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using Sentieon STAR (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/parsetables": null, "localcdsearch/annotate": null, "sentieon/staralign": null, "longphase/haplotag": null, "ampcombi2/complete": null}}, "target": "sentieon/staralign", "target_idx": 2}
{"id": "mod_gt_stat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GenomeTools gt-stat utility to show statistics about features contained in GFF3 files (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "cooler_balance": "Run matrix balancing on a cool file", "gemmi_cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "gt_stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files"}}, "target": "gt_stat", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_2_20", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_bwameme_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA-MEME index for reference genome (tools: bwameme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "gatk4/mergevcfs": "Merges several vcf files", "bowtie/build": "Create bowtie index for reference genome", "bwameme/index": "Create BWA-MEME index for reference genome", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples)."}}, "target": "bwameme/index", "target_idx": 3}
{"id": "resource_biomformat_convert_5", "category": "resource_profiling", "state": {"process": "BIOMFORMAT_CONVERT", "tool": "biomformat/convert", "description": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HDF5) formats are supported"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOMFORMAT_CONVERT (Convert biom table to different format.\nConversion between text tab-delimited, B) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_status_0_3", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "mod_repeatmodeler_repeatmodeler_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs de novo transposable element (TE) family identification with RepeatModeler (tools: repeatmodeler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpeff/download": null, "alignoth": null, "repeatmodeler/repeatmodeler": null, "ataqv/mkarv": null, "agat/spfilterbyorfsize": null}}, "target": "repeatmodeler/repeatmodeler", "target_idx": 2}
{"id": "intent_build_pipeline_16", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_blast_blastdbcmd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Retrieve entries from a BLAST database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "vsearch_usearchglobal": "Compare target sequences to fasta-formatted query sequences using global pairwise alignment.", "blast_blastdbcmd": "Retrieve entries from a BLAST database", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "mgnifam_generatefamilies": "Iteratively builds protein family HMM profiles from MMseqs2 sequence clusters and expands them against a prote"}}, "target": "blast_blastdbcmd", "target_idx": 2}
{"id": "mod_carveme_carve_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe (tools: carveme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4spark/baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "carveme/carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "gapseq/fill": "Perform gap filling on draft metabolic model", "kallisto/index": "Create kallisto index", "gapseq/medium": "Predict growth medium from a draft model and pathway predictions"}}, "target": "carveme/carve", "target_idx": 1}
{"id": "schema_std_readsimulator_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/readsimulator", "description": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/readsimulator?", "criteria": {"sample,fastq_1,strandedness": null, "sample,seed": null, "sample,bundle,image": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "sample,seed", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_7_2", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "FASTQC", "library_inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "schema_std_tumourevo_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tumourevo", "description": "Analysis pipeline to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/tumourevo?", "criteria": {"SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "patient,vcf,tbi,dataset,tumour_sample": null, "sample,type,level,msfile": null}}, "target": "patient,vcf,tbi,dataset,tumour_sample", "target_idx": 2}
{"id": "mod_bedtools_genomecov_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., aligned sequences) for a given genome. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "president": "Calculate pairwise nucleotide identity with respect to a reference sequence", "meningotype": "Serotyping of Neisseria meningitidis assemblies", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "bedtools_genomecov", "target_idx": 0}
{"id": "mod_hhsuite_hhblits_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast and sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs) (tools: hhsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"helitronscanner/scan": "HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes", "hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "hmmer/hmmfetch": "extract hmm from hmm database file or create index for hmm database", "hhsuite/hhblits": "Fast and sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "bcl_demultiplex": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq"}}, "target": "hhsuite/hhblits", "target_idx": 3}
{"id": "samplesheet_arch_mira_influenza_sc2_5_2", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels", "pipeline": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline custom/mira-nf, determine the input samplesheet column structure for: Custom MIRA-NF Influenza / SC2 pipeline.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_bwamem3_mem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align fastq reads to a fasta reference using bwa-mem3 (tools: bwamem3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA", "sentieon_coveragemetrics": "Accelerated implementation of the GATK DepthOfCoverage tool.", "seroba_run": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3"}}, "target": "bwamem3_mem", "target_idx": 4}
{"id": "mod_coptr_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the coverage map along the reference genome (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit_wps": "Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription", "coptr_extract": "Computes the coverage map along the reference genome", "deepsomatic": "DeepSomatic is an extension of deep learning-based variant caller DeepVariant that takes aligned reads (in BAM", "circularmapper_circulargenerator": "A method to improve mappings on circular genomes, using the BWA mapper.", "coverm_contig": "Map reads to contigs and estimate coverage"}}, "target": "coptr_extract", "target_idx": 1}
{"id": "noul_include_modular_process_syntax_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diaproteomics", "assay_type": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "data_format": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions?", "criteria": {"sample,raw_file,condition": null, "sample,peptides_tsv": null, "sample,mzml": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "mod_longphase_haplotag_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modifications for Nanopore and PacBio platforms. (tools: longphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"htodemux": "Demultiplex samples based on data from cell hashing.", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "autocycler/cluster": "Cluster replicons in compressed assemblies with Autocycler.", "ectyper": "In silico prediction of E. coli serotype", "longphase/haplotag": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi"}}, "target": "longphase/haplotag", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_43", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_strvctvre_strvctvre_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a structural variant classifier for exonic deletions and duplications (tools: strvctvre)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "custom_rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "caddsv_run": "Score structural variants with CADD-SV.", "entrezdirect_esummary": "Queries an NCBI database using Unique Identifier(s)", "strvctvre_strvctvre": "a structural variant classifier for exonic deletions and duplications"}}, "target": "strvctvre_strvctvre", "target_idx": 4}
{"id": "mod_pharokka_pharokka_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functional annotation of phages (tools: pharokka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pharokka_pharokka": "Functional annotation of phages", "bacphlip": "A bacteriophage lifestyle prediction tool", "plink_extract": "Subset plink bfiles with a text file of variant identifiers", "genomad_endtoend": "Identify mobile genetic elements present in genomic assemblies", "bedtools_intersect": "Allows one to screen for overlaps between two sets of genomic features."}}, "target": "pharokka_pharokka", "target_idx": 0}
{"id": "resource_bedtools_closest_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_CLOSEST", "tool": "bedtools/closest", "description": "For each feature in A, finds the closest feature (upstream or downstream) in B."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_CLOSEST (For each feature in A, finds the closest feature (upstream or downstream) in B.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_airrflow_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework. Topics: airr, b-cell, immcantation, immunorepertoire, repseq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "seqsubmit": "nf-core pipeline for data submission to ENA", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo"}}, "target": "airrflow", "target_idx": 4}
{"id": "noul_channel_join_operator_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_cnvkit_segment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Infer discrete copy number segments from the given coverage table. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/segment": "Infer discrete copy number segments from the given coverage table.", "cnvkit/genemetrics": "Copy number variant detection from high-throughput sequencing data", "cnvkit/call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number", "mmseqs_contig_taxonomy": "Assign taxonomy to contigs using the MMseqs2 workflow.", "scramble/clusteranalysis": "The Cluster Analysis tool of Scramble analyses and interprets the soft-clipped clusters found by `cluster_iden"}}, "target": "cnvkit/segment", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_quantify_rsem_0", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_RSEM", "modules": ["rsem/calculateexpression", "sentieon/rsemcalculateexpression", "custom/rsemmergecounts", "quant_tximport_summarizedexperiment"], "description": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_RSEM (rsem/calculateexpression, sentieon/rsemcalculateexpression, custom/rsemmergecounts, quant_tximport_summarizedexperiment) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow quantify_rsem": null, "Local subworkflow QUANTIFY_RSEM": null, "Leave them out": null}}, "target": "Use nf-core subworkflow quantify_rsem", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_6_5", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Xenium in situ subcellular spatial RNA transcriptomics input samplesheet?", "criteria": {"sample,image": null, "sample,vcf": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "resource_basicpy_2", "category": "resource_profiling", "state": {"process": "BASICPY", "tool": "basicpy", "description": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is developed based on the Matlab version of BaSiC tool with major improvements in the algorithm."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASICPY (BaSiCPy is a python package for background and shading correction of optical mic) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_marsseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze MARS-seq v2 pre-processing pipeline with velocity. Topics: facs-sorting, mars-seq, single-cell, single-cell-rna-seq, star-solo, transcriptional-dynamics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo"}}, "target": "marsseq", "target_idx": 4}
{"id": "noul_retry_errorstrategy_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_mageck_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mageck count for functional genomics, reads are usually mapped to a specific sgRNA (tools: mageck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "mageck_count": "mageck count for functional genomics, reads are usually mapped to a specific sgRNA", "gtdbtk_classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "sentieon_tnscope": "TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, us"}}, "target": "mageck_count", "target_idx": 2}
{"id": "mod_plink_exclude_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Exclude variant identifiers from plink bfiles (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_gxf_busco_plot": "Runs BUSCO for input assemblies and their annotations in GFF/GFF3/GTF format, and creates summary plots using ", "plink/bcf": "Analyses binary variant call format (BCF) files using plink", "plink/exclude": "Exclude variant identifiers from plink bfiles", "plink/indep": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other.", "ribotish/predict": "Quality control of riboseq bam data"}}, "target": "plink/exclude", "target_idx": 2}
{"id": "mod_hifiasm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Whole-genome assembly using PacBio HiFi reads (tools: hifiasm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gfastats": "A single fast and exhaustive tool for summary statistics and simultaneous *fa*\n(fasta, fastq, gfa [.gz]) genom", "glimpse2/phase": "Tool for imputation and phasing from vcf file or directly from bam files.", "biscuit/epiread": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compl", "hifiasm": "Whole-genome assembly using PacBio HiFi reads", "hmmer/hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile"}}, "target": "hifiasm", "target_idx": 3}
{"id": "mod_rhocall_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Markup VCF file using rho-calls. (tools: rhocall)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy_scrublet": "Detect doublets in single-cell RNA-seq data using Scrublet via Scanpy", "rhocall_viz": "Call regions of homozygosity and make tentative UPD calls", "ngsbits_rohhunter": "RohHunter is a tool for run of homozygosity (ROH) detection based on a variant list in VCF format.", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "rhocall_annotate": "Markup VCF file using rho-calls."}}, "target": "rhocall_annotate", "target_idx": 4}
{"id": "pipe_all101_circdna_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for ampliconarchitect. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants"}}, "target": "circdna", "target_idx": 1}
{"id": "noul_executor_support_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "local_subworkflow_prepilluminareads_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should PREPILLUMINAREADS (trimmomatic) be built?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow PREPILLUMINAREADS": null, "Leave them out": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 1}
{"id": "field_constraint_expected_cells_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "mod_samtools_consensus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a consensus FASTA/FASTQ/PILEUP (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_merge": null, "bismark_coverage2cytosine": null, "delly_call": null, "samtools_consensus": null, "drep_dereplicate": null}}, "target": "samtools_consensus", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_19", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_chopper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter and trim long read data. (tools: zcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamutil/clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo", "bedtools/bamtobed": "Converts a bam file to a bed12 file.", "chopper": "Filter and trim long read data.", "bbmap/filterbyname": "Filter out sequences by sequence header name(s)", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "chopper", "target_idx": 2}
{"id": "resource_bcftools_filter_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_FILTER", "tool": "bcftools/filter", "description": "Filters VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_FILTER (Filters VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "core_tool_salmon_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Transcript-level abundance estimation and pseudo-alignment directly from raw paired-end RNA-seq FASTQ reads without full genome mapping.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"samtools": null, "salmon": null, "featurecounts": null, "kallisto": null, "rsem": null}}, "target": "salmon", "target_idx": 1}
{"id": "intent_ask_question_10", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Visium spatial transcriptomics with histology image", "data_format": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,image": null, "sample,bam": null, "sample,image": null, "sample,fastq_1,fastq_2,image,slide,area": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 3}
{"id": "samplesheet_arch_bulk_small_rna_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/smrnaseq) for Small RNA / miRNA sequencing. Input files: Single-end 50bp miRNA reads with 3-prime adapter.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1,mirna_id": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_fasta_newick_epang_gappa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in nf-core/phyloplace. (tools: fasta_newick_epang_gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/fixmateinformation": null, "fastme": null, "fasta_newick_epang_gappa": null, "epang/split": null, "bcftools/consensus": null}}, "target": "fasta_newick_epang_gappa", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_5", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_variantbam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtering, downsampling and profiling alignments in BAM/CRAM formats (tools: variantbam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_reblockgvcf": "Condenses homRef blocks in a single-sample GVCF", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bam_markduplicates_samtools": "Samtools markduplicate SAM/BAM/CRAM file"}}, "target": "variantbam", "target_idx": 1}
{"id": "mod_whatshap_phase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Phase variants in a VCF file using long-read sequencing data (tools: whatshap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/tsv2exprofiledb": "Conversion of expandable profile to databases to the MMseqs2 databases format", "hifiasm": "Whole-genome assembly using PacBio HiFi reads", "beagle5/beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "whatshap/phase": "Phase variants in a VCF file using long-read sequencing data", "muse/sump": "Computes tier-based cutoffs from a sample-specific error model which is generated by muse/call and reports the"}}, "target": "whatshap/phase", "target_idx": 3}
{"id": "mod_quilt_quilt2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased reference panel in VCF/BCF format. (tools: quilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"beagle5_beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "quilt_quilt2": "QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased re", "bam_create_som_pon_gatk": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a geno", "glimpse_ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information.", "odgi_layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and "}}, "target": "quilt_quilt2", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_33", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_all101_readsimulator_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for readsimulator analysis? Specific context: A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data.. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection"}}, "target": "readsimulator", "target_idx": 1}
{"id": "pipe_all101_drugresponseeval_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for cell-lines analysis? Specific context: Pipeline for testing drug response prediction models in a statistically and biologically sound way.. Topics: cell-lines, cross-validation, deep-learning, drug-response, drug-response-prediction, drugs. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "callingcards": "A pipeline for processing calling cards data"}}, "target": "drugresponseeval", "target_idx": 2}
{"id": "samplesheet_arch_vcf_annotation_pipeline_4_4", "category": "samplesheet_schema", "state": {"technology": "Variant Annotation", "workflow_entry": "ENSEMBLVEP", "library_inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: BGZF-compressed VCF files with companion Tabix index files?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "subworkflow_pkg_bam_impute_quilt_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_QUILT", "modules": ["gawk", "quilt/quilt", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using QUILT software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_QUILT (gawk, quilt/quilt, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_impute_quilt": null, "Local subworkflow BAM_IMPUTE_QUILT": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_impute_quilt", "target_idx": 0}
{"id": "mod_hmmer_eslreformat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: reformats sequence files, see HMMER documentation for details. The module requires that the format is specified in ext.args in a config file, and that this comes last. See the tools help for possible values. (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscreen_fastqscreen": "Align reads to multiple reference genomes using fastq-screen", "merquryfk_ploidyplot": "An improved version of Smudgeplot using FastK", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "hmmer_eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie"}}, "target": "hmmer_eslreformat", "target_idx": 4}
{"id": "core_tool_kraken2_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Exact k-mer matching taxonomic classifier mapping metagenomic reads to bacterial and viral reference genomes with lowest common ancestor algorithm.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"diamond": null, "centrifuge": null, "metaphlan": null, "kraken2": null, "motus": null}}, "target": "kraken2", "target_idx": 3}
{"id": "mod_ngscheckmate_vafncm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determining whether sequencing data comes from the same individual by using SNP matching. This module generates PT files from a bed file containing individual positions. (tools: ngscheckmate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_ngscheckmate": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set o", "liftoff": "Uses Liftoff to accurately map annotations in GFF or GTF between assemblies of the same,\nor closely-related sp", "ngscheckmate_vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "cellsnp_modea": "Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A ", "ngsbits_updhunter": "UPD detection from trio variant data."}}, "target": "ngscheckmate_vafncm", "target_idx": 2}
{"id": "samplesheet_arch_spatial_xenium_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Xenium in situ subcellular spatial RNA transcriptomics", "data_format": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null, "sample,vcf": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "assay_type": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "data_format": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multi-taxonomic profiling of complex metagenomic shotgun reads input samplesheet?", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_datasync_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/datasync", "assay": "datasync pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/datasync (nf-core/datasync is a system operation pipeline that provide)?", "criteria": {"sample,group,ref_fasta,ref_gff,use_ref": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "sample,fastq_1,fastq_2,barcode": null, "id,taxid,fasta_dna,fasta_aa": null}}, "target": "sample,input,output_path,checksum_md5,checksum_sha", "target_idx": 1}
{"id": "noul_channel_operator_map_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_custom_tabulartogseacls_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make a GSEA class file (.cls) from tabular inputs (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gsea_gsea": null, "vt_decomposeblocksub": null, "bamtools_convert": null, "bclconvert": null, "custom_tabulartogseacls": null}}, "target": "custom_tabulartogseacls", "target_idx": 4}
{"id": "field_constraint_sample_0_13", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "format: file-path": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "noul_default_empty_channel_behavior_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "field_constraint_bai_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "mod_hmmer_hmmalign_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: hmmalign from the HMMER suite aligns a number of sequences to an HMM profile (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shigapass": "ShigaPass is an in silico tool used to predict Shigella serotypes and to differentiate between Shigella, EIEC ", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "alignoth": "Creating alignment plots from bam files", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "hmmer_hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile"}}, "target": "hmmer_hmmalign", "target_idx": 4}
{"id": "subworkflow_pkg_bam_qc_picard_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_PICARD", "modules": ["picard/collectmultiplemetrics", "picard/collectwgsmetrics", "picard/collecthsmetrics"], "description": "Produces comprehensive statistics from BAM file"}, "question": {"type": "choice", "instructions": "How should BAM_QC_PICARD (picard/collectmultiplemetrics, picard/collectwgsmetrics, picard/collecthsmetrics) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_qc_picard": null, "Leave them out": null, "Local subworkflow BAM_QC_PICARD": null}}, "target": "Use nf-core subworkflow bam_qc_picard", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic cancer variant calling with tumor-normal pairs", "data_format": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic cancer variant calling with tumor-normal pairs input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_strdrop_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build reference json from sequencing coverage in STR VCFs (tools: strdrop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/summarise": null, "stranger": null, "prokka": null, "strdrop/build": null, "expansionhunterdenovo/profile": null}}, "target": "strdrop/build", "target_idx": 3}
{"id": "noul_named_process_output_emits_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_holodeck_simulate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simulate sequencing reads from a reference genome with holodeck (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "holodeck/eval": "Evaluate alignment accuracy of holodeck-simulated reads", "holodeck/simulate": "Simulate sequencing reads from a reference genome with holodeck", "slimfastq": "Fast, efficient, lossless compression of FASTQ files.", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads"}}, "target": "holodeck/simulate", "target_idx": 2}
{"id": "resource_bacphlip_3", "category": "resource_profiling", "state": {"process": "BACPHLIP", "tool": "bacphlip", "description": "A bacteriophage lifestyle prediction tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACPHLIP (A bacteriophage lifestyle prediction tool) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bbmap_clumpify_4", "category": "resource_profiling", "state": {"process": "BBMAP_CLUMPIFY", "tool": "bbmap/clumpify", "description": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_CLUMPIFY (Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_idr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate) (tools: idr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_convert": "Converts certain output formats to VCF", "jvarkit_dict2bed": "Extract BED file from hts files containing a dictionary (VCF,BAM, CRAM, DICT, etc...)", "idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)", "homer_annotatepeaks": "Annotate peaks with HOMER suite", "homer_makeucscfile": "Create a UCSC bed graph with the HOMER suite"}}, "target": "idr", "target_idx": 2}
{"id": "noul_named_process_output_emits_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_4_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end ribosome protected RNA fragments (RPFs) with strandedness?", "criteria": {"sample,fastq_1,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnafusion) for RNA gene fusion detection (Arriba, STAR-Fusion). Input files: Paired-end oncology RNA-seq reads for chimeric transcript discovery.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for RNA gene fusion detection (Arriba, STAR-Fusion) with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_3_2", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Tumor-only somatic variant calling without matched normal with entry step FASTQC.", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_funcscan_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for amp. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "callingcards": "A pipeline for processing calling cards data"}}, "target": "funcscan", "target_idx": 0}
{"id": "mod_aardvark_compare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF. (tools: aardvark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/compare": null, "bcftools/filter": null, "ucsc/bedtobigbed": null, "aardvark/merge": null, "picard/collectwgsmetrics": null}}, "target": "aardvark/compare", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "field_constraint_bai_3_9", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "resource_biscuit_pileup_5", "category": "resource_profiling", "state": {"process": "BISCUIT_PILEUP", "tool": "biscuit/pileup", "description": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_PILEUP (Computes cytosine methylation and callable SNV mutations, optionally in referenc) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_0_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "mod_last_dotplot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Makes a dotplot (Oxford Grid) of pair-wise sequence alignments (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ensemblvep/download": "Ensembl Variant Effect Predictor (VEP). The cache downloading options are controlled through `task.ext.args`.", "seroba/run": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "last/dotplot": "Makes a dotplot (Oxford Grid) of pair-wise sequence alignments", "last/mafswap": "Reorder alignments in a MAF file", "last/lastal": "Aligns query sequences to target sequences indexed with lastdb"}}, "target": "last/dotplot", "target_idx": 2}
{"id": "mod_coreograph_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, to identify complete/incomplete tissue cores on a tissue microarray. It has been trained on 9 TMA slides of different sizes and tissue types. (tools: coreograph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coreograph": null, "popscle/dscpileup": null, "falint": null, "ilastik/pixelclassification": null, "deepcell/mesmer": null}}, "target": "coreograph", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_7_2", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "samplesheet_arch_scrna_multiome_0_4", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,rna_fastq,atac_fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_wgs_6_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ", "pipeline": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Pacific Biosciences HiFi sequencing input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_tximeta_tximport_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Import transcript-level abundances and estimated counts for gene-level\nanalysis packages (tools: tximeta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pychopper": "Identify, orient and trim nanopore cDNA reads", "tximeta/tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages", "cafe": "Analysis of gene family evolution", "atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files", "aria2": "CLI Download utility"}}, "target": "tximeta/tximport", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_6_4", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic tumor-normal calling from pre-aligned BAM files input samplesheet?", "criteria": {"sample,vcf": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_2_25", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_ribotish_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality control of riboseq bam data (tools: ribotish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plastid/metagenegenerate": null, "bedops/convert2bed": null, "rclone/checksum": null, "dotseq/dotseq": null, "ribotish/predict": null}}, "target": "ribotish/predict", "target_idx": 4}
{"id": "resource_bcftools_concat_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONCAT", "tool": "bcftools/concat", "description": "Concatenate VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONCAT (Concatenate VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_37", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_ampcombi2_complete_0", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_COMPLETE", "tool": "ampcombi2/complete", "description": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_COMPLETE (A submodule that merges all output summary tables from ampcombi/parsetables in o) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_custom_summarisetelomereestimation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a unified summary (tools: pandas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmap/map": "create mappability files for a genome", "cellrangerarc/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkref c", "telomerehunter": "In silico estimation of telomere content and composition from cancer genomes", "tidk/plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "custom/summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a"}}, "target": "custom/summarisetelomereestimation", "target_idx": 4}
{"id": "samplesheet_arch_chipseq_with_control_0_3", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "template": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "resource_arcashla_extract_5", "category": "resource_profiling", "state": {"process": "ARCASHLA_EXTRACT", "tool": "arcashla/extract", "description": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCASHLA_EXTRACT (Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alterna) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedtools_sort_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SORT", "tool": "bedtools/sort", "description": "Sorts a feature file by chromosome and other criteria."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SORT (Sorts a feature file by chromosome and other criteria.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_medium", "target_idx": 2}
{"id": "resource_bcftools_convert_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONVERT", "tool": "bcftools/convert", "description": "Converts certain output formats to VCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONVERT (Converts certain output formats to VCF) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_quant_tximport_summarizedexperiment_0", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT", "modules": ["custom/tx2gene", "tximeta/tximport", "summarizedexperiment/summarizedexperiment"], "description": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT (custom/tx2gene, tximeta/tximport, summarizedexperiment/summarizedexperiment) be structured in DSL2?", "criteria": {"Use nf-core subworkflow quant_tximport_summarizedexperiment": null, "Leave them out": null, "Local subworkflow QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow quant_tximport_summarizedexperiment", "target_idx": 0}
{"id": "mod_pygenprop_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a Micromeda file containing pathway annotations for one or more genomes.\nSupporting InterProScan and protein sequence information can also be optionally incorporated. (tools: pygenprop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sratools_prefetch": "Download sequencing data from the NCBI Sequence Read Archive (SRA).", "eggnogmapper": "Fast genome-wide functional annotation through orthology assignment.", "mgnifam_generatefamilies": "Iteratively builds protein family HMM profiles from MMseqs2 sequence clusters and expands them against a prote", "interproscan": "Produces protein annotations and predictions from an amino acids FASTA file", "pygenprop_build": "Generate a Micromeda file containing pathway annotations for one or more genomes.\nSupporting InterProScan and "}}, "target": "pygenprop_build", "target_idx": 4}
{"id": "resource_agat_sqstatbasic_3", "category": "resource_profiling", "state": {"process": "AGAT_SQSTATBASIC", "tool": "agat/sqstatbasic", "description": "Provides basic statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SQSTATBASIC (Provides basic statistics in text format from a GFF/GTF annotation file) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_41", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_aardvark_compare_1", "category": "resource_profiling", "state": {"process": "AARDVARK_COMPARE", "tool": "aardvark/compare", "description": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_COMPARE (A tool to evaluate variant calling performance by comparing a query VCF against ) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_5_3", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/dualrnaseq, determine the input samplesheet column structure for: Dual RNA-seq simultaneous host and pathogen transcriptomics.", "criteria": {"sample,fastq_1": null, "sample,host_fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "resource_bamreadcount_1", "category": "resource_profiling", "state": {"process": "BAMREADCOUNT", "tool": "bamreadcount", "description": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMREADCOUNT (bam-readcount is a utility that runs on a BAM or CRAM file and generates low-lev) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_1_2", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "resource_beagle5_beagle_0", "category": "resource_profiling", "state": {"process": "BEAGLE5_BEAGLE", "tool": "beagle5/beagle", "description": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEAGLE5_BEAGLE (Beagle v5.5 is a software package for phasing genotypes and for imputing ungenot) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_funcscan_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: (Meta-)genome screening for functional and natural product gene sequences. Topics: amp, amr, antibiotic-resistance, antimicrobial-peptides, antimicrobial-resistance-genes, arg. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "funcscan", "target_idx": 5}
{"id": "mod_tcoffee_alncompare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compares 2 alternative MSAs to evaluate them. (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4spark_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "tcoffee_alncompare": "Compares 2 alternative MSAs to evaluate them.", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "sourmash_taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information."}}, "target": "tcoffee_alncompare", "target_idx": 2}
{"id": "schema_std_oncoanalyser_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "description": "A comprehensive cancer DNA/RNA analysis and reporting pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/oncoanalyser?", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,alleles,mhc_class,filename": null, "sample_id,img_directory,parameter_file": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "sample_id,group_id,subject_id,sample_type,sequence_type", "target_idx": 3}
{"id": "resource_bedtools_merge_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MERGE", "tool": "bedtools/merge", "description": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MERGE (combines overlapping or “book-ended” features in an interval file into a single ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_32", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_vcfpgloader_load_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: High-performance VCF to PostgreSQL loader using asyncpg for bulk variant ingestion (tools: vcf-pg-loader)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "custom/orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c", "parabricks/applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "vcfpgloader/load": "High-performance VCF to PostgreSQL loader using asyncpg for bulk variant ingestion"}}, "target": "vcfpgloader/load", "target_idx": 4}
{"id": "mod_htsnimtools_vcfcheck_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will instead want whole exome) coverage and uses that as an expectation of variants. (tools: htsnimtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/happy": "Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row", "iqtree": "Produces a Newick format phylogeny from a multiple sequence alignment using the maximum likelihood algorithm. ", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "htsnimtools/vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "fastavalidator": "\"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror lo"}}, "target": "htsnimtools/vcfcheck", "target_idx": 3}
{"id": "mod_bcftools_roh_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered. (tools: roh)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pneumocat": null, "scramble_clusteridentifier": null, "rhocall_viz": null, "rhocall_annotate": null, "bcftools_roh": null}}, "target": "bcftools_roh", "target_idx": 4}
{"id": "samplesheet_arch_mira_influenza_sc2_2_1", "category": "samplesheet_schema", "state": {"pipeline": "custom/mira-nf", "assay_type": "Custom MIRA-NF Influenza / SC2 pipeline", "data_format": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_opt_flip_track_stat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Off-target probe detection (tools: opt_flip_track_stat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequencetools/pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "meryl/histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "opt/flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple", "opt/stat": "stat summarizes opt binding predictions", "opt_flip_track_stat": "Off-target probe detection"}}, "target": "opt_flip_track_stat", "target_idx": 4}
{"id": "samplesheet_arch_cancer_longitudinal_4_2", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Serial plasma cfDNA and biopsy FASTQs across treatment intervals?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_expected_cells_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_5_2", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pre-aligned BAM variant calling pipeline.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "schema_std_pixelator_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pixelator", "assay": "pixelator pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/pixelator (Pipeline to generate Proximity Network Assay data with Pixel)?", "criteria": {"sample,bundle,image": null, "id,raw_file": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null}}, "target": "sample,fastq_1,fastq_2,pool,hash_index", "target_idx": 2}
{"id": "mod_hamronization_summarize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to summarize and combine all hAMRonization reports into a single file (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization_summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "eido_validate": "Validate samplesheet or PEP config against a schema", "variantextractor": "Deterministic and standard extractor of SNVs, indels and structural variants (SVs)\nfrom VCF files. Homogenizes", "hamronization_fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "hamronization_abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification"}}, "target": "hamronization_summarize", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_2_47", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_0_1", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_47", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_retry_errorstrategy_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_ripgrep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ripgrep recursively searches directories for a regex pattern (tools: ripgrep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pneumocat": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment", "yara_mapper": "Align reads to a reference genome using YARA", "ripgrep": "ripgrep recursively searches directories for a regex pattern", "macsyfinder_search": "Search for macromolecular systems in protein datasets using MacSyFinder"}}, "target": "ripgrep", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_23", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "field_constraint_fastq_2_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "field_constraint_status_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "format: file-path": null, "enum: [auto, forward, reverse]": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_entrezdirect_esummary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries an NCBI database using Unique Identifier(s) (tools: entrezdirect)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/sratoolsncbisettings": "Test for the presence of suitable NCBI settings or create them on the fly.", "csvtk/join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "entrezdirect/esummary": "Queries an NCBI database using Unique Identifier(s)", "goat/taxonsearch": "Query metadata for any taxon across the tree of life.", "verifybamid/verifybamid": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig"}}, "target": "entrezdirect/esummary", "target_idx": 2}
{"id": "pipe_all101_seqsubmit_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for seqsubmit analysis? Specific context: nf-core pipeline for data submission to ENA. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "seqsubmit": "nf-core pipeline for data submission to ENA", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo"}}, "target": "seqsubmit", "target_idx": 3}
{"id": "mod_mcstaging_macsima2mc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO. (tools: macsima2mc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ilastik_pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "gatk4_samtofastq": "Converts BAM/SAM file to FastQ format", "baysor_run": "Bayesian segmentation of spatial transcriptomics data.", "mcstaging_macsima2mc": "Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO.", "bioformats2raw": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible "}}, "target": "mcstaging_macsima2mc", "target_idx": 3}
{"id": "mod_opt_stat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: stat summarizes opt binding predictions (tools: opt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools_dedup": null, "sentieon_hsmetrics": null, "td2_longorfs": null, "opt_stat": null, "opt_flip_track_stat": null}}, "target": "opt_stat", "target_idx": 3}
{"id": "subworkflow_pkg_deepvariant_1", "category": "subworkflow_packaging", "state": {"subworkflow": "DEEPVARIANT", "modules": ["deepvariant/makeexamples", "deepvariant/callvariants", "deepvariant/postprocessvariants"], "description": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data"}, "question": {"type": "choice", "instructions": "How should DEEPVARIANT (deepvariant/makeexamples, deepvariant/callvariants, deepvariant/postprocessvariants) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow deepvariant": null, "Local subworkflow DEEPVARIANT": null}}, "target": "Use nf-core subworkflow deepvariant", "target_idx": 2}
{"id": "noul_deprecated_dsl1_set_keyword_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_fastqe_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data. (tools: fastqe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae_trim": null, "fasta_index_dna": null, "openmsthirdparty_cometadapter": null, "fastqe": null, "busco_plot": null}}, "target": "fastqe", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_wgs_1_5", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "template": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "resource_bbmap_pileup_1", "category": "resource_profiling", "state": {"process": "BBMAP_PILEUP", "tool": "bbmap/pileup", "description": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_PILEUP (Calculates per-scaffold or per-base coverage information from an unsorted sam or) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_gather_bcftools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_GATHER_BCFTOOLS", "modules": ["bcftools/sort", "bcftools/concat", "htslib/bgziptabix"], "description": "Concatenate several VCF files using bcftools concat."}, "question": {"type": "choice", "instructions": "How should VCF_GATHER_BCFTOOLS (bcftools/sort, bcftools/concat, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow VCF_GATHER_BCFTOOLS": null, "Use nf-core subworkflow vcf_gather_bcftools": null}}, "target": "Use nf-core subworkflow vcf_gather_bcftools", "target_idx": 3}
{"id": "pipe_all101_oncoanalyser_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for cancer analysis? Specific context: A comprehensive cancer DNA/RNA analysis and reporting pipeline. Topics: cancer, clinical, ctdna, dna, exome, longitudinal. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "metapep": "From metagenomes to epitopes and beyond", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]"}}, "target": "oncoanalyser", "target_idx": 1}
{"id": "resource_baysor_preview_0", "category": "resource_profiling", "state": {"process": "BAYSOR_PREVIEW", "tool": "baysor/preview", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_PREVIEW (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bowtie2_align_1", "category": "resource_profiling", "state": {"process": "BOWTIE2_ALIGN", "tool": "bowtie2/align", "description": "Align reads to a reference genome using bowtie2"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_ALIGN (Align reads to a reference genome using bowtie2) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_metaboigniter_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for identification. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqsubmit": "nf-core pipeline for data submission to ENA", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri"}}, "target": "metaboigniter", "target_idx": 4}
{"id": "mod_diamond_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculate clusters of highly similar sequences (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "custom_clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "rclone_copy": "Copy files or directories between local and/or remote storage using Rclone", "diamond_cluster": "calculate clusters of highly similar sequences", "pydamage_filter": "Damage parameter estimation for ancient DNA"}}, "target": "diamond_cluster", "target_idx": 3}
{"id": "resource_bedtools_complement_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COMPLEMENT", "tool": "bedtools/complement", "description": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COMPLEMENT (Returns all intervals in a genome that are not covered by at least one interval ) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_4_0", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs?", "criteria": {"sample,otu_table": null, "sample,fastq_1": null, "sample,primer_fwd,primer_rev": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: ATAC-seq chromatin accessibility with biological replicates)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ATAC-seq chromatin accessibility with biological replicates with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "mod_gget_gget_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic databases. gget consists of a collection of separate but interoperable modules, each designed to facilitate one type of database querying in a single line of code. (tools: gget)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gget/gget": "gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic da", "parabricks/deepvariant": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating deepvariant.", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "bowtie/align": "Align reads to a reference genome using bowtie", "bedtools/complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}}, "target": "gget/gget", "target_idx": 0}
{"id": "field_constraint_fastq_2_0_11", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_4_2", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Aligned BAM files?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/bacass --input samplesheet.csv (Assay: Hybrid bacterial assembly combining short Illumina and long Nanopore reads)", "question": {"type": "choice", "instructions": "Which columns are standard for Hybrid bacterial assembly combining short Illumina and long Nanopore reads input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_metabuli_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a database for classification with metabuli from FASTA files and a taxonomy (tools: metabuli)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metabuli_build": "Builds a database for classification with metabuli from FASTA files and a taxonomy", "antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "blast_makeblastdb": "Builds a BLAST database", "learnmsa_align": "Align sequences using learnMSA", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq"}}, "target": "metabuli_build", "target_idx": 0}
{"id": "pipe_all101_bactmap_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for bacteria. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "callingcards": "A pipeline for processing calling cards data", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "bactmap", "target_idx": 3}
{"id": "schema_std_spatialaxe_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "description": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/spatialaxe?", "criteria": {"sample,bundle,image": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "sample_id,bam,vcf,library_id,lane": null}}, "target": "sample,bundle,image", "target_idx": 0}
{"id": "resource_bbmap_repair_5", "category": "resource_profiling", "state": {"process": "BBMAP_REPAIR", "tool": "bbmap/repair", "description": "Re-pairs reads that became disordered or had some mates eliminated."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_REPAIR (Re-pairs reads that became disordered or had some mates eliminated.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_3_1", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "template": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Environmental community metatranscriptomics de novo assembly with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "pipe_all101_mag_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Assembly and binning of metagenomes. Topics: annotation, assembly, binning, long-read-sequencing, metagenomes, metagenomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demo": null, "readsimulator": null, "pathogensurveillance": null, "spatialaxe": null, "mag": null, "hadge": null, "metapep": null, "taxprofiler": null}}, "target": "mag", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_0_1", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_0_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "resource_bedtools_sort_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SORT", "tool": "bedtools/sort", "description": "Sorts a feature file by chromosome and other criteria."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SORT (Sorts a feature file by chromosome and other criteria.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_medium", "target_idx": 1}
{"id": "mod_seqtk_mergepe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Interleave pair-end reads from FastQ files (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc/splitbam": "Split BAM file based on gene list in BED format", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "bedtools/merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "seqtk/mergepe": "Interleave pair-end reads from FastQ files", "oatk": "An nf-core module for the OATK"}}, "target": "seqtk/mergepe", "target_idx": 3}
{"id": "mod_universc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to run UniverSC an open-source pipeline to demultiplex and process single-cell RNA-Seq data (tools: universc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bclconvert": "Demultiplex Illumina BCL files", "mgikit_demultiplex": "Demultiplex MGI fastq files", "universc": "Module to run UniverSC an open-source pipeline to demultiplex and process single-cell RNA-Seq data", "seqsero2": "Salmonella serotype prediction from reads and assemblies", "multivcfanalyzer": "SNP table generator from GATK UnifiedGenotyper with functionality geared for aDNA"}}, "target": "universc", "target_idx": 2}
{"id": "schema_std_mag_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "description": "Assembly and binning of metagenomes", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/mag?", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "sample,fastq_1": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,seq_data,pbi,start_from": null}}, "target": "sample,run,group,short_reads_1,short_reads_2", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_4_3", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "template": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs?", "criteria": {"sample,cpg,methylation": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_macsyfinder_search_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search for macromolecular systems in protein datasets using MacSyFinder (tools: macsyfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macsyfinder_search": "Search for macromolecular systems in protein datasets using MacSyFinder", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "mirdeep2_mapper": "miRDeep2 Mapper is a tool that prepares deep sequencing reads for downstream miRNA detection by collapsing rea", "sentieon_tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.", "alignoth": "Creating alignment plots from bam files"}}, "target": "macsyfinder_search", "target_idx": 0}
{"id": "resource_angsd_gl_0", "category": "resource_profiling", "state": {"process": "ANGSD_GL", "tool": "angsd/gl", "description": "Calculated genotype likelihoods from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_GL (Calculated genotype likelihoods from BAM files.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_channel_collect_operator_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_6", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_seqkit_translate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Translate DNA/RNA to protein sequence (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/translate": "Translate DNA/RNA to protein sequence", "seqkit/grep": "Select sequences from a large file based on name/ID", "seqkit/pair": "match up paired-end reads from two fastq files", "smncopynumbercaller": "tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion ", "prinseqplusplus": "PRINSEQ++ is a C++ implementation of the prinseq-lite.pl program. It can be used to filter, reformat or trim g"}}, "target": "seqkit/translate", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_5_4", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/metatdenovo, determine the input samplesheet column structure for: Environmental community metatranscriptomics de novo assembly.", "criteria": {"sample,bam": null, "sample,rrna_fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "mod_transrate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reference-free and reference-based quality assessment of de novo transcriptome\nassemblies. Only sequence-based (--assembly) and reference-based (--reference) metrics\nare supported. Read-based metrics (--left/--right) are not: they hard-require the\n`bam-read` binary, which isn't published on any conda channel, and their aligner\n(snap-aligner, pinned to an old dev build) segfaults building an index for at least\nsmall test genomes. (tools: transrate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"transrate": "Reference-free and reference-based quality assessment of de novo transcriptome\nassemblies. Only sequence-based", "mudskipper/bulk": "Convert genomic BAM/SAM files to transcriptomic BAM/RAD files.", "pydamage/filter": "Damage parameter estimation for ancient DNA", "busco/generateplot": "BUSCO plot generation tool", "suppa/psiperisoform": "Calculate PSI values for transcript isoforms using SUPPA"}}, "target": "transrate", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_23", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_17", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "subworkflow_pkg_bam_impute_stitch_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_STITCH", "modules": ["stitch", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using STITCH software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_STITCH (stitch, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_impute_stitch": null, "Local subworkflow BAM_IMPUTE_STITCH": null}}, "target": "Use nf-core subworkflow bam_impute_stitch", "target_idx": 2}
{"id": "subworkflow_pkg_bam_create_som_pon_gatk_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CREATE_SOM_PON_GATK", "modules": ["gatk4/mutect2", "gatk4/genomicsdbimport", "gatk4/createsomaticpanelofnormals", "gatk4/mergevcfs", "gatk4/mergemutectstats"], "description": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a genomicsdbworkspace using genomicsdbimport, then use this to create a panel of normals using createsomaticpanelofnormals."}, "question": {"type": "choice", "instructions": "How should BAM_CREATE_SOM_PON_GATK (gatk4/mutect2, gatk4/genomicsdbimport, gatk4/createsomaticpanelofnormals, gatk4/mergevcfs, gatk4/mergemutectstats) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_create_som_pon_gatk": null, "Local subworkflow BAM_CREATE_SOM_PON_GATK": null}}, "target": "Use nf-core subworkflow bam_create_som_pon_gatk", "target_idx": 2}
{"id": "mod_seacr_callpeak_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call peaks using SEACR on sequenced reads in bedgraph format (tools: seacr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer/makeucscfile": "Create a UCSC bed graph with the HOMER suite", "seacr/callpeak": "Call peaks using SEACR on sequenced reads in bedgraph format", "sam2lca/analyze": "Calling lowest common ancestors from multi-mapped reads in SAM/BAM/CRAM files", "presto/filterseq": "Filter reads by quality score.", "homer/annotatepeaks": "Annotate peaks with HOMER suite"}}, "target": "seacr/callpeak", "target_idx": 1}
{"id": "schema_std_metaboigniter_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/metaboigniter. Description: Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/metaboigniter.", "criteria": {"vcf,fasta,genome,site,source": null, "sample,type,level,msfile": null, "sample_id,mapped,index,file_type": null, "sample,fastq_1,fastq_2,barcode_details": null}}, "target": "sample,type,level,msfile", "target_idx": 1}
{"id": "mod_vsearch_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength). (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"singlem_dbdownload": "Download the SingleM metapackage database used for metagenome profiling", "vsearch_usearchglobal": "Compare target sequences to fasta-formatted query sequences using global pairwise alignment.", "vsearch_sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).", "localcdsearch_download": "A command-line tool for downloading databases for local protein domain annotation using NCBI's Conserved Domai", "vsearch_fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format."}}, "target": "vsearch_sort", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_download_prefetch_fasterqdump_sratools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS", "modules": ["custom/sratoolsncbisettings", "sratools/prefetch", "sratools/fasterqdump"], "description": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA)."}, "question": {"type": "choice", "instructions": "How should FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS (custom/sratoolsncbisettings, sratools/prefetch, sratools/fasterqdump) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS": null, "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools": null}}, "target": "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools", "target_idx": 3}
{"id": "mod_hmmcopy_gccounter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta reference (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmcopy_mapcounter": null, "taxonkit_lineage": null, "cnvkit_reference": null, "hmmcopy_gccounter": null, "kmcp_profile": null}}, "target": "hmmcopy_gccounter", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_25", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "pipe_all101_coproid_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for adna. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom"}}, "target": "coproid", "target_idx": 5}
{"id": "mod_rpbp_selectperiodicoffsets_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produced upstream. For each\nread length, the offset with the highest periodicity Bayes-factor mean\nis selected - this is the offset that, when added to a read's 5' end,\nis estimated to land closest to the ribosomal P-site (the codon being\ndecoded). Downstream, these offsets are used to convert raw read\n5'-end coordinates into P-site positions when counting reads against\ncandidate ORFs.\n\nEmits one row per read length (length, best offset, supporting Bayes\nfactor statistics). The next step\n(`rpbp/getperiodiclengthsoffsets`) filters this table to the high-quality\npairs that pass user-specified count / signal thresholds before\nP-site counting in `rpbp/extractorfprofiles`. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "rpbp/selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ", "rpbp/getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "gatk4/indexfeaturefile": "Creates an index for a feature file, e.g. VCF or BED file."}}, "target": "rpbp/selectperiodicoffsets", "target_idx": 1}
{"id": "pipe_all101_genomeassembler_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads. Topics: genome-assembly. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri"}}, "target": "genomeassembler", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_5", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_biscuit_mergecg_2", "category": "resource_profiling", "state": {"process": "BISCUIT_MERGECG", "tool": "biscuit/mergecg", "description": "Merges methylation information for opposite-strand C's in a CpG context"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_MERGECG (Merges methylation information for opposite-strand C's in a CpG context) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic cancer variant calling with tumor-normal pairs)", "question": {"type": "choice", "instructions": "Which columns are standard for Somatic cancer variant calling with tumor-normal pairs input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_rnavar_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: gatk4 RNA variant calling pipeline. Topics: gatk4, rna, rnaseq, variant-calling, worflow. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"smrnaseq": null, "rnaseq": null, "slamseq": null, "sopa": null, "rnavar": null}}, "target": "rnavar", "target_idx": 4}
{"id": "noul_dynamic_resource_allocation_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_tiff_segmentation_vpt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool (tools: tiff_segmentation_vpt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ilastik/pixelclassification": null, "unicycler": null, "tiff_segmentation_vpt": null, "goatools/findenrichment": null, "baysor/run": null}}, "target": "tiff_segmentation_vpt", "target_idx": 2}
{"id": "mod_picard_collectwgsmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics about coverage and performance of whole genome sequencing (WGS) experiments. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "csvtk/concat": "Concatenate two or more CSV (or TSV) tables into a single table", "bwa/samse": "Convert bwa SA coordinate file to SAM format", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "picard/collectwgsmetrics": "Collect metrics about coverage and performance of whole genome sequencing (WGS) experiments."}}, "target": "picard/collectwgsmetrics", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_1_30", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_seqkit_split2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split single or paired-end fastq.gz files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": null, "csvtk/split": null, "whatshap/phase": null, "seqkit/split2": null, "fusionreport/detect": null}}, "target": "seqkit/split2", "target_idx": 3}
{"id": "mod_eido_validate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validate samplesheet or PEP config against a schema (tools: validate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eido_convert": "Convert any PEP project or Nextflow samplesheet to any format", "eido_validate": "Validate samplesheet or PEP config against a schema", "deeparg_predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "meryl_histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "fq_lint": "fq lint is a FASTQ file pair validator."}}, "target": "eido_validate", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_20", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "pipe_all101_sopa_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Nextflow version of Sopa - spatial omics pipeline and analysis. Topics: segmentation, spatial-omics, spatial-proteomics, spatial-transcriptomics, spatialdata. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "seqsubmit": "nf-core pipeline for data submission to ENA", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]"}}, "target": "sopa", "target_idx": 4}
{"id": "field_constraint_fastq_1_0_14", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "mod_bcftools_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge VCF files (tools: merge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_merge": "Merge VCF files", "atlas_call": "generate VCF file from a BAM file using various calling methods", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "bcl_demultiplex": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq", "diann_insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so"}}, "target": "bcftools_merge", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/metatdenovo --input samplesheet.csv (Assay: Environmental community metatranscriptomics de novo assembly)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Environmental community metatranscriptomics de novo assembly with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/chipseq) for ChIP-seq with IP and input control design. Input files: Paired-end FASTQ reads for immunoprecipitation and input chromatin.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,antibody,control": null, "sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 0}
{"id": "pipe_all101_bactmap_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for bacteria analysis? Specific context: A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences. Topics: bacteria, bacterial, bacterial-genome-analysis, genomics, mapping, phylogeny. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "seqsubmit": "nf-core pipeline for data submission to ENA", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "bactmap", "target_idx": 6}
{"id": "field_constraint_status_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "pipe_all101_seqsubmit_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: nf-core pipeline for data submission to ENA. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "seqsubmit": "nf-core pipeline for data submission to ENA", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n"}}, "target": "seqsubmit", "target_idx": 1}
{"id": "field_constraint_phenotype_1_5", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_5_5", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "template": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/chipseq, determine the input samplesheet column structure for: ChIP-seq with IP and input control design.", "criteria": {"sample,antibody,control": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "mod_samtools_depth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the depth at each position or region. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/tab2fx": "Convert tabular format (first two/three columns) to FASTA/Q format.", "sentieon/tnfilter": "Filters the raw output of sentieon/tnhaplotyper2.", "metabat2/metabat2": "Metagenome binning of contigs", "deeptools/bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig ", "samtools/depth": "Computes the depth at each position or region."}}, "target": "samtools/depth", "target_idx": 4}
{"id": "resource_bedops_gtf2bed_2", "category": "resource_profiling", "state": {"process": "BEDOPS_GTF2BED", "tool": "bedops/gtf2bed", "description": "Convert gtf format to bed format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_GTF2BED (Convert gtf format to bed format) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_antismash_antismashlitedownloaddatabases_4", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES", "tool": "antismash/antismashlitedownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_cobrameta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining of contigs fragmented during de novo assembly. (tools: cobra-meta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"optitype": "Perform HLA-I typing of sequencing data", "drep_compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "quast": "Quality Assessment Tool for Genome Assemblies", "cobrameta": "A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining o", "vclust_cluster": "Vclust cluster performs threshold-based clustering by assigning a genome sequence to a cluster if its similari"}}, "target": "cobrameta", "target_idx": 3}
{"id": "schema_std_eager_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/eager. Description: A fully reproducible and state-of-the-art ancient DNA analysis pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/eager.", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample_id,bam,vcf,library_id,lane": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "sample_id,bam,vcf,library_id,lane", "target_idx": 2}
{"id": "mod_pharmcat_matcher_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to be used in the PharmCAT pipeline, it can also be run independently.\nThe Named Allele Matcher does not currently support structural variants, including gene copy\nnumber. If structural variants are detected in the VCF data, it will be ignored and a warning\nwill be issued.\nIf it detects more than the expected number of alleles in the GT column of the VCF, only the\nfirst two alleles will be used and a warning will be issued. On haploid chromosomes, only\nthe first allele will be used. (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/annotate": "Add or remove annotations.", "atlas/call": "generate VCF file from a BAM file using various calling methods", "pharmcat/matcher": "The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to", "longstitch": "\"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - ", "picard/markduplicates": "Locate and tag duplicate reads in a BAM file"}}, "target": "pharmcat/matcher", "target_idx": 2}
{"id": "mod_famsa_guidetree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Renders a guidetree in famsa (tools: famsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_phase_shapeit5": "Subworkflow to phase a reference panel VCF file using SHAPEIT5.\nThe panel is first chunked by chromosome by gl", "foldmason/createdb": "Creates a database for Foldmason.", "ampir": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ", "emboss/cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "famsa/guidetree": "Renders a guidetree in famsa"}}, "target": "famsa/guidetree", "target_idx": 4}
{"id": "pipe_all101_scnanoseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics. Topics: 10xgenomics, long-read-sequencing, nanopore, rna-seq, rnaseq, scrna-seq. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]"}}, "target": "scnanoseq", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_42", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_bamclipper_2", "category": "resource_profiling", "state": {"process": "BAMCLIPPER", "tool": "bamclipper", "description": "This module is used to clip primer sequences from your alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCLIPPER (This module is used to clip primer sequences from your alignments.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "intent_ask_question_15", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "prepare_data": null, "debug_error": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_6_0", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "INPUT_CHECK", "library_inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns are standard for Custom MIRA-NF Influenza / SC2 pipeline input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_deprecated_file_output_syntax_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_agat_spfilterfeaturefromkilllist_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": null, "tinc": null, "agat/spextractsequences": null, "agat/spfilterfeaturefromkilllist": null, "wipertools/reportgather": null}}, "target": "agat/spfilterfeaturefromkilllist", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_3_2", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Environmental community metatranscriptomics de novo assembly with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "mod_proseg_proseg2baysor_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert proseg outputs to baysor format for import to Xenium explorer (tools: proseg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "iphop/predict": "Predict phage host using iPHoP", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "ilastik/pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "dastool/dastool": "DAS Tool binning step."}}, "target": "proseg/proseg2baysor", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_9", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cancer_longitudinal_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Longitudinal cancer monitoring across multiple timepoints", "data_format": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Serial plasma cfDNA and biopsy FASTQs across treatment intervals?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "intent_debug_error_4", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "mod_kat_hist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a histogram of the number of distinct k-mers having a given frequency. (tools: kat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_buildcustom": "Build ganon database using custom reference sequences.", "kat_hist": "Creates a histogram of the number of distinct k-mers having a given frequency.", "ganon_report": "Generate a ganon report file from the output of ganon classify", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "mcstaging_imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata."}}, "target": "kat_hist", "target_idx": 1}
{"id": "resource_bowtie2_build_0", "category": "resource_profiling", "state": {"process": "BOWTIE2_BUILD", "tool": "bowtie2/build", "description": "Builds bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_BUILD (Builds bowtie index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_ribotish_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality control of riboseq bam data (tools: ribotish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gedi_indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "ribotish_predict": "Quality control of riboseq bam data", "gedi_price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "skesa": "Assemble microbial genomes from short-read FASTQ files into contigs in FASTA format using SKESA.", "survivor_bedpetovcf": "Converts a bedpe file to a VCF file (beta version)"}}, "target": "ribotish_predict", "target_idx": 1}
{"id": "resource_amps_5", "category": "resource_profiling", "state": {"process": "AMPS", "tool": "amps", "description": "Post-processing script of the MaltExtract component of the HOPS package"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPS (Post-processing script of the MaltExtract component of the HOPS package) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_4_4", "category": "samplesheet_schema", "state": {"technology": "3D Chromatin Structure", "workflow_entry": "FASTQC", "library_inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_3_1", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "template": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Data-Independent Acquisition (DIA) quantitative mass spectrometry with entry step INPUT_CHECK.", "criteria": {"sample,raw_file,condition": null, "sample,peptides_tsv": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "mod_agat_convertgff2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes a GFF3 file and converts to a bed12 file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "genotyphi_parse": "Genotype Salmonella Typhi from Mykrobe results", "pairix": "a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates"}}, "target": "agat_convertgff2bed", "target_idx": 2}
{"id": "mod_wipertools_reportgather_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that merges wiping reports generated by wipertools_fastqwiper (tools: reportgather)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wipertools/reportgather": "A tool of the wipertools suite that merges wiping reports generated by wipertools_fastqwiper", "nanoplot": "Run NanoPlot on nanopore-sequenced reads", "hypo": "Assembly polisher using short (and long) reads", "ganon/report": "Generate a ganon report file from the output of ganon classify", "pharmcat/reporter": "The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescri"}}, "target": "wipertools/reportgather", "target_idx": 0}
{"id": "mod_annotsv_installannotations_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Install the AnnotSV annotations (tools: annotsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlasgeneannotationmanipulation/gtf2featureannotation": null, "annotsv/annotsv": null, "annotsv/installannotations": null, "homer/annotatepeaks": null, "nextgenmap": null}}, "target": "annotsv/installannotations", "target_idx": 2}
{"id": "mod_bam_dedup_stats_samtools_umicollapse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: umicollapse, index BAM file and run samtools stats, flagstat and idxstats (tools: bam_dedup_stats_samtools_umicollapse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "freyja/demix": "specify the relative abundance of each known haplotype", "bam_dedup_stats_samtools_umicollapse": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats", "fgbio/groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever "}}, "target": "bam_dedup_stats_samtools_umicollapse", "target_idx": 2}
{"id": "schema_std_proteinannotator_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinannotator", "description": "Generation of sequence-level annotations for amino acid sequences", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/proteinannotator?", "criteria": {"id,fasta": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample,bam,bai,cram,crai": null}}, "target": "id,fasta", "target_idx": 0}
{"id": "pipe_all101_cageseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags.. Topics: cage, cage-seq, cageseq-data, gene-expression, rna. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"spatialaxe": null, "hicar": null, "cageseq": null, "imcyto": null, "reportho": null}}, "target": "cageseq", "target_idx": 2}
{"id": "mod_picard_scatterintervalsbyns_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into intervals of alternating regions of N and ACGT bases (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trnascanse": "Detection of tRNA sequences using covariance models", "bed_scatter_bedtools": "Scatters inputted BED files by the amount specified.\nThe configuration in nextflow.config should be added to y", "gatk4_intervallisttools": "Splits the interval list file into unique, equally-sized interval files and place it under a directory", "stacks_refmap": "ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available.", "picard_scatterintervalsbyns": "Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into inte"}}, "target": "picard_scatterintervalsbyns", "target_idx": 4}
{"id": "mod_pypgx_runngspipeline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PyPGx pharmacogenomics genotyping pipeline for NGS data. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk/concat": "Concatenate two or more CSV (or TSV) tables into a single table", "folddisco/query": "Search a prebuilt folddisco index for a discontinuous residue motif in a query protein structure", "pypgx/computecontrolstatistics": "Compute summary statistics for control gene from BAM files.", "gatk4/concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "pypgx/runngspipeline": "PyPGx pharmacogenomics genotyping pipeline for NGS data."}}, "target": "pypgx/runngspipeline", "target_idx": 4}
{"id": "samplesheet_arch_ancient_dna_eager_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/eager --input samplesheet.csv (Assay: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment)", "question": {"type": "choice", "instructions": "Which columns are standard for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment input samplesheet?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_bacass_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Simple bacterial assembly and annotation pipeline. Topics: assembly, bacterial-genomes, denovo, denovo-assembly, genome-assembly, hybrid-assembly. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]"}}, "target": "bacass", "target_idx": 0}
{"id": "mod_finaletoolkit_endmotifs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Measure the frequency of 5' k-mer end motifs. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit/mds": "Comnpute the Motif Diversity Score using normalized Shannon entropy\n(Jiang et al., 2020).", "finaletoolkit/endmotifs": "Measure the frequency of 5' k-mer end motifs.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "mmseqs_contig_taxonomy": "Assign taxonomy to contigs using the MMseqs2 workflow.", "bam_vcf_impute_glimpse2": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow\ntakes VCF files, phased ref"}}, "target": "finaletoolkit/endmotifs", "target_idx": 1}
{"id": "mod_artic_minion_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run the alignment/variant-call/consensus logic of the artic pipeline (tools: artic)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtools_vcftobedpe": "Convert a VCF file to a BEDPE file.", "artic_aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "artic_minion": "Run the alignment/variant-call/consensus logic of the artic pipeline", "artic_guppyplex": "Aggregates fastq files with demultiplexed reads", "gatk4_filterintervals": "Filters intervals based on annotations and/or count statistics."}}, "target": "artic_minion", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/cageseq --input samplesheet.csv (Assay: CAGE-seq 5-prime capped transcript end sequencing)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CAGE-seq 5-prime capped transcript end sequencing with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_proteus_readproteingroups_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: reads a maxQuant proteinGroups file with Proteus (tools: proteus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond_cluster": "calculate clusters of highly similar sequences", "bcftools_sort": "Sorts VCF files", "proteus_readproteingroups": "reads a maxQuant proteinGroups file with Proteus", "diann_insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "samtools_stats": "Produces comprehensive statistics from SAM/BAM/CRAM file"}}, "target": "proteus_readproteingroups", "target_idx": 2}
{"id": "resource_barrnap_0", "category": "resource_profiling", "state": {"process": "BARRNAP", "tool": "barrnap", "description": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BARRNAP (barrnap uses a hmmer profile to find rrnas in reads or contig fasta files) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bamcmp_5", "category": "resource_profiling", "state": {"process": "BAMCMP", "tool": "bamcmp", "description": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For instance, filtering out mouse reads from patient derived xenograft mouse models (PDX)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCMP (Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and ) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bamutil_trimbam_3", "category": "resource_profiling", "state": {"process": "BAMUTIL_TRIMBAM", "tool": "bamutil/trimbam", "description": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_TRIMBAM (trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_fgumi_duplexmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects a suite of metrics to QC duplex sequencing data (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo/merge": "Merge STR profiles into a multi-sample STR profile", "vcflib/vcffixup": "Generates a VCF stream where AC and NS have been generated for each record using sample genotypes.", "fgbio/collectduplexseqmetrics": "Collects a suite of metrics to QC duplex sequencing data.", "fgumi/dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "fgumi/duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data"}}, "target": "fgumi/duplexmetrics", "target_idx": 4}
{"id": "samplesheet_arch_viral_ont_single_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral genome sequencing on Oxford Nanopore MinION / GridION)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral genome sequencing on Oxford Nanopore MinION / GridION with entry step NANOPLOT.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "resource_bamtools_split_3", "category": "resource_profiling", "state": {"process": "BAMTOOLS_SPLIT", "tool": "bamtools/split", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_SPLIT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_samtools_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "helitronscanner/scan": "HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes", "custom/getchromsizes": "Generates a FASTA file of chromosome sizes and a fasta index file", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "samtools/index": "Index SAM/BAM/CRAM file"}}, "target": "samtools/index", "target_idx": 4}
{"id": "resource_amplify_predict_0", "category": "resource_profiling", "state": {"process": "AMPLIFY_PREDICT", "tool": "amplify/predict", "description": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPLIFY_PREDICT (AMPlify is an attentive deep learning model for antimicrobial peptide prediction) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_subsample_fq_salmon_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SUBSAMPLE_FQ_SALMON", "modules": ["fq/subsample", "salmon/quant", "salmon/index"], "description": "Subsample fastq"}, "question": {"type": "choice", "instructions": "How should FASTQ_SUBSAMPLE_FQ_SALMON (fq/subsample, salmon/quant, salmon/index) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_SUBSAMPLE_FQ_SALMON": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_subsample_fq_salmon": null}}, "target": "Use nf-core subworkflow fastq_subsample_fq_salmon", "target_idx": 3}
{"id": "resource_bowtie2_align_0", "category": "resource_profiling", "state": {"process": "BOWTIE2_ALIGN", "tool": "bowtie2/align", "description": "Align reads to a reference genome using bowtie2"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_ALIGN (Align reads to a reference genome using bowtie2) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_mafft_align_2", "category": "subworkflow_packaging", "state": {"subworkflow": "MAFFT_ALIGN", "modules": ["mafft/align"], "description": "Prepare channels for running MAFFT/align"}, "question": {"type": "choice", "instructions": "How should MAFFT_ALIGN (mafft/align) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow MAFFT_ALIGN": null, "Use nf-core subworkflow mafft_align": null}}, "target": "Use nf-core subworkflow mafft_align", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_2", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_phantompeakqualtools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: \"This package computes informative enrichment and quality measures\nfor ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq data. It can also be used\nto obtain robust estimates of the predominant fragment length or\ncharacteristic tag shift values in these assays.\" (tools: phantompeakqualtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macs3_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "trimgalore": "A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith e", "idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "phantompeakqualtools": "\"This package computes informative enrichment and quality measures\nfor ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq "}}, "target": "phantompeakqualtools", "target_idx": 4}
{"id": "mod_portello_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transfer HiFi read mappings from their own assembly contigs to a standard reference (tools: portello)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shasta": "The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using DNA reads g", "ale": "ALE: assembly likelihood estimator.", "sylph/query": "Sylph query command for querying genome databases against reads/metagenomes", "portello": "Transfer HiFi read mappings from their own assembly contigs to a standard reference", "abacas": "Contiguate draft genome assembly"}}, "target": "portello", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "assay_type": "RNA gene fusion detection (Arriba, STAR-Fusion)", "data_format": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_4_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FastQ reads per sample?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_angsd_dosaf_3", "category": "resource_profiling", "state": {"process": "ANGSD_DOSAF", "tool": "angsd/dosaf", "description": "Estimate site allele frequencies from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOSAF (Estimate site allele frequencies from BAM files.) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_strandedness_3_9", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"format: file-path": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "resource_blast_blastdbcmd_0", "category": "resource_profiling", "state": {"process": "BLAST_BLASTDBCMD", "tool": "blast/blastdbcmd", "description": "Retrieve entries from a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTDBCMD (Retrieve entries from a BLAST database) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_fasta_index_bismark_bwameth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate index files from reference fasta for bismark and bwameth (tools: fasta_index_bismark_bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/report": "Collects bismark alignment reports", "proovframe/fix": "frame-shift correction for long read (meta)genomics - fix frameshifts in reads", "paragraph/vcf2paragraph": "Convert a VCF file to a JSON graph", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "fasta_index_bismark_bwameth": "Generate index files from reference fasta for bismark and bwameth"}}, "target": "fasta_index_bismark_bwameth", "target_idx": 4}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_7_1", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "template": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "schema_std_multiplesequencealign_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/multiplesequencealign", "assay": "multiplesequencealign pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/multiplesequencealign (A pipeline to run and systematically evaluate Multiple Seque)?", "criteria": {"id,fasta,sequence": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "sample,nuclear_image,spot_table,membrane_image": null, "id,fasta,reference,optional_data,template": null}}, "target": "id,fasta,reference,optional_data,template", "target_idx": 3}
{"id": "mod_svanalyzer_svbenchmark_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SVbenchmark compares a set of “test” structural variants in VCF format to a known truth set (also in VCF format) and outputs estimates of sensitivity and specificity. (tools: svanalyzer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmcopy/gccounter": "gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta", "svanalyzer/svbenchmark": "SVbenchmark compares a set of “test” structural variants in VCF format to a known truth set (also in VCF forma", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "octopusv/plot": "Plot structural variant statistics using octopusv stat output", "octopusv/plotcircos": "Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file."}}, "target": "svanalyzer/svbenchmark", "target_idx": 1}
{"id": "noul_retry_errorstrategy_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_gatk4_splitcram_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits CRAM files efficiently by taking advantage of their container based structure (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamreadcount": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencin", "pychopper": "Identify, orient and trim nanopore cDNA reads", "biobambam/bammarkduplicates2": "Locate and tag duplicate reads in a BAM file", "gatk4/splitcram": "Splits CRAM files efficiently by taking advantage of their container based structure", "tidk/plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`"}}, "target": "gatk4/splitcram", "target_idx": 3}
{"id": "pipe_all101_methylseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair. Topics: bisulfite-sequencing, dna-methylation, em-seq, epigenome, epigenomics, methyl-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T"}}, "target": "methylseq", "target_idx": 0}
{"id": "field_constraint_bam_1_3", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "mod_ssuissero_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotype prediction of Streptococcus suis assemblies (tools: ssuissero)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format", "pindel_pindel": "Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and", "ssuissero": "Serotype prediction of Streptococcus suis assemblies", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "ssuissero", "target_idx": 3}
{"id": "subworkflow_pkg_orftable_fasta_gtf_buildorfcatalogue_2", "category": "subworkflow_packaging", "state": {"subworkflow": "ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE", "modules": ["custom/orfnormalise", "custom/orfmerge", "bedtools/getfasta", "seqkit/translate", "mmseqs/easycluster", "custom/orfcollapse"], "description": "Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller"}, "question": {"type": "choice", "instructions": "How should ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE (custom/orfnormalise, custom/orfmerge, bedtools/getfasta, seqkit/translate, mmseqs/easycluster, custom/orfcollapse) be structured in DSL2?", "criteria": {"Local subworkflow ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE": null, "Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_snpeff_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "ensemblvep/vep", "snpeff/download", "snpeff/snpeff", "htslib/bgziptabix", "bcftools/pluginscatter", "bcftools/concat", "bcftools/sort"], "description": "Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkflow uses the scatter-gather method to run VEP/snpEff in parallel to increase throughput. The input VCF is split into multiple smaller VCFs of fixed size, which are annotated separately and concatenated back together to a single output file per sample. Only VCF/BCF outputs are currently supported."}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP_SNPEFF (ensemblvep/download, ensemblvep/vep, snpeff/download, snpeff/snpeff, htslib/bgziptabix, bcftools/pluginscatter, bcftools/concat, bcftools/sort) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff": null, "Local subworkflow VCF_ANNOTATE_ENSEMBLVEP_SNPEFF": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff", "target_idx": 1}
{"id": "resource_admixture_4", "category": "resource_profiling", "state": {"process": "ADMIXTURE", "tool": "admixture", "description": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datasets, where the individuals are unrelated (for example, the individuals in a case-control association study)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADMIXTURE (ADMIXTURE is a program for estimating ancestry in a model-based manner from larg) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_2_44", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "local_subworkflow_nextclade_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should NEXTCLADE (nextclade/run) be built?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow nextclade": null, "Local subworkflow NEXTCLADE": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 3}
{"id": "mod_gedi_indexgenome_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction (tools: gedi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"minimac4/compressref": "Compression of a reference panel for genotype imputation to `.msav` format", "gedi/price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "custom/summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a", "gedi/indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}}, "target": "gedi/indexgenome", "target_idx": 3}
{"id": "pipe_all101_lsmquant_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline for processing and analysis of light-sheet microscopy images.. Topics: 3dunet, image-analysis, image-processing, light-sheet-microcopy, segmentation, stitching. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods."}}, "target": "lsmquant", "target_idx": 2}
{"id": "mod_regenie_splitl0_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rrnatranscripts": "Ribosomal RNA extraction from a GTF file.", "regenie/splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "regenie/runl0": "Run one REGENIE step 1 level-0 job from a split master file", "scvitools/solo": "Detect doublets in single-cell RNA-Seq data", "regenie/step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions"}}, "target": "regenie/splitl0", "target_idx": 1}
{"id": "mod_gridss_generateponbedpe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/call": null, "mobsuite/recon": null, "sentieon/staralign": null, "gridss/generateponbedpe": null, "gridss/extractoverlappingfragments": null}}, "target": "gridss/generateponbedpe", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_19", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_fgumi_duplexmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects a suite of metrics to QC duplex sequencing data (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data", "fgbio_collectduplexseqmetrics": "Collects a suite of metrics to QC duplex sequencing data.", "preseq_ccurve": "Software for predicting library complexity and genome coverage in high-throughput sequencing", "sentieon_applyvarcal": "Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the sec", "fgumi_clip": "Clip overlapping reads in a BAM file with fgumi"}}, "target": "fgumi_duplexmetrics", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_bwa_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWA", "modules": ["bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bwa then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWA (bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_align_bwa": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_BWA": null}}, "target": "Use nf-core subworkflow fastq_align_bwa", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_40", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_taxprofiler_shotgun_2_0", "category": "samplesheet_schema", "state": {"technology": "Metagenomics Profiling", "workflow_entry": "FASTQC", "library_inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,kraken_db": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "local_subworkflow_daisribosome_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should DAISRIBOSOME (dais) be built?", "criteria": {"Use nf-core subworkflow daisribosome": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow DAISRIBOSOME": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 3}
{"id": "resource_agat_spmergeannotations_1", "category": "resource_profiling", "state": {"process": "AGAT_SPMERGEANNOTATIONS", "tool": "agat/spmergeannotations", "description": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated names and fixes other oddities met in those files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPMERGEANNOTATIONS (This script merge different gff annotation files in one. It uses the AGAT parser) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_comet_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool (tools: comet)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wisecondorx/gender": "Returns the gender of a .npz resulting from convert, based on a Gaussian mixture model trained during the newr", "diamond/deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo", "diamond/linclust": "Fast protein sequence clustering using a greedy incremental approach", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool"}}, "target": "comet", "target_idx": 4}
{"id": "resource_barrnap_5", "category": "resource_profiling", "state": {"process": "BARRNAP", "tool": "barrnap", "description": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BARRNAP (barrnap uses a hmmer profile to find rrnas in reads or contig fasta files) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_haplocheck_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial DNA. Haplocheck also works as a proxy tool for nDNA studies and provides\nusers a graphical report to investigate the contamination further. Internally, it uses the\nHaplogrep tool, that supports rCRS and RSRS mitochondrial versions. (tools: haplocheck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep2_classify": "classification into haplogroups", "saltshaker_call": "mtDNA deletion and duplication calling downstream of mitosalt", "fcsgx_cleangenome": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome asse", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "semibin_singleeasybin": "metagenomic binning with self-supervised learning"}}, "target": "haplocheck", "target_idx": 3}
{"id": "mod_openms_idfilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters peptide/protein identification results by different criteria. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vclust/align": null, "dshbio/filtergff3": null, "openms/idfilter": null, "agat/spkeeplongestisoform": null, "agat/spfilterbyorfsize": null}}, "target": "openms/idfilter", "target_idx": 2}
{"id": "field_constraint_sex_0_9", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"pattern: ^\\S+\\.gz$": null, "format: file-path": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "mod_samtools_idxstats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reports alignment summary statistics for a BAM/CRAM/SAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op", "ltrretriever/lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric ", "gstama/polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)", "samtools/idxstats": "Reports alignment summary statistics for a BAM/CRAM/SAM file", "viennarna/rnacofold": "calculate secondary structures of two RNAs with dimerization"}}, "target": "samtools/idxstats", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_45", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_apbs_1", "category": "resource_profiling", "state": {"process": "APBS", "tool": "apbs", "description": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Boltzmann Solver). Produces electrostatic potential\nmaps and solvation energy values for large biomolecular assemblages."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to APBS (Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nus) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_strandedness_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"format: file-path": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "pipe_all101_rnasplice_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis. Topics: alternative-splicing, rna, rna-seq, splicing. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra"}}, "target": "rnasplice", "target_idx": 3}
{"id": "mod_kmcp_profile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate taxonomic profile from search results (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"apbs": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Bol", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "kmcp/profile": "Generate taxonomic profile from search results", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "bcftools/index": "Index VCF tools"}}, "target": "kmcp/profile", "target_idx": 2}
{"id": "mod_orftable_fasta_gtf_buildorfcatalogue_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller\nORF prediction tables. Chains:\n\n  1. `custom/orfnormalise` (one invocation per caller-tagged input;\n     dispatch by the per-record `caller` val) - reconciles each\n     caller's native output table into a unified BED12 + sidecar TSV.\n  2. `custom/orfmerge` (one cohort-level invocation) - class-aware\n     clustering of normalised calls across callers and samples.\n  3. `bedtools/getfasta` + `seqkit/translate` - lifts the merged BED12\n     into a catalogue AA FASTA.\n  4. `mmseqs/easycluster` + `custom/orfcollapse` (optional, `val_collapse`) -\n     clusters catalogue peptides by amino-acid identity and folds duplicate\n     small ORFs to one representative each.\n\nThe collapse identity threshold defaults to `--min-seq-id 0.9` (the GENCODE\nRibo-seq ORF catalogue convention; Mudge et al. 2022), set on\n`MMSEQS_EASYCLUSTER` in this subworkflow's `nextflow.config`. Override it via\n`ext.args` on `MMSEQS_EASYCLUSTER` in the consuming pipeline's config if a\ndifferent cutoff is wanted.\n\nSupports five callers via the per-record `caller` val: ribocode, ribotish,\nribotricer, rpbp, price. Any subset can be supplied. When `ch_orf_tables` is empty\nthe subworkflow short-circuits the merge + FASTA chain and the output\nchannels are empty.\n\nOutput meta is hardcoded to `[ id: 'cohort' ]`; downstream consumers that\nwant a different cohort id should `.map` the emitted channels or\noverride `ext.prefix` on `CUSTOM_ORFMERGE` / `BEDTOOLS_GETFASTA` /\n`SEQKIT_TRANSLATE` to control output filenames. (tools: orftable_fasta_gtf_buildorfcatalogue)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/orfmerge": "Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `cus", "picard/mergesamfiles": "Merges multiple BAM files into a single file", "orftable_fasta_gtf_buildorfcatalogue": "Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller\nORF prediction tables. Chains:\n\n  1. `", "samtools/quickcheck": "Quickly check that input files appear to be intact. Checks that beginning of the file contains a valid header ", "gedi/indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction"}}, "target": "orftable_fasta_gtf_buildorfcatalogue", "target_idx": 2}
{"id": "mod_interproscan_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces protein annotations and predictions from an amino acids FASTA file (tools: interproscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "snippy_run": "Rapid haploid variant calling", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "fairy_coverage": "Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a Meta", "interproscan": "Produces protein annotations and predictions from an amino acids FASTA file"}}, "target": "interproscan", "target_idx": 4}
{"id": "pipe_all101_chipseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze ChIP-seq peak-calling, QC and differential analysis pipeline.. Topics: chip, chip-seq, chromatin-immunoprecipitation, macs2, peak-calling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"chipseq": null, "cutandrun": null, "genomeqc": null, "methylseq": null, "demo": null}}, "target": "chipseq", "target_idx": 0}
{"id": "resource_bcftools_merge_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MERGE", "tool": "bcftools/merge", "description": "Merge VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MERGE (Merge VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bedtools_makewindows_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAKEWINDOWS", "tool": "bedtools/makewindows", "description": "Makes adjacent or sliding windows across a genome or BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAKEWINDOWS (Makes adjacent or sliding windows across a genome or BED file.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_hmmsearch_rank_fastas_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_HMMSEARCH_RANK_FASTAS", "modules": ["hmmer/hmmsearch", "hmmer/hmmrank", "seqtk/subseq"], "description": "Run hmmsearch and output separate fasta files for top scoring hits to each profile"}, "question": {"type": "choice", "instructions": "How should FASTA_HMMSEARCH_RANK_FASTAS (hmmer/hmmsearch, hmmer/hmmrank, seqtk/subseq) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_hmmsearch_rank_fastas": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_HMMSEARCH_RANK_FASTAS": null}}, "target": "Use nf-core subworkflow fasta_hmmsearch_rank_fastas", "target_idx": 0}
{"id": "resource_arriba_download_2", "category": "resource_profiling", "state": {"process": "ARRIBA_DOWNLOAD", "tool": "arriba/download", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_DOWNLOAD (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_seqkit_concat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenating multiple uncompressed sequence files together (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/concat": "Concatenating multiple uncompressed sequence files together", "emboss/cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "bcftools/concat": "Concatenate VCF files", "vcf_gather_bcftools": "Concatenate several VCF files using bcftools concat.\nAn additional option can be given to sort the concatenate", "dshbio/filterbed": "Filter features in gzipped BED format"}}, "target": "seqkit/concat", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_47", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_45", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_deprecated_dsl1_set_keyword_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bedtools_slop_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SLOP", "tool": "bedtools/slop", "description": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SLOP (Adds a specified number of bases in each direction (unique values may be specifi) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_checkirma_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should CHECKIRMA (custom/checkirma) be built?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow checkirma": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "mod_wipertools_fastqscatter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that splits FASTQ files into chunks (tools: fastqscatter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": null, "fcsgx_fetchdb": null, "art_illumina": null, "bamtofastq10x": null, "wipertools_fastqscatter": null}}, "target": "wipertools_fastqscatter", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_10", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_fastq_shortreads_preprocess_qc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality check and preprocessing subworkflow of Illumina short reads\nthat can do: quality check of input reads and generate statistics,\npreprocess and validate reads, barcode removal, remove adapters and merge reads,\nfilter by sequence complexity, deduplicate reads, remove host contamination,\nconcatenate reads and generate statistics for post-processing reads.\nWARNING: requires at least the process configurations from the nextflow.config\nto be added to the modules.config in the pipeline in order to work as intended. (tools: fastq_shortreads_preprocess_qc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "fastdup": "FastDup is a tool designed to locate and tag duplicate reads in a coordinate-sorted SAM or BAM file, using the", "atlas_recal": "Gives an estimation of the sequencing bias based on known invariant sites", "fastq_shortreads_preprocess_qc": "Quality check and preprocessing subworkflow of Illumina short reads\nthat can do: quality check of input reads "}}, "target": "fastq_shortreads_preprocess_qc", "target_idx": 4}
{"id": "mod_catpack_prepare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a CAT_pack database based on input FASTAs (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_classify_catpack": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack).", "rpbp_preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs", "krona_ktupdatetaxonomy": "KronaTools Update Taxonomy downloads a taxonomy database", "vcf_filter_bcftools_ensemblvep": "Filter VCF file with bcftools and filter_vep"}}, "target": "catpack_prepare", "target_idx": 2}
{"id": "resource_abra2_2", "category": "resource_profiling", "state": {"process": "ABRA2", "tool": "abra2", "description": "Assembly Based ReAligner for next-generation sequencing data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRA2 (Assembly Based ReAligner for next-generation sequencing data) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bracken_build_3", "category": "resource_profiling", "state": {"process": "BRACKEN_BUILD", "tool": "bracken/build", "description": "Extends a Kraken2 database to be compatible with Bracken"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BUILD (Extends a Kraken2 database to be compatible with Bracken) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_49", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_31", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_3_1", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 3}
{"id": "mod_fastcov_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a coverage plot from one or more bam files (tools: fastcov)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastcov": "Generate a coverage plot from one or more bam files", "custom/bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "gatk4/sitedepthtobaf": "EXPERIMENTAL TOOL! Convert SiteDepth to BafEvidence", "cnvkit/coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "bbmap/bbnorm": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result i"}}, "target": "fastcov", "target_idx": 0}
{"id": "noul_container_environment_specification_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_biscuit_index_5", "category": "resource_profiling", "state": {"process": "BISCUIT_INDEX", "tool": "biscuit/index", "description": "Indexes a reference genome for use with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_INDEX (Indexes a reference genome for use with Biscuit) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_phenotype_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "mod_samtools_faidx_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index FASTA file, and optionally generate a file of chromosome sizes (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shapeit5/ligate": "Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chu", "bowtie/build": "Create bowtie index for reference genome", "samtools/faidx": "Index FASTA file, and optionally generate a file of chromosome sizes", "bcftools/index": "Index VCF tools", "srst2/srst2": "Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLS"}}, "target": "samtools/faidx", "target_idx": 2}
{"id": "mod_snippy_core_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Core-SNP alignment from Snippy outputs (tools: snippy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt/suffixerator": "Computes enhanced suffix array using GenomeTools gt-suffixerator utility", "tidk/search": "Searches a genome for a telomere string such as TTAGGG", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "snippy/core": "Core-SNP alignment from Snippy outputs"}}, "target": "snippy/core", "target_idx": 4}
{"id": "noul_default_empty_channel_behavior_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_3_1", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "template": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Dual RNA-seq simultaneous host and pathogen transcriptomics with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_9", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_custom_filterdifferentialtable_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters a differential expression table based on logFC and adjusted p-value thresholds (tools: pandas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "custom/filterdifferentialtable": "Filters a differential expression table based on logFC and adjusted p-value thresholds", "wisecondorx/newref": "Create a new reference using healthy reference samples", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont"}}, "target": "custom/filterdifferentialtable", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_0_1", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_binning_concoct_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BINNING_CONCOCT", "modules": ["concoct/cutupfasta", "concoct/concoctcoveragetable", "concoct/concoct", "concoct/mergecutupclustering", "concoct/extractfastabins"], "description": "Runs the CONCOCT workflow of contig binning"}, "question": {"type": "choice", "instructions": "How should FASTA_BINNING_CONCOCT (concoct/cutupfasta, concoct/concoctcoveragetable, concoct/concoct, concoct/mergecutupclustering, concoct/extractfastabins) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_BINNING_CONCOCT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_binning_concoct": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_binning_concoct", "target_idx": 2}
{"id": "mod_svtyper_svtypersso_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SVTyper-sso computes structural variant (SV) genotypes based on breakpoint depth on a SINGLE sample (tools: svtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caddsv/get": null, "propr/logratio": null, "svtyper/svtypersso": null, "integronfinder": null, "annotsv/installannotations": null}}, "target": "svtyper/svtypersso", "target_idx": 2}
{"id": "mod_quantify_pseudo_alignment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects (tools: quantify_pseudo_alignment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "nonpareil/nonpareilcurvesr": "Generate summary reports with raw data for Nonpareil NPO curves, including MultiQC compatible JSON/TSV files", "bam_stringtie_merge": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a ", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects"}}, "target": "quantify_pseudo_alignment", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_26", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_demultiplex_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/demultiplex", "assay": "demultiplex pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/demultiplex (Demultiplexing pipeline for sequencing data)?", "criteria": {"family_id,sample,file_path,hpo_terms,sex": null, "vcf,fasta,genome,site,source": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,bam,vcf,rna_matrix,hto_matrix": null}}, "target": "id,samplesheet,lane,flowcell,per_flowcell_manifest", "target_idx": 2}
{"id": "noul_retry_errorstrategy_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_universc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to run UniverSC an open-source pipeline to demultiplex and process single-cell RNA-Seq data (tools: universc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paragraph/idxdepth": null, "bcl2fastq": null, "pbjasmine": null, "bases2fastq": null, "universc": null}}, "target": "universc", "target_idx": 4}
{"id": "samplesheet_arch_germline_lane_split_6_5", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multi-lane Illumina sequencing run of clinical samples input samplesheet?", "criteria": {"lane,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_executor_support_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/methylseq) for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq). Input files: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/methylseq, determine the input samplesheet column structure for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq).", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "intent_ask_question_11", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "debug_error": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 1}
{"id": "mod_hifiadapterfilt_hifiadapterfilt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ output, filtering statistics, BLAST hits,\nand a list of blocked read IDs. (tools: hifiadapterfilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt/downloaddb": null, "hifiadapterfilt/hifiadapterfilt": null, "anota2seq/anota2seqrun": null, "merfin/hist": null, "hifitrimmer/filterbam": null}}, "target": "hifiadapterfilt/hifiadapterfilt", "target_idx": 1}
{"id": "mod_folddisco_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a geometric-hashing index of discontinuous structural motifs from a directory of protein structure files (tools: folddisco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/createdb": "Create an MMseqs database from an existing FASTA/Q file", "suppa/generateevents": "Generates alternative splicing events from a GTF file using SUPPA.", "custom/getchromsizes": "Generates a FASTA file of chromosome sizes and a fasta index file", "bwamem3/index": "Create bwa-mem3 index for reference genome", "folddisco/index": "Build a geometric-hashing index of discontinuous structural motifs from a directory of protein structure files"}}, "target": "folddisco/index", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_2_6", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_bftools_showinf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract OME xml data from OME-tif (tools: bftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser/info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "bftools/showinf": "Extract OME xml data from OME-tif", "molkartgarage/clahe": "Contrast-limited adjusted histogram equalization (CLAHE) on single-channel tif images.", "idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)", "blobtk/create": "Creates a minimal blobdir."}}, "target": "bftools/showinf", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_5", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_quant_tximport_summarizedexperiment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedExperiment objects (tools: quant_tximport_summarizedexperiment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"manta_somatic": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "samtools_bam2fq": "The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format", "quant_tximport_summarizedexperiment": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedEx"}}, "target": "quant_tximport_summarizedexperiment", "target_idx": 4}
{"id": "samplesheet_arch_spatial_xenium_4_0", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Xenium output bundle with transcripts CSV, cell polygons, and morphology images?", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "mod_jvarkit_vcfpolyx_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: annotate VCF files for poly repeats (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/call": "generate VCF file from a BAM file using various calling methods", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "plink/genome": "Calculates identity-by-descent over autosomal SNPs", "pharokka/installdatabases": "Install databases necessary for Pharokka's functional analysis", "jvarkit/vcfpolyx": "annotate VCF files for poly repeats"}}, "target": "jvarkit/vcfpolyx", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_2_0", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_allelecounter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a count of coverage of alleles (tools: allelecounter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "htseq/count": "count how many reads map to each feature", "allelecounter": "Generates a count of coverage of alleles", "cellranger/count": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expressi"}}, "target": "allelecounter", "target_idx": 3}
{"id": "mod_jellyfish_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm (tools: jellyfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jellyfish/count": "Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm", "shapeit5/switch": "Program to compute switch error rate and genotyping error rate given simulated or trio data.", "fastk/fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "fastk/histex": "A fast K-mer counter for high-fidelity shotgun datasets", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "jellyfish/count", "target_idx": 0}
{"id": "mod_crisprcleanr_normalize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: remove false positives of functional crispr genomics due to CNVs (tools: crisprcleanr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs", "instrain_compare": "Strain-level comparisons across multiple inStrain profiles", "csvtk_sort": "Sort  CSV (or TSV) tables", "miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "bedtools_sort": "Sorts a feature file by chromosome and other criteria."}}, "target": "crisprcleanr_normalize", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_36", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_bcftools_pluginimputeinfo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available. (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_pluginimputeinfo": null, "homer_maketagdirectory": null, "cnvkit_coverage": null, "bcftools_call": null, "bcftools_index": null}}, "target": "bcftools_pluginimputeinfo", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_hisat2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_HISAT2", "modules": ["hisat2/align", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using hisat2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_HISAT2 (hisat2/align, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_ALIGN_HISAT2": null, "Use nf-core subworkflow fastq_align_hisat2": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_hisat2", "target_idx": 2}
{"id": "mod_rclone_check_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Check that files in source and destination paths match (tools: rclone)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone_checksum": "Check files in a destination path against a checksum SUM file", "rclone_check": "Check that files in source and destination paths match", "cobiontid_kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written", "ichorcna_run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst"}}, "target": "rclone_check", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "schema_std_omicsgenetraitassociation_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/omicsgenetraitassociation. Description: A nextflow pipeline which integrates multiple omic data streams and performs coordinated analysis.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/omicsgenetraitassociation.", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "patient,sample,vcf,status,cna": null, "sample,fastq_1,fastq_2,group": null, "sample_id,bam,vcf,library_id,lane": null}}, "target": "sample,trait,pascal,twas,additional_sources", "target_idx": 0}
{"id": "mod_ashlar_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Alignment by Simultaneous Harmonization of Layer/Adjacency Registration (tools: ashlar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "bcftools_pluginvcf2table": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output", "trgt_plot": "Visualize tandem repeats genotyped by TRGT"}}, "target": "ashlar", "target_idx": 2}
{"id": "mod_custom_orfnormalise_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for cross-caller merging.\n\nAn \"ORF caller\" is a tool that scans ribosome-profiling (Ribo-seq) data and\npredicts which open reading frames are being translated. Each caller writes\nits own table format and uses its own location encoding, classification\nvocabulary, and confidence score. This module reconciles five callers into\none harmonised schema. The `caller` val input selects the parser;\nsupported values:\n\n  - ribocode    (RiboCode predicted ORF table; transcript-coord input,\n                 lifted to genomic blocks against the GTF)\n  - ribotish    (Ribo-TISH predict output; GenomePos + optional Blocks)\n  - ribotricer  (Ribotricer detect-orfs translating ORFs TSV; ORF span\n                 parsed from ORF_ID, multi-exon blocks recovered by\n                 intersecting with host-transcript exon structure from\n                 the GTF)\n  - rpbp        (Rp-Bp predicted-orfs BED12 with extra columns)\n  - price       (PRICE orfs.tsv; Gedi-style Location field, already genomic)\n\nOutput BED12 column order:\n  chrom start end name score strand thickStart thickEnd itemRgb\n  blockCount blockSizes blockStarts\nThe BED `name` column carries `<caller>|<caller-native-id>`. The BED `score`\ncolumn is the caller's native score rescaled to 0-1000 (higher == more\nconfident regardless of native direction).\n\nOutput sidecar TSV columns:\n  orf_id caller sample_id chrom start end strand gene_id transcript_id\n  orf_class aa_length score orf_type_native is_smorf\n\n`orf_type_native` carries the caller's own ORF-type label verbatim, so every\nharmonisation decision below stays auditable without re-running the caller.\nORF-type tokens are matched exactly (casefolded) against each caller's closed\nvocabulary, on the part before any colon so that a qualified label such as\nRibo-TISH's `Novel:CDSFrameOverlap` matches on `Novel`. Tokens whose location\nmatches no entry cause the process to fail; successful outputs report\n`unmapped_orf_type=0` on the `# parser_columns:` provenance line.\n\n`orf_class` is purely positional: it records where the ORF sits relative to\nthe annotated CDS and never encodes its length. Select small ORFs with the\n`is_smorf` column (`aa_length` <= `--smorf-max-aa`, default 100).\n\n`aa_length` is derived as `(nucleotide_length - 3) // 3` for every caller\nexcept Ribo-TISH, whose `AALen` column is taken verbatim. If `AALen` counts\nthe stop codon, `is_smorf` is caller-dependent by one residue exactly at the\n`--smorf-max-aa` boundary. Not reconciled: it needs a Ribo-TISH run whose\nnucleotide lengths can be compared against `AALen` directly.\n\nHarmonised `orf_class` vocabulary written into the sidecar TSV:\n\n  - canonical_cds: ORF maps to an annotated CDS (including truncated /\n                   extended variants of one).\n  - uORF:          upstream ORF, not overlapping the CDS.\n  - uoORF:         upstream ORF overlapping the CDS out of frame.\n  - dORF:          downstream ORF, not overlapping the CDS.\n  - doORF:         downstream ORF overlapping the CDS out of frame.\n  - intORF:        ORF contained within the CDS, out of frame.\n  - novel_u:       novel / intergenic ORF not assigned to an annotated CDS.\n  - other:         anything a caller cannot place.\n\nNot every caller can report every class, so the absence of a class for one\ncaller is a tool limitation rather than evidence about the ORF:\n\n  - Ribo-TISH's `5'UTR` covers both uORF and uoORF, and `3'UTR` both dORF\n    and doORF: `tisType()` tests only the start position.\n  - PRICE's vocabulary has no doORF.\n  - ribotricer's `internal` is the terminal fall-through of\n    `check_orf_type()` rather than a positive out-of-frame call, so it maps\n    to `other`; mapping it to intORF would assert a frame relationship\n    ribotricer never tested.\n\nPer-caller mapping notes (lossy collapses):\n\n  - PRICE's `Gene` column concatenates every gene overlapping an ORF's\n    genomic span, so `gene_id` is resolved from the GTF via the ORF's\n    transcript id; the `Gene` column is used only for transcripts absent\n    from the annotation, and can then carry a multi-gene value.\n  - PRICE `iORF` maps to `intORF` and `orphan` to `novel_u` (it is both the\n    not-transcript-consistent label and PRICE's fall-through). `intronic`\n    has no positional equivalent and maps to `other`. The exact PRICE\n    sub-type is preserved in `orf_type_native`.\n  - Rp-Bp's predicted-orfs BED carries no ORF-type column; this module\n    defaults every Rp-Bp call to `canonical_cds` (the post-\n    selectfinalpredictionset curated set is dominated by canonical\n    CDSs). uORF/dORF/novel calls present in Rp-Bp's separate\n    `.tab.gz` / `extracted-orfs.bed.gz` files are not propagated here.\n\nEach caller's native confidence score has a \"direction\" - some are\nlower-is-better (p-values), some are higher-is-better (Bayes factors,\nphase scores):\n\n  ribocode:   min  (combined p-value)\n  ribotish:   min  (combined p-value)\n  ribotricer: max  (phase_score)\n  rpbp:       max  (Bayes factor mean)\n  price:      min  (p-value)\n\nDownstream merging uses this to pick the best per-ORF call. (tools: orfnormalise)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c", "gatk4/calculatecontamination": "Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummari", "bedtools/maskfasta": "masks sequences in a FASTA file based on intervals defined in a feature file.", "dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "gedi/price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm"}}, "target": "custom/orfnormalise", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_0_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "core_tool_quast_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Evaluate, compare, and compute quality metrics (N50, L50, misassemblies, completeness) for draft genome assemblies against reference genomes.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"busco": "Benchmark universal single-copy orthologs", "multiqc": "MultiQC report", "checkm": "Metagenome quality", "mummer": "Alignment tool", "quast": "Quality Assessment Tool for Genome Assemblies evaluating contigs metrics (N50, misassemblies)"}}, "target": "quast", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_0_7", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_tfactivity_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tfactivity", "assay": "tfactivity pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/tfactivity (Bioinformatics pipeline that makes use of expression and ope)?", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,fastq_1,strandedness": null, "patient,sample,vcf,status,cna": null}}, "target": "sample,condition,assay,peak_file,footprinting", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_gxf_busco_plot_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_GXF_BUSCO_PLOT", "modules": ["busco/busco", "busco/plot", "gffread"], "description": "Runs BUSCO for input assemblies and their annotations in GFF/GFF3/GTF format, and creates summary plots using `busco --plot`"}, "question": {"type": "choice", "instructions": "How should FASTA_GXF_BUSCO_PLOT (busco/busco, busco/plot, gffread) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTA_GXF_BUSCO_PLOT": null, "Leave them out": null, "Use nf-core subworkflow fasta_gxf_busco_plot": null}}, "target": "Use nf-core subworkflow fasta_gxf_busco_plot", "target_idx": 3}
{"id": "field_constraint_strandedness_0_5", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"type: boolean": null, "pattern: ^[0-9]+$": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "mod_sratools_prefetch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download sequencing data from the NCBI Sequence Read Archive (SRA). (tools: sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo", "artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "sratools/prefetch": "Download sequencing data from the NCBI Sequence Read Archive (SRA)."}}, "target": "sratools/prefetch", "target_idx": 4}
{"id": "subworkflow_pkg_vcf_extract_relate_somalier_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_EXTRACT_RELATE_SOMALIER", "modules": ["htslib/bgziptabix", "somalier/extract", "somalier/relate"], "description": "Perform somalier extraction and relate stats on input VCFs"}, "question": {"type": "choice", "instructions": "How should VCF_EXTRACT_RELATE_SOMALIER (htslib/bgziptabix, somalier/extract, somalier/relate) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow VCF_EXTRACT_RELATE_SOMALIER": null, "Use nf-core subworkflow vcf_extract_relate_somalier": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_extract_relate_somalier", "target_idx": 2}
{"id": "mod_methyldackel_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts per-base methylation metrics from alignments (tools: methyldackel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_idscoreswitcher": null, "bismark_methylationextractor": null, "crumble": null, "bismark_align": null, "methyldackel_extract": null}}, "target": "methyldackel_extract", "target_idx": 4}
{"id": "samplesheet_arch_cancer_longitudinal_0_1", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,bam": null, "sample,timepoint,fastq": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_1_4", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_rnafusion_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "assay": "rnafusion pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnafusion (RNA-seq analysis pipeline for detection of gene-fusions)?", "criteria": {"sample,fastq_1,fastq_2,replicate,antibody": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 1}
{"id": "mod_dysgu_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient detection of structural variations. (tools: dysgu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caddsv/get": "Download CADD-SV annotation resources or SegmentNT model files.", "dastool/scaffolds2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "memote/report": "Generate HTML quality report snapshot for genome-scale metabolic models", "caddsv/run": "Score structural variants with CADD-SV."}}, "target": "dysgu/run", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_0_28", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_gfastats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A single fast and exhaustive tool for summary statistics and simultaneous *fa*\n(fasta, fastq, gfa [.gz]) genome assembly file manipulation. (tools: gfastats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "gfastats": "A single fast and exhaustive tool for summary statistics and simultaneous *fa*\n(fasta, fastq, gfa [.gz]) genom", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "snpdists": "Pairwise SNP distance matrix from a FASTA sequence alignment"}}, "target": "gfastats", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_14", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_beagle5_beagle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers. (tools: beagle5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"beagle5/beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "hifiasm": "Whole-genome assembly using PacBio HiFi reads", "shapeit5/phasecommon": "Tool to phase common sites, typically SNP array data, or the first step of WES/WGS data.", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "merquryfk/merquryfk": "FastK based version of Merqury"}}, "target": "beagle5/beagle", "target_idx": 0}
{"id": "pipe_all101_variantprioritization_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR).. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin"}}, "target": "variantprioritization", "target_idx": 6}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "noul_undeclared_process_file_inputs_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_39", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_kma_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This module wraps the index module of the KMA alignment tool. (tools: kma)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "kma_index": "This module wraps the index module of the KMA alignment tool.", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "kma_index", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_gcta_reml_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run univariate REML heritability estimation with a dense GRM (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gedi_indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "gcta_bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "gcta_bivariatereml": "Run bivariate REML analysis with a single dense GRM", "huggingface_download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "gcta_reml": "Run univariate REML heritability estimation with a dense GRM"}}, "target": "gcta_reml", "target_idx": 4}
{"id": "field_constraint_fastq_1_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"type: integer": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "samplesheet_arch_proteomics_dia_5_4", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/diaproteomics, determine the input samplesheet column structure for: Data-Independent Acquisition (DIA) quantitative mass spectrometry.", "criteria": {"sample,raw_file,condition": null, "sample,fastq_1,fastq_2": null, "sample,mzml": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "resource_bcftools_consensus_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONSENSUS", "tool": "bcftools/consensus", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONSENSUS (Compresses VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_32", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_angsd_gl_4", "category": "resource_profiling", "state": {"process": "ANGSD_GL", "tool": "angsd/gl", "description": "Calculated genotype likelihoods from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_GL (Calculated genotype likelihoods from BAM files.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_whatshap_haplotag_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tag reads by haplotype (tools: whatshap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_regressive": "Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3", "minimac4_compressref": "Compression of a reference panel for genotype imputation to `.msav` format", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O", "whatshap_haplotag": "Tag reads by haplotype"}}, "target": "whatshap_haplotag", "target_idx": 4}
{"id": "mod_demuxem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplexing cell nucleus hashing data, using the estimated antibody background probability. (tools: demuxem)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nonpareil/set": null, "manta/convertinversion": null, "bff": null, "htodemux": null, "demuxem": null}}, "target": "demuxem", "target_idx": 4}
{"id": "mod_svtools_vcftobedpe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a VCF file to a BEDPE file. (tools: svtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtools/vcftobedpe": "Convert a VCF file to a BEDPE file.", "severus": "Severus is a somatic structural variation (SV) caller for long reads (both PacBio and ONT)", "viennarna/rnafold": "Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary str", "lsa/cosine": "Calculates the cosine similarity matrix between samples based on a gene expression matrix.", "rtgtools/svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs"}}, "target": "svtools/vcftobedpe", "target_idx": 0}
{"id": "mod_filtlong_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtlong filters long reads based on quality measures or short read data. (tools: filtlong)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"filtlong": "Filtlong filters long reads based on quality measures or short read data.", "last/mafconvert": "Converts MAF alignments in another format.", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads."}}, "target": "filtlong", "target_idx": 0}
{"id": "resource_bedops_gtf2bed_5", "category": "resource_profiling", "state": {"process": "BEDOPS_GTF2BED", "tool": "bedops/gtf2bed", "description": "Convert gtf format to bed format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_GTF2BED (Convert gtf format to bed format) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_29", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_17", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_29", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_bases2fastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Element Biosciences bases files (tools: bases2fastq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/mutect2": null, "qcat": null, "bam_variant_demix_boot_freyja": null, "bases2fastq": null, "idemux": null}}, "target": "bases2fastq", "target_idx": 3}
{"id": "schema_std_rnadnavar_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnadnavar. Description: Pipeline for RNA and DNA integrated analysis for somatic mutation detection.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnadnavar.", "criteria": {"sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,run,group,short_reads_1,short_reads_2": null, "patient,sample,fastq_1,fastq_2,bam": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 2}
{"id": "pipe_all101_stableexpression_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). The ideal use case is for determining the most suitable RT-qPCR reference genes for a given species.. Topics: expression, housekeeping-genes, qpcr-analysis. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training"}}, "target": "stableexpression", "target_idx": 5}
{"id": "resource_bamutil_clipoverlap_2", "category": "resource_profiling", "state": {"process": "BAMUTIL_CLIPOVERLAP", "tool": "bamutil/clipoverlap", "description": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_CLIPOVERLAP (clips overlapping read pairs. When two mates overlap, this tool will clip the re) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_samtools_faidx_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index FASTA file, and optionally generate a file of chromosome sizes (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "samtools_faidx": "Index FASTA file, and optionally generate a file of chromosome sizes", "fastq_fetch_clean_hostile": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files", "kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "biscuit_index": "Indexes a reference genome for use with Biscuit"}}, "target": "samtools_faidx", "target_idx": 1}
{"id": "mod_damageprofiler_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage (tools: damageprofiler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pmdtools_filter": "pmdtools command to filter ancient DNA molecules from others", "mapad_map": "Map short-reads to an indexed reference genome", "damageprofiler": "A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage", "cutesv": "structural-variant calling with cutesv", "regenie_splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs"}}, "target": "damageprofiler", "target_idx": 2}
{"id": "mod_numorph_intensity_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: performs shading correction and intensity normalization between tile stacks (tools: numorph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"numorph/3dunet": null, "tidk/explore": null, "preseq/lcextrap": null, "numorph/intensity": null, "numorph/resample": null}}, "target": "numorph/intensity", "target_idx": 3}
{"id": "pipe_all101_kmermaid_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: k-mer similarity analysis pipeline. Topics: k-mer, kmer, kmer-counting, kmer-frequency-count. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "callingcards": "A pipeline for processing calling cards data"}}, "target": "kmermaid", "target_idx": 7}
{"id": "pipe_all101_ribomsqc_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metaboigniter": null, "demo": null, "ribomsqc": null, "riboseq": null, "sarek": null}}, "target": "ribomsqc", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_1_7", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Multiplexed Oxford Nanopore run with barcode demultiplexing. Input files: Nanopore sequencing run with sample to barcode assignment and flowcell type.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "pipe_all101_chipseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze ChIP-seq peak-calling, QC and differential analysis pipeline.. Topics: chip, chip-seq, chromatin-immunoprecipitation, macs2, peak-calling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]"}}, "target": "chipseq", "target_idx": 0}
{"id": "mod_yak_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a tool to build k-mer hash table for fasta and fastq files (tools: yak)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamdbg/asm": "Metagenome assembler for long-read sequences (HiFi and ONT).", "bcftools/merge": "Merge VCF files", "yak/count": "a tool to build k-mer hash table for fasta and fastq files", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity", "merqury/hapmers": "A script to generate hap-mer dbs for trios"}}, "target": "yak/count", "target_idx": 2}
{"id": "field_constraint_fastq_1_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "mod_blobtk_snail_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates blobtk snail plots. (tools: btk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk/plot": null, "blobtk/snail": null, "blast/updateblastdb": null, "mat2json": null, "blobtk/create": null}}, "target": "blobtk/snail", "target_idx": 1}
{"id": "schema_std_pathogensurveillance_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pathogensurveillance", "assay": "pathogensurveillance pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/pathogensurveillance (Surveillance of pathogens using population genomics and sequ)?", "criteria": {"sample_id,idat_red,idat_green,group": null, "patient,vcf,tbi,dataset,tumour_sample": null, "sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,library_id,lane": null}}, "target": "sample_id,name,description,path,path_2", "target_idx": 2}
{"id": "field_constraint_bai_2_10", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "mod_bcftools_pluginfixploidy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes. (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/annotate": "Add or remove annotations.", "bcftools/pluginfixploidy": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignmen", "bcftools/csq": "bcftools Haplotype-aware consequence caller", "diamond/makedb": "Builds a DIAMOND database", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "bcftools/pluginfixploidy", "target_idx": 1}
{"id": "mod_tiara_tiara_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle (tools: tiara)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk_plot": "Creates differing styles of blobplots depending on provided arguments.", "leafcutter_differentialsplicing": "Perform differential splicing analysis to identify junctions with significant changes in splicing between cond", "concoct_concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "tiara_tiara": "Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle", "concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT"}}, "target": "tiara_tiara", "target_idx": 3}
{"id": "resource_bamreadcount_0", "category": "resource_profiling", "state": {"process": "BAMREADCOUNT", "tool": "bamreadcount", "description": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMREADCOUNT (bam-readcount is a utility that runs on a BAM or CRAM file and generates low-lev) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_hamronization_deeparg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize DeepARG outputs using the hAMRonization specification (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "gcta/remlldms": "Run REML-LDMS heritability estimation with an MGRM manifest", "cnvkit/batch": "Copy number variant detection from high-throughput sequencing data", "hamronization/deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "hamronization/deeparg", "target_idx": 3}
{"id": "samplesheet_arch_methylseq_bisulfite_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "assay_type": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "data_format": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_ampir_1", "category": "resource_profiling", "state": {"process": "AMPIR", "tool": "ampir", "description": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ampir uses a supervised statistical machine learning approach to predict AMPs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPIR (A fast and user-friendly method to predict antimicrobial peptides (AMPs) from an) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_cellsnp_modea_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A of cellsnp-lite after read alignment to obtain the snp x cell pileup UMI or read count matrices for each alleles of given or detected SNPs for droplet based single cell data. (tools: cellsnp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "caddsv_get": "Download CADD-SV annotation resources or SegmentNT model files.", "cellsnp_modea": "Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A ", "sequencetools_pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "falco": "Run falco on sequenced reads"}}, "target": "cellsnp_modea", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/dualrnaseq --input samplesheet.csv (Assay: Dual RNA-seq simultaneous host and pathogen transcriptomics)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 1}
{"id": "mod_clustalo_guidetree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Renders a guidetree in clustalo (tools: clustalo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"famsa/guidetree": "Renders a guidetree in famsa", "clustalo/guidetree": "Renders a guidetree in clustalo", "famsa/align": "Aligns sequences using FAMSA", "gapseq/doall": "Complete gapseq workflow from genome to gap-filled model", "samtools/faidx": "Index FASTA file, and optionally generate a file of chromosome sizes"}}, "target": "clustalo/guidetree", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_vcf_gather_bcftools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenate several VCF files using bcftools concat.\nAn additional option can be given to sort the concatenated VCF. (tools: vcf_gather_bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_gather_bcftools": null, "bcftools/concat": null, "vcf_impute_glimpse": null, "aardvark/merge": null, "primerprospector/analyzeprimers": null}}, "target": "vcf_gather_bcftools", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cutandrun) for CUT&RUN / CUT&TAG chromatin profiling with IgG control. Input files: Paired-end low-input fragment FASTQs with target antibody and IgG negative control.", "question": {"type": "choice", "instructions": "Which columns are standard for CUT&RUN / CUT&TAG chromatin profiling with IgG control input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "mod_fairy_sketch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sketches FASTQ reads into binary sketch (.bcsp) files for alignment-free coverage estimation. (tools: fairy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani_dist": "Simple ANI calculation between reference and query genomes.", "plink_exclude": "Exclude variant identifiers from plink bfiles", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3", "ska_fasta": "Create genome sketch using split k-mers", "fairy_sketch": "Sketches FASTQ reads into binary sketch (.bcsp) files for alignment-free coverage estimation."}}, "target": "fairy_sketch", "target_idx": 4}
{"id": "resource_bbmap_sendsketch_0", "category": "resource_profiling", "state": {"process": "BBMAP_SENDSKETCH", "tool": "bbmap/sendsketch", "description": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_SENDSKETCH (Compares query sketches to reference sketches hosted on a remote server via the ) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_8_2", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bam,bai": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "mod_merquryfk_katcomp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A reimplemenation of Kat Comp to work with FastK databases (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastk_fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "ganon_classify": "Classify FASTQ files against ganon database", "merquryfk_katcomp": "A reimplemenation of Kat Comp to work with FastK databases", "sparsesignatures": "mutational signature deconvolution of cancer cells", "iphop_download": "Download, extract, and check md5 of iPHoP databases"}}, "target": "merquryfk_katcomp", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_0_4", "category": "samplesheet_schema", "state": {"technology": "Small RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1,mirna_id": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_8_3", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "pipe_all101_bactmap_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences. Topics: bacteria, bacterial, bacterial-genome-analysis, genomics, mapping, phylogeny. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build"}}, "target": "bactmap", "target_idx": 5}
{"id": "resource_bigslice_downloaddb_4", "category": "resource_profiling", "state": {"process": "BIGSLICE_DOWNLOADDB", "tool": "bigslice/downloaddb", "description": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_DOWNLOADDB (Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nu) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_18", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bedtools_groupby_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GROUPBY", "tool": "bedtools/groupby", "description": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another column."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GROUPBY (Groups features in a BED file by given column(s) and computes summary statistics) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_allelecounter_2", "category": "resource_profiling", "state": {"process": "ALLELECOUNTER", "tool": "allelecounter", "description": "Generates a count of coverage of alleles"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALLELECOUNTER (Generates a count of coverage of alleles) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_stadeniolib_scramble_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Advanced sequence file format conversions (tools: scramble)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bioawk": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats.", "picrust2/pipeline": "Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data", "cnvpytor/importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file.", "stadeniolib/scramble": "Advanced sequence file format conversions", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "stadeniolib/scramble", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_5_3", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cageseq, determine the input samplesheet column structure for: CAGE-seq 5-prime capped transcript end sequencing.", "criteria": {"sample,bam": null, "sample,tss_bed": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "resource_bedtools_multiinter_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MULTIINTER", "tool": "bedtools/multiinter", "description": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MULTIINTER (Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_phenotype_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "enum: [normal, tumor]": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_fetch_clean_hostile_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FETCH_CLEAN_HOSTILE", "modules": ["hostile/fetch", "hostile/clean"], "description": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files"}, "question": {"type": "choice", "instructions": "How should FASTQ_FETCH_CLEAN_HOSTILE (hostile/fetch, hostile/clean) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_FETCH_CLEAN_HOSTILE": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_fetch_clean_hostile": null}}, "target": "Use nf-core subworkflow fastq_fetch_clean_hostile", "target_idx": 3}
{"id": "mod_gedi_price_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm (tools: gedi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sambamba/depth": "Outputs a coverage file from bam files", "gedi/price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "plastid/makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-", "homer/makeucscfile": "Create a UCSC bed graph with the HOMER suite", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}}, "target": "gedi/price", "target_idx": 1}
{"id": "resource_anarcii_2", "category": "resource_profiling", "state": {"process": "ANARCII", "tool": "anarcii", "description": "A language model for antigen receptor numbering"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANARCII (A language model for antigen receptor numbering) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "intent_debug_error_19", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "ask_question": null, "debug_error": null}}, "target": "debug_error", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_tn_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic cancer variant calling with tumor-normal pairs. Input files: Paired-end FASTQs for patient tumor and germline normal tissue.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_sex_0_0", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "pipe_all101_nanostring_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze An analysis pipeline for Nanostring nCounter expression data.. Topics: nanostring, nanostringnorm. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": null, "nanostring": null, "ampliseq": null, "pangenome": null, "viralintegration": null}}, "target": "nanostring", "target_idx": 1}
{"id": "field_constraint_bai_1_11", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "mod_lofreq_callparallel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: It predicts variants using multiple processors (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lofreq_callparallel": "It predicts variants using multiple processors", "vcftools": "A set of tools written in Perl and C++ for working with VCF files", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "hisat3n_align": "Align nucleotide conversion sequencing reads (e.g., bisulfite-seq, SLAM-seq) to a reference genome with HISAT-", "bcftools_concat": "Concatenate VCF files"}}, "target": "lofreq_callparallel", "target_idx": 0}
{"id": "resource_bcftools_plotvcfstats_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLOTVCFSTATS", "tool": "bcftools/plotvcfstats", "description": "Plots the output of bcftools stats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLOTVCFSTATS (Plots the output of bcftools stats) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Tumor-only somatic variant calling without matched normal)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Tumor-only somatic variant calling without matched normal?", "criteria": {"patient,normal,tumor": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_6_5", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi unaligned BAM variant calling input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "subworkflow_pkg_mmseqs_contig_taxonomy_0", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_CONTIG_TAXONOMY", "modules": ["mmseqs/databases", "mmseqs/createdb", "mmseqs/taxonomy", "mmseqs/createtsv"], "description": "Assign taxonomy to contigs using the MMseqs2 workflow."}, "question": {"type": "choice", "instructions": "How should MMSEQS_CONTIG_TAXONOMY (mmseqs/databases, mmseqs/createdb, mmseqs/taxonomy, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Local subworkflow MMSEQS_CONTIG_TAXONOMY": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow mmseqs_contig_taxonomy": null}}, "target": "Use nf-core subworkflow mmseqs_contig_taxonomy", "target_idx": 3}
{"id": "pipe_all101_kmermaid_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for k-mer analysis? Specific context: k-mer similarity analysis pipeline. Topics: k-mer, kmer, kmer-counting, kmer-frequency-count. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": "Read-based functional profiling of microbiome sequencing data", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "seqsubmit": "nf-core pipeline for data submission to ENA", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]"}}, "target": "kmermaid", "target_idx": 4}
{"id": "pipe_all101_atacseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for atac-seq analysis? Specific context: ATAC-seq peak-calling and QC analysis pipeline. Topics: atac-seq, chromatin-accessibiity. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]"}}, "target": "atacseq", "target_idx": 5}
{"id": "samplesheet_arch_epigenomics_hic_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/hic --input samplesheet.csv (Assay: Hi-C chromosome conformation capture mapping)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bed": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_argnorm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD). (tools: argnorm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "skani/triangle": "All-to-all ANI computation.", "gatk4/intervallisttools": "Splits the interval list file into unique, equally-sized interval files and place it under a directory", "hamronization/summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "argnorm", "target_idx": 4}
{"id": "field_constraint_fastq_2_0_10", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "mod_shigapass_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ShigaPass is an in silico tool used to predict Shigella serotypes and to differentiate between Shigella, EIEC (Enteroinvasive E. coli), and non Shigella/EIEC using assembled whole genomes. (tools: shigapass)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_star": "Align reads to a reference genome using bowtie2 then sort with samtools", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "shigapass": "ShigaPass is an in silico tool used to predict Shigella serotypes and to differentiate between Shigella, EIEC ", "mmseqs_cluster": "Cluster sequences using MMSeqs2 cluster."}}, "target": "shigapass", "target_idx": 3}
{"id": "resource_bedtools_subtract_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SUBTRACT", "tool": "bedtools/subtract", "description": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining portion of A."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SUBTRACT (Finds overlaps between two sets of regions (A and B), removes the overlaps from ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_scrnaseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/scrnaseq. Description: Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/scrnaseq.", "criteria": {"sample,seed": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,fastq_barcode,expected_cells", "target_idx": 3}
{"id": "schema_std_scnanoseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/scnanoseq. Description: Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/scnanoseq.", "criteria": {"seeds,network,perturbed_networks": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,fastq,cell_count": null, "id,fasta": null}}, "target": "sample,fastq,cell_count", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_9", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_pretextmap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converts sam/bam/cram/pairs into genome contact map (tools: pretextmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": "split single end read groups by length and merge paired end reads", "ascat": "copy number profiles of tumour cells.", "pretextmap": "converts sam/bam/cram/pairs into genome contact map", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga", "hicap": "Identify cap locus serotype and structure in your Haemophilus influenzae assemblies"}}, "target": "pretextmap", "target_idx": 2}
{"id": "noul_channel_operator_map_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/diaproteomics --input samplesheet.csv (Assay: Data-Independent Acquisition (DIA) quantitative mass spectrometry)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fasta": null, "sample,peptides_tsv": null, "sample,raw_file,condition": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "mod_metamaps_classify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strain-level metagenomic assignment (tools: metamaps)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamaps/mapdirectly": "Maps long reads to a metamaps database", "metamaps/classify": "Strain-level metagenomic assignment", "seqfu/derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th", "catpack/bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "emboss/revseq": "the revseq program from emboss reverse complements a nucleotide sequence"}}, "target": "metamaps/classify", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_4", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bwafastalign_mem_3", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_MEM", "tool": "bwafastalign/mem", "description": "Performs fastq alignment to a fasta reference using BWA-FastAlign."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_MEM (Performs fastq alignment to a fasta reference using BWA-FastAlign.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "resource_bedtools_makewindows_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAKEWINDOWS", "tool": "bedtools/makewindows", "description": "Makes adjacent or sliding windows across a genome or BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAKEWINDOWS (Makes adjacent or sliding windows across a genome or BED file.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_plink_exclude_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Exclude variant identifiers from plink bfiles (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety_embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "plink_extract": "Subset plink bfiles with a text file of variant identifiers", "plink_genome": "Calculates identity-by-descent over autosomal SNPs", "sniffles": "structural-variant calling with sniffles", "plink_exclude": "Exclude variant identifiers from plink bfiles"}}, "target": "plink_exclude", "target_idx": 4}
{"id": "samplesheet_arch_rnafusion_pe_1_2", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery", "pipeline": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fusion_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_maxquant_lfq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run standard proteomics data analysis with MaxQuant, mostly dedicated to label-free. Paths to fasta and raw files needs to be marked by \"PLACEHOLDER\" (tools: maxquant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"maxquant_lfq": "Run standard proteomics data analysis with MaxQuant, mostly dedicated to label-free. Paths to fasta and raw fi", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "csvtk_sort": "Sort  CSV (or TSV) tables", "checkm2_databasedownload": "CheckM2 database download", "bcftools_sort": "Sorts VCF files"}}, "target": "maxquant_lfq", "target_idx": 0}
{"id": "resource_bamutil_trimbam_5", "category": "resource_profiling", "state": {"process": "BAMUTIL_TRIMBAM", "tool": "bamutil/trimbam", "description": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_TRIMBAM (trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_abundance_differential_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A subworkflow for filtering differential abundance results (tools: abundance_differential_filter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bed_scatter_bedtools": null, "gubbins": null, "limma/differential": null, "abundance_differential_filter": null, "anota2seq/anota2seqrun": null}}, "target": "abundance_differential_filter", "target_idx": 3}
{"id": "resource_alignoth_2", "category": "resource_profiling", "state": {"process": "ALIGNOTH", "tool": "alignoth", "description": "Creating alignment plots from bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALIGNOTH (Creating alignment plots from bam files) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_biscuit_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexes a reference genome for use with Biscuit (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "biscuit_index": "Indexes a reference genome for use with Biscuit", "proteus_readproteingroups": "reads a maxQuant proteinGroups file with Proteus", "biscuit_align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "bedtools_split": "Split BED files into several smaller BED files"}}, "target": "biscuit_index", "target_idx": 1}
{"id": "mod_pilon_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Automatically improve draft assemblies and find variation among strains, including large event detection (tools: pilon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pilon": null, "bam_dedup_stats_samtools_umitools": null, "hypo": null, "abra2": null, "humann3/regroup": null}}, "target": "pilon", "target_idx": 0}
{"id": "schema_std_proteinannotator_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/proteinannotator. Description: Generation of sequence-level annotations for amino acid sequences.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/proteinannotator.", "criteria": {"id,fasta": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,fastq_1,fastq_2,group": null, "sample,bundle,image": null}}, "target": "id,fasta", "target_idx": 0}
{"id": "mod_pypgx_preparedepthofcoverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare a depth of coverage file for all target genes with SV from BAM files. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx_computecontrolstatistics": "Compute summary statistics for control gene from BAM files.", "pypgx_preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "pypgx_createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "gatk4_condensedepthevidence": "Merges adjacent DepthEvidence records", "samtools_bam2fq": "The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format"}}, "target": "pypgx_preparedepthofcoverage", "target_idx": 1}
{"id": "pipe_all101_clipseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling options.. Topics: clip, clip-seq, peak-calling, rna-rbp-interactions. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drugresponseeval": null, "demultiplex": null, "hadge": null, "clipseq": null, "cageseq": null}}, "target": "clipseq", "target_idx": 3}
{"id": "mod_metamaps_classify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strain-level metagenomic assignment (tools: metamaps)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack_summarise": "Summarises results from CAT/BAT/RAT classification steps", "metamaps_classify": "Strain-level metagenomic assignment", "samtools_ampliconclip": "Clips read alignments where they match BED file defined regions", "catpack_reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "gubbins": "Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively iden"}}, "target": "metamaps_classify", "target_idx": 1}
{"id": "resource_bff_2", "category": "resource_profiling", "state": {"process": "BFF", "tool": "bff", "description": "Generating cell hashing calls from a matrix of count data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFF (Generating cell hashing calls from a matrix of count data.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_rpbp_estimatemetagenebayesfactors_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of actively translating ribosomes.\nFor each candidate (read length, P-site offset) pair, Rp-Bp fits two\ncompeting Bayesian models to the count window around annotated start\ncodons: a \"periodic\" model whose signal repeats every three\nnucleotides, and a \"non-periodic\" background model. The Bayes factor\n(ratio of the two marginal likelihoods) quantifies how much the data\nprefer the periodic explanation.\n\nReturns one row per (length, offset) pair with the mean and variance of\nthe log Bayes factor across MCMC samples. Downstream,\n`rpbp/selectperiodicoffsets` picks the best offset per length from\nthis table, and `rpbp/getperiodiclengthsoffsets` filters to the\nhigh-confidence pairs that drive ORF-level scoring.\n\nUses the Stan models bundled inside the rpbp Python package. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hisat3n/build": "Build HISAT-3N index for nucleotide conversion sequencing alignment", "rpbp/extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "rpbp/extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "rpbp/estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "fastk/merge": "A tool to merge FastK histograms"}}, "target": "rpbp/estimatemetagenebayesfactors", "target_idx": 3}
{"id": "mod_picard_meanqualitybycycle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics about the mean quality by cycle of a paired-end library. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "custom_clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "hmmer_hmmsearch": "search profile(s) against a sequence database", "plink2_vcf2bgen": "Convert from VCF file to BGEN file version 1.2 format preserving dosages.", "picard_meanqualitybycycle": "Collect metrics about the mean quality by cycle of a paired-end library."}}, "target": "picard_meanqualitybycycle", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_subsample_fq_salmon_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SUBSAMPLE_FQ_SALMON", "modules": ["fq/subsample", "salmon/quant", "salmon/index"], "description": "Subsample fastq"}, "question": {"type": "choice", "instructions": "How should FASTQ_SUBSAMPLE_FQ_SALMON (fq/subsample, salmon/quant, salmon/index) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_subsample_fq_salmon": null, "Local subworkflow FASTQ_SUBSAMPLE_FQ_SALMON": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_subsample_fq_salmon", "target_idx": 1}
{"id": "resource_bcftools_index_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_INDEX", "tool": "bcftools/index", "description": "Index VCF tools"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_INDEX (Index VCF tools) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_5_4", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/taxprofiler, determine the input samplesheet column structure for: Multi-taxonomic profiling of complex metagenomic shotgun reads.", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_pyrodigal_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pyrodigal is a Python module that provides bindings to Prodigal, a fast, reliable protein-coding gene prediction for prokaryotic genomes. (tools: pyrodigal)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk_sort": "Sort  CSV (or TSV) tables", "t1k_build": "A module to create a reference database and coordinate files for T1K.", "macs3_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "pyrodigal": "Pyrodigal is a Python module that provides bindings to Prodigal, a fast, reliable protein-coding gene predicti", "crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs"}}, "target": "pyrodigal", "target_idx": 3}
{"id": "resource_bcftools_mpileup_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MPILEUP", "tool": "bcftools/mpileup", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MPILEUP (Compresses VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_gatk4_applyvqsr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a two-stage process called Variant Quality Score Recalibration (VQSR).\nSpecifically, it applies filtering to the input variants based on the recalibration table produced\nin the first step by VariantRecalibrator and a target sensitivity value. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snapaligner_align": "Performs fastq alignment to a fasta reference using SNAP", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "fastq_fastqc_umitools_trimgalore": "Read QC, UMI extraction and trimming", "gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "gatk4_applyvqsr", "target_idx": 3}
{"id": "resource_agat_convertbed2gff_3", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTBED2GFF", "tool": "agat/convertbed2gff", "description": "Takes a bed12 file and converts to a GFF3 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTBED2GFF (Takes a bed12 file and converts to a GFF3 file) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_sanitise_seqkit_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SANITISE_SEQKIT", "modules": ["seqkit/sana", "seqkit/pair"], "description": "Filters and reports malformed FASTQ sequences with seqkit/sana,"}, "question": {"type": "choice", "instructions": "How should FASTQ_SANITISE_SEQKIT (seqkit/sana, seqkit/pair) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_SANITISE_SEQKIT": null, "Leave them out": null, "Use nf-core subworkflow fastq_sanitise_seqkit": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_sanitise_seqkit", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_0_3", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Tumor-only somatic variant calling without matched normal?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_5_3", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/hic, determine the input samplesheet column structure for: Hi-C chromosome conformation capture mapping.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_1_2", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_pairgenomealign_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for comparative-genomics analysis? Specific context: Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results. Topics: comparative-genomics, dot-plot, genomics, last, pairwise-alignment, synteny. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "seqsubmit": "nf-core pipeline for data submission to ENA"}}, "target": "pairgenomealign", "target_idx": 2}
{"id": "mod_cnvkit_export_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert copy number ratio tables (.cnr files) or segments (.cns) to another format. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_export": null, "cnvkit_coverage": null, "deeptools_alignmentsieve": null, "cnvkit_fix": null, "gfastats": null}}, "target": "cnvkit_export", "target_idx": 0}
{"id": "mod_octopusv_svcf2vcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts octopusv SVCF files to the standard VCF format (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "octopusv_svcf2vcf": "Converts octopusv SVCF files to the standard VCF format", "coptr_index": "Indexes a directory of fasta files for use with CoPTR", "cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm"}}, "target": "octopusv_svcf2vcf", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_2_5", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "resource_agat_convertspgxf2gxf_2", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGXF2GXF", "tool": "agat/convertspgxf2gxf", "description": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGXF2GXF (Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_6_0", "category": "samplesheet_schema", "state": {"technology": "Spatial Transcriptomics", "workflow_entry": "FASTQC", "library_inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Visium spatial transcriptomics with histology image input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,image": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_26", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_1_4", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "noul_exit_code_137_cause_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "schema_std_funcprofiler_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/funcprofiler", "assay": "funcprofiler pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/funcprofiler (Read-based functional profiling of microbiome sequencing dat)?", "criteria": {"sample,id,data_path,fastq_dir,cytaimage": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 2}
{"id": "resource_bcftools_pluginsplit_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSPLIT", "tool": "bcftools/pluginsplit", "description": "Split VCF by sample, creating single- or multi-sample VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSPLIT (Split VCF by sample, creating single- or multi-sample VCFs.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_38", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_sanitise_seqkit_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SANITISE_SEQKIT", "modules": ["seqkit/sana", "seqkit/pair"], "description": "Filters and reports malformed FASTQ sequences with seqkit/sana,"}, "question": {"type": "choice", "instructions": "How should FASTQ_SANITISE_SEQKIT (seqkit/sana, seqkit/pair) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_SANITISE_SEQKIT": null, "Use nf-core subworkflow fastq_sanitise_seqkit": null}}, "target": "Use nf-core subworkflow fastq_sanitise_seqkit", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_4_3", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Aligned BAM files?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "schema_std_viralrecon_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay": "viralrecon pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/viralrecon (Assembly and intrahost/low-frequency variant calling for vir)?", "criteria": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,fastq_1,fastq_2,barcode": null, "ID,R1,R2,LongFastQ,Fast5": null, "id,fasta": null}}, "target": "sample,fastq_1,fastq_2,barcode", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_9", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_arriba_visualisation_1", "category": "resource_profiling", "state": {"process": "ARRIBA_VISUALISATION", "tool": "arriba/visualisation", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_VISUALISATION (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_31", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: FAIRE-seq / DNAse-seq open chromatin profiling)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: FAIRE-seq / DNAse-seq open chromatin profiling.", "criteria": {"sample,bed": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bamcmp_1", "category": "resource_profiling", "state": {"process": "BAMCMP", "tool": "bamcmp", "description": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For instance, filtering out mouse reads from patient derived xenograft mouse models (PDX)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCMP (Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and ) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bigscape_bigscape_5", "category": "resource_profiling", "state": {"process": "BIGSCAPE_BIGSCAPE", "tool": "bigscape/bigscape", "description": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSCAPE_BIGSCAPE (BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clust) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_12", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bbmap_bbduk_4", "category": "resource_profiling", "state": {"process": "BBMAP_BBDUK", "tool": "bbmap/bbduk", "description": "Adapter and quality trimming of sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBDUK (Adapter and quality trimming of sequencing reads) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_30", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_21", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_pycoqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: pycoqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"medaka": "A tool to create consensus sequences and variant calls from nanopore sequencing data", "busco_download": "Download database for BUSCO", "busco_busco": "Benchmarking Universal Single Copy Orthologs", "pycoqc": "write your description here", "mcroni": "Analysis of mcr-1 gene (mobilized colistin resistance) for sequence variation"}}, "target": "pycoqc", "target_idx": 3}
{"id": "mod_parabricks_genotypegvcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glnexus": null, "parabricks_genotypegvcf": null, "hamronization_summarize": null, "gatk4_combinegvcfs": null, "cramino": null}}, "target": "parabricks_genotypegvcf", "target_idx": 1}
{"id": "samplesheet_arch_scrna_multiome_2_4", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "mod_ribowaltz_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data (tools: ribowaltz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribowaltz": "Calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data", "ribocode_gtfupdate": "Update GTF annotation file for RiboCode compatibility", "anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "gedi_price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "cellrangerarc_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma"}}, "target": "ribowaltz", "target_idx": 0}
{"id": "resource_bcftools_merge_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MERGE", "tool": "bcftools/merge", "description": "Merge VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MERGE (Merge VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_ampcombi2_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete using MMseqs2 cluster. (tools: ampcombi2/cluster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "picard/sortvcf": "Sorts vcf files", "amplify/predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "cellbender/merge": "Module to use CellBender to remove ambient RNA from single-cell RNA-seq data", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin"}}, "target": "ampcombi2/cluster", "target_idx": 4}
{"id": "pipe_all101_hgtseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline to investigate horizontal gene transfer from NGS data. Topics: bwa-mem, bwa-mem2, fastqc, genomics-visualization, ggbio, horizontal-gene-transfer. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scrnaseq": null, "cageseq": null, "drop": null, "hgtseq": null, "phaseimpute": null}}, "target": "hgtseq", "target_idx": 3}
{"id": "field_constraint_fastq_2_1_4", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "field_constraint_expected_cells_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "mod_foldcomp_compress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Efficient compression tool for protein structures (tools: foldcomp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone_checksum": null, "samplesheetparser_info": null, "foldcomp_compress": null, "cdhit_cdhit": null, "caalm_caalm": null}}, "target": "foldcomp_compress", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Multi-lane Illumina sequencing run of clinical samples)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_holodeck_eval_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment accuracy of holodeck-simulated reads (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"survivor_simsv": null, "holodeck_eval": null, "idemux": null, "holodeck_mutate": null, "pints_caller": null}}, "target": "holodeck_eval", "target_idx": 1}
{"id": "mod_eigenstratdatabasetools_eigenstratsnpcoverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provide the SNP coverage of each individual in an eigenstrat formatted dataset. (tools: eigenstratdatabasetools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eigenstratdatabasetools_eigenstratsnpcoverage": null, "longphase_haplotag": null, "bedtools_coverage": null, "cnvkit_coverage": null, "last_dotplot": null}}, "target": "eigenstratdatabasetools_eigenstratsnpcoverage", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_14", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_pints_caller_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Main caller script for peak calling (tools: pints)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "macs3/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "macs2/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "pints/caller": "Main caller script for peak calling", "rseqc/readdistribution": "Calculate how mapped reads are distributed over genomic features"}}, "target": "pints/caller", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "data_format": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Fungal ITS1/ITS2 marker gene amplicon surveillance with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,primer_its1,primer_its2": null, "sample,unite_fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_tiara_tiara_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle (tools: tiara)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "sequali": "Sequence quality metrics for FASTQ and uBAM files.", "tiara/tiara": "Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle", "dastool/dastool": "DAS Tool binning step."}}, "target": "tiara/tiara", "target_idx": 3}
{"id": "pipe_all101_pairgenomealign_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results. Topics: comparative-genomics, dot-plot, genomics, last, pairwise-alignment, synteny. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo"}}, "target": "pairgenomealign", "target_idx": 9}
{"id": "mod_bam_split_by_region_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split the reads in the input bam by specified genomic region. (tools: bam_split_by_region)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "bam_split_by_region": "Split the reads in the input bam by specified genomic region.", "csvtk_split": "Splits CSV/TSV into multiple files according to column values", "muse_sump": "Computes tier-based cutoffs from a sample-specific error model which is generated by muse/call and reports the"}}, "target": "bam_split_by_region", "target_idx": 2}
{"id": "intent_build_pipeline_20", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "build_pipeline", "target_idx": 0}
{"id": "mod_sortmerna_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Local sequence alignment tool for filtering, mapping and clustering. (tools: SortMeRNA)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_zipper": "Zip an unmapped UMI BAM together with its aligned BAM using fgumi", "hifitrimmer_trim": "Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/F", "sortmerna": "Local sequence alignment tool for filtering, mapping and clustering.", "smoove_call": "smoove simplifies and speeds calling and genotyping SVs for short reads. It also improves specificity by remov", "hifitrimmer_filterbam": "Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLA"}}, "target": "sortmerna", "target_idx": 2}
{"id": "mod_taxonkit_name2taxid_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert taxon names to TaxIds (tools: taxonkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensor2/msi": null, "ganon/table": null, "fastavalidator": null, "bbmap/sendsketch": null, "taxonkit/name2taxid": null}}, "target": "taxonkit/name2taxid", "target_idx": 4}
{"id": "mod_paragraph_idxdepth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determines the depth in a BAM/CRAM file (tools: paragraph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": null, "metaphlan3_mergemetaphlantables": null, "abra2": null, "paragraph_idxdepth": null, "glnexus": null}}, "target": "paragraph_idxdepth", "target_idx": 3}
{"id": "field_constraint_bam_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_3", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_igvreports_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A Python application to generate self-contained HTML reports for variant review and other genomic applications (tools: igvreports)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/call": "generate VCF file from a BAM file using various calling methods", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "cellrangeratac/mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkfastq com", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon"}}, "target": "igvreports", "target_idx": 2}
{"id": "intent_build_pipeline_18", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 0}
{"id": "resource_biomformat_convert_2", "category": "resource_profiling", "state": {"process": "BIOMFORMAT_CONVERT", "tool": "biomformat/convert", "description": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HDF5) formats are supported"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOMFORMAT_CONVERT (Convert biom table to different format.\nConversion between text tab-delimited, B) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_21", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_6", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "noul_file_pairing_in_channel_tuples_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_qualimap_bamqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment data (tools: qualimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_download": "Download database for BUSCO", "untarfiles": "Extract files.", "admixture": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datas", "qualimap_bamqc": "Evaluate alignment data", "chelae_trim": "Adapter and quality trimming of short-read FASTQ data using chelae."}}, "target": "qualimap_bamqc", "target_idx": 3}
{"id": "field_constraint_expected_cells_0_7", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"enum: [auto, single, paired]": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_12", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bcftools_concat_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONCAT", "tool": "bcftools/concat", "description": "Concatenate VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONCAT (Concatenate VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "intent_build_pipeline_9", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "prepare_data": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "noul_module_metadata_propagation_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_magmap_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Best-practice analysis pipeline for mapping reads to a (large) collections of genomes. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo"}}, "target": "magmap", "target_idx": 2}
{"id": "mod_scanpy_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter cells and genes in single-cell RNA-seq data using Scanpy (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy_filter": null, "agat_spkeeplongestisoform": null, "arcane_filter": null, "purecn_run": null, "bedtools_multiinter": null}}, "target": "scanpy_filter", "target_idx": 0}
{"id": "schema_std_drop_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/drop", "description": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/drop?", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE", "target_idx": 1}
{"id": "noul_workflow_completion_lifecycle_hook_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "local_subworkflow_preparereports_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPAREREPORTS (custom/preparereports, multiqc).", "criteria": {"Leave them out": null, "Use nf-core subworkflow preparereports": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPAREREPORTS": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 3}
{"id": "noul_modular_subworkflow_composition_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_bracken_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extends a Kraken2 database to be compatible with Bracken (tools: bracken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/build": "Extends a Kraken2 database to be compatible with Bracken", "huggingface/download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "kraken2/buildstandard": "Downloads and builds Kraken2 standard database", "krakentools/extractkrakenreads": "Extract reads classified at any user-specified taxonomy IDs.", "sentieon/tnscope": "TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, us"}}, "target": "bracken/build", "target_idx": 0}
{"id": "schema_std_pairgenomealign_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pairgenomealign. Description: Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pairgenomealign.", "criteria": {"sample,tools,file,index": null, "sample,fasta": null, "sample_id,bam,vcf,library_id,lane": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null}}, "target": "sample,fasta", "target_idx": 1}
{"id": "intent_ask_question_19", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "prepare_data": null, "ask_question": null}}, "target": "ask_question", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_49", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_kaiju_kaiju2table_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep3_classify": "classification into haplogroups", "kaiju_kaiju2table": "write your description here", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "ganon_classify": "Classify FASTQ files against ganon database", "bcftools_csq": "bcftools Haplotype-aware consequence caller"}}, "target": "kaiju_kaiju2table", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_37", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_all101_readsimulator_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data.. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinfamilies": null, "isoseq": null, "readsimulator": null, "molkart": null, "sarek": null, "drop": null, "methylong": null, "metaboigniter": null, "sopa": null, "fastqrepair": null}}, "target": "readsimulator", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq with strandedness. Input files: Paired-end FASTQ reads with library strandedness.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_43", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_strandedness_0_8", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"pattern: ^[0-9]+$": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_1_31", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_last_lastdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare sequences for subsequent alignment with lastal. (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuger/build": "Build centrifuger database for taxonomic profiling", "last/postmask": "Post-alignment masking", "last/mafswap": "Reorder alignments in a MAF file", "last/lastdb": "Prepare sequences for subsequent alignment with lastal.", "purecn/run": "Run PureCN workflow to normalize, segment and determine purity and ploidy"}}, "target": "last/lastdb", "target_idx": 3}
{"id": "mod_rclone_check_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Check that files in source and destination paths match (tools: rclone)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone/checksum": "Check files in a destination path against a checksum SUM file", "rclone/check": "Check that files in source and destination paths match", "plink/epistasis": "Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others.", "shasum": "Print SHA256 (256-bit) checksums.", "entrezdirect/xtract": "Queries an NCBI database using an UID"}}, "target": "rclone/check", "target_idx": 1}
{"id": "noul_single_hyphen_cli_params_error_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_plink_fastepistasis_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"delly/call": "Call structural variants", "plink/fastepistasis": "Fast Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others.", "plink/epistasis": "Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others.", "spaceranger/mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command", "dastool/dastool": "DAS Tool binning step."}}, "target": "plink/fastepistasis", "target_idx": 1}
{"id": "noul_single_hyphen_cli_params_error_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_sickle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A windowed adaptive trimming tool for FASTQ files using quality (tools: sickle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sickle": null, "rasusa": null, "mmseqs/easysearch": null, "ariba/run": null, "ariba/getref": null}}, "target": "sickle", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_2_4", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels", "pipeline": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_9", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_gcta_makebksparse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a sparse GRM from a dense GRM for downstream fastGWA analyses (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`", "gcta/makebksparse": "Create a sparse GRM from a dense GRM for downstream fastGWA analyses", "emboss/seqret": "Reads in one or more sequences, converts, filters, or transforms them and writes them out again", "gcta/bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "ribowaltz": "Calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data"}}, "target": "gcta/makebksparse", "target_idx": 1}
{"id": "resource_bismark_align_2", "category": "resource_profiling", "state": {"process": "BISMARK_ALIGN", "tool": "bismark/align", "description": "Performs alignment of BS-Seq reads using bismark"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_ALIGN (Performs alignment of BS-Seq reads using bismark) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_6_4", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq input samplesheet?", "criteria": {"plate,sample,bam": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,well,fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_proseg_proseg2baysor_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert proseg outputs to baysor format for import to Xenium explorer (tools: proseg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"baysor_run": "Bayesian segmentation of spatial transcriptomics data.", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "cellrangerarc_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma", "nonpareil_nonpareil": "Calculate metagenome redundancy curve from FASTQ files", "proseg_proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer"}}, "target": "proseg_proseg2baysor", "target_idx": 4}
{"id": "noul_publishdir_directive_usage_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_bwa_aln_0", "category": "resource_profiling", "state": {"process": "BWA_ALN", "tool": "bwa/aln", "description": "Find SA coordinates of the input reads for bwa short-read mapping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_ALN (Find SA coordinates of the input reads for bwa short-read mapping) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_6_4", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping", "pipeline": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for CAGE-seq 5-prime capped transcript end sequencing input samplesheet?", "criteria": {"sample,bam": null, "sample,tss_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_multiple_script_sections_invalid_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_detaxizer_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.. Topics: de-identification, decontamination, edna, fastq, filter, long-reads. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"denovotranscript": null, "nanostring": null, "genomeassembler": null, "hgtseq": null, "cutandrun": null, "oncoanalyser": null, "detaxizer": null, "funcscan": null}}, "target": "detaxizer", "target_idx": 6}
{"id": "samplesheet_arch_scrna_multiome_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for 10x Multiome single-cell joint RNA and ATAC chromatin. Input files: Paired FASTQs for both GEX and ATAC modalities per nucleus.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Multiome single-cell joint RNA and ATAC chromatin with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,matrix": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "schema_std_pacvar_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "description": "Longread PacBio sequencing processing for WGS and PureTarget", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pacvar?", "criteria": {"sample,bam,pbi,fail,repeat_id": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2,library_id,lane": null}}, "target": "sample,bam,pbi,fail,repeat_id", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_33", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_gnu_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Writes a sorted concatenation of file/s (tools: gnu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clame": null, "semibin/singleeasybin": null, "bedtools/sort": null, "ngsbits/rohhunter": null, "gnu/sort": null}}, "target": "gnu/sort", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_0_6", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_quast_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality Assessment Tool for Genome Assemblies (tools: quast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": null, "seqtk/cutn": null, "ale": null, "quast": null, "gatk4/germlinecnvcaller": null}}, "target": "quast", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_se_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Single-end Illumina RNA-seq with strandedness", "data_format": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end FASTQ reads per library?", "criteria": {"sample,bam": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "mod_freyja_update_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: downloads new versions of the curated SARS-CoV-2 lineage file and barcodes (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scds": "Module to use scds for doublet scoring", "mash_screen": "Screens query sequences against large sequence databases", "freyja_update": "downloads new versions of the curated SARS-CoV-2 lineage file and barcodes", "blast_makeblastdb": "Builds a BLAST database", "blast_blastdbcmd": "Retrieve entries from a BLAST database"}}, "target": "freyja_update", "target_idx": 2}
{"id": "resource_biomformat_convert_4", "category": "resource_profiling", "state": {"process": "BIOMFORMAT_CONVERT", "tool": "biomformat/convert", "description": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HDF5) formats are supported"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOMFORMAT_CONVERT (Convert biom table to different format.\nConversion between text tab-delimited, B) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_named_process_output_emits_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_antismash_antismash_2", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASH", "tool": "antismash/antismash", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASH (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_sequali_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sequence quality metrics for FASTQ and uBAM files. (tools: sequali)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leehom": "Bayesian reconstruction of ancient DNA fragments", "plink/indeppairwise": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of varia", "hificnv": "Copy number variant calling from PacBio HiFi reads", "bbmap/repair": "Re-pairs reads that became disordered or had some mates eliminated.", "sequali": "Sequence quality metrics for FASTQ and uBAM files."}}, "target": "sequali", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_1_8", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay_type": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "data_format": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CUT&RUN / CUT&TAG chromatin profiling with IgG control with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null, "sample,bam": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "resource_agat_convertbed2gff_2", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTBED2GFF", "tool": "agat/convertbed2gff", "description": "Takes a bed12 file and converts to a GFF3 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTBED2GFF (Takes a bed12 file and converts to a GFF3 file) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bismark_coverage2cytosine_4", "category": "resource_profiling", "state": {"process": "BISMARK_COVERAGE2CYTOSINE", "tool": "bismark/coverage2cytosine", "description": "Relates methylation calls back to genomic cytosine contexts."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_COVERAGE2CYTOSINE (Relates methylation calls back to genomic cytosine contexts.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_anarcii_3", "category": "resource_profiling", "state": {"process": "ANARCII", "tool": "anarcii", "description": "A language model for antigen receptor numbering"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANARCII (A language model for antigen receptor numbering) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bcftools_convert_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONVERT", "tool": "bcftools/convert", "description": "Converts certain output formats to VCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONVERT (Converts certain output formats to VCF) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_mykrobe_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: AMR predictions for supported species (tools: mykrobe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": null, "ariba/run": null, "mykrobe/predict": null, "zip": null, "fasta_vclust_prefilter_align_cluster": null}}, "target": "mykrobe/predict", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_0_1", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"plate,sample,bam": null, "sample,matrix": null, "sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_find_mirna_mirdeep2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FIND_MIRNA_MIRDEEP2", "modules": ["seqkit/fq2fa", "seqkit/replace", "bowtie/build", "mirdeep2/mapper", "mirdeep2/mirdeep2"], "description": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, processes and replaces any whitespace in sequence IDs, builds a Bowtie index of the genome, and then maps reads using miRDeep2 mapper before identifying known and novel miRNAs."}, "question": {"type": "choice", "instructions": "How should FASTQ_FIND_MIRNA_MIRDEEP2 (seqkit/fq2fa, seqkit/replace, bowtie/build, mirdeep2/mapper, mirdeep2/mirdeep2) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_find_mirna_mirdeep2": null, "Local subworkflow FASTQ_FIND_MIRNA_MIRDEEP2": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_find_mirna_mirdeep2", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_0_0", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_agat_spextractsequences_5", "category": "resource_profiling", "state": {"process": "AGAT_SPEXTRACTSEQUENCES", "tool": "agat/spextractsequences", "description": "This script extracts sequences in fasta format according to features described\nin a gff file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPEXTRACTSEQUENCES (This script extracts sequences in fasta format according to features described\ni) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_fcs_fcsadaptor_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run NCBI's FCS adaptor on assembled genomes (tools: fcs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trnascanse": "Detection of tRNA sequences using covariance models", "fcs/fcsadaptor": "Run NCBI's FCS adaptor on assembled genomes", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "anarcii": "A language model for antigen receptor numbering", "ale": "ALE: assembly likelihood estimator."}}, "target": "fcs/fcsadaptor", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_2_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bamaligncleaner_5", "category": "resource_profiling", "state": {"process": "BAMALIGNCLEANER", "tool": "bamaligncleaner", "description": "removes unused references from header of sorted BAM/CRAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMALIGNCLEANER (removes unused references from header of sorted BAM/CRAM files.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_19", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "schema_std_omicsgenetraitassociation_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/omicsgenetraitassociation", "assay": "omicsgenetraitassociation pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/omicsgenetraitassociation (A nextflow pipeline which integrates multiple omic data stre)?", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,barcode": null, "sample,seed": null}}, "target": "sample,trait,pascal,twas,additional_sources", "target_idx": 0}
{"id": "mod_fastq_align_hisat2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using hisat2 then sort with samtools (tools: fastq_align_hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "manta/germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "ska/distance": "Calculate pairwise distances and basic clustering from SKA sketches", "fastq_align_hisat2": "Align reads to a reference genome using hisat2 then sort with samtools", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "fastq_align_hisat2", "target_idx": 3}
{"id": "mod_quantify_pseudo_alignment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects (tools: quantify_pseudo_alignment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequencetools_pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "ldak_kvikstep1": "Run LDAK-KVIK step 1 to fit the genome-wide model and emit the minimal prediction artifact tuple consumed by l", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "quantify_pseudo_alignment", "target_idx": 1}
{"id": "local_subworkflow_prepilluminareads_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should PREPILLUMINAREADS (trimmomatic) be built?", "criteria": {"Local subworkflow PREPILLUMINAREADS": null, "Leave them out": null, "Use nf-core subworkflow prepilluminareads": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 0}
{"id": "field_constraint_fastq_2_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "subworkflow_pkg_bam_ngscheckmate_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_NGSCHECKMATE", "modules": ["bcftools/mpileup", "ngscheckmate/ncm"], "description": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs."}, "question": {"type": "choice", "instructions": "How should BAM_NGSCHECKMATE (bcftools/mpileup, ngscheckmate/ncm) be structured in DSL2?", "criteria": {"Local subworkflow BAM_NGSCHECKMATE": null, "Use nf-core subworkflow bam_ngscheckmate": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_ngscheckmate", "target_idx": 1}
{"id": "mod_cdhit_cdhitest_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster nucleotide sequences using sequence similarity (tools: cdhit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "htseq/count": "count how many reads map to each feature", "isoseq/cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences", "cdhit/cdhitest": "Cluster nucleotide sequences using sequence similarity", "galah": "Cluster genome FASTA files by average nucleotide identity"}}, "target": "cdhit/cdhitest", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_4", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_3", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_agat_convertspgff2tsv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a GFF/GTF file into a TSV file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "nonpareil/curve": "Visualise metagenome redundancy curve in PNG format from a single Nonpareil npo file", "agat/convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "perbase": "Per-base metrics on BAM/CRAM files."}}, "target": "agat/convertspgff2tsv", "target_idx": 3}
{"id": "resource_ariba_getref_5", "category": "resource_profiling", "state": {"process": "ARIBA_GETREF", "tool": "ariba/getref", "description": "Download and prepare database for Ariba analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_GETREF (Download and prepare database for Ariba analysis) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP", "modules": ["ensemblvep/vep", "tabix/tabix"], "description": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP (ensemblvep/vep, tabix/tabix) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow VCF_ANNOTATE_ENSEMBLVEP": null, "Use nf-core subworkflow vcf_annotate_ensemblvep": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep", "target_idx": 2}
{"id": "mod_comebin_runcomebin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning (tools: comebin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"comebin_runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs", "gridss_gridss": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements."}}, "target": "comebin_runcomebin", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_0_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "HIFIADAPTERFILT", "library_inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_sanitise_seqkit_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SANITISE_SEQKIT", "modules": ["seqkit/sana", "seqkit/pair"], "description": "Filters and reports malformed FASTQ sequences with seqkit/sana,"}, "question": {"type": "choice", "instructions": "How should FASTQ_SANITISE_SEQKIT (seqkit/sana, seqkit/pair) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_SANITISE_SEQKIT": null, "Use nf-core subworkflow fastq_sanitise_seqkit": null}}, "target": "Use nf-core subworkflow fastq_sanitise_seqkit", "target_idx": 3}
{"id": "resource_bedtools_bamtobed_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_BAMTOBED", "tool": "bedtools/bamtobed", "description": "Converts a bam file to a bed12 file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_BAMTOBED (Converts a bam file to a bed12 file.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_pridepy_downloadfile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download a single file from the PRIDE Archive by name using pridepy. (tools: pridepy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pridepy/downloadfile": "Download a single file from the PRIDE Archive by name using pridepy.", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo", "aria2": "CLI Download utility", "dastool/dastool": "DAS Tool binning step.", "mirdeep2/mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs."}}, "target": "pridepy/downloadfile", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_25", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_5_2", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter", "pipeline": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/smrnaseq, determine the input samplesheet column structure for: Small RNA / miRNA sequencing.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_container_environment_specification_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_31", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_fastq_1_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "mod_apbs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Boltzmann Solver). Produces electrostatic potential\nmaps and solvation energy values for large biomolecular assemblages. (tools: apbs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gemmi_cif2json": null, "spotiflow": null, "apbs": null, "pdb2pqr": null, "ngsbits_rohhunter": null}}, "target": "apbs", "target_idx": 2}
{"id": "resource_bedops_gtf2bed_4", "category": "resource_profiling", "state": {"process": "BEDOPS_GTF2BED", "tool": "bedops/gtf2bed", "description": "Convert gtf format to bed format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDOPS_GTF2BED (Convert gtf format to bed format) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_deeptools_computematrix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculates scores per genome regions for other deeptools plotting utilities (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools/group": "Group reads based on their UMI and mapping coordinates", "abacas": "Contiguate draft genome assembly", "deeptools/computematrix": "calculates scores per genome regions for other deeptools plotting utilities", "skesa": "Assemble microbial genomes from short-read FASTQ files into contigs in FASTA format using SKESA.", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file"}}, "target": "deeptools/computematrix", "target_idx": 2}
{"id": "mod_purgedups_pbcstat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create read depth histogram and base-level read depth for an assembly based on pacbio data (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/dumpsoftwareversions": "Custom module used to dump software versions within the nf-core pipeline template", "purgedups/pbcstat": "Create read depth histogram and base-level read depth for an assembly based on pacbio data", "vcflib/vcffilter": "Command line tools for parsing and manipulating VCF files.", "csvtk/sort": "Sort  CSV (or TSV) tables", "bedtools/sort": "Sorts a feature file by chromosome and other criteria."}}, "target": "purgedups/pbcstat", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_4_2", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs for patient tumor and germline normal tissue?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_proteinfamilies_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/proteinfamilies. Description: Generation and updating of protein families.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/proteinfamilies.", "criteria": {"sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1": null, "id,taxid,fasta_dna,fasta_aa": null}}, "target": "sample,fasta,existing_hmms_to_update,existing_msas_to_update", "target_idx": 0}
{"id": "mod_longphase_phase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modifications for Nanopore and PacBio platforms. (tools: longphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"longphase_phase": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi", "vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "scanpy_hashsolo": "Probabilistic demultiplexing of cell hashing data", "glimpse_phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods", "bcftools_mpileup": "Compresses VCF files"}}, "target": "longphase_phase", "target_idx": 0}
{"id": "resource_bcftools_mpileup_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MPILEUP", "tool": "bcftools/mpileup", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MPILEUP (Compresses VCF files) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_denovotranscript_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq. Topics: denovo-assembly, rna-seq, transcriptome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet"}}, "target": "denovotranscript", "target_idx": 3}
{"id": "mod_fusioncatcher_fusioncatcher_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data (tools: fusioncatcher)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba_arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "fusioncatcher_fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "parabricks_starfusion": "This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. Thi", "singlem_dbdownload": "Download the SingleM metapackage database used for metagenome profiling", "mmseqs_easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2"}}, "target": "fusioncatcher_fusioncatcher", "target_idx": 1}
{"id": "field_constraint_fastq_2_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_cram_indexed_2_4", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,cram": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "resource_autocycler_trim_3", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_TRIM", "tool": "autocycler/trim", "description": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_TRIM (Trim cluster assembly graphs to remove unsupported segments prior to resolution.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_0_0", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_anndata_getsize_5", "category": "resource_profiling", "state": {"process": "ANNDATA_GETSIZE", "tool": "anndata/getsize", "description": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_GETSIZE (Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_0_45", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_blobtk_create_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a minimal blobdir. (tools: btk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk/create": "Creates a minimal blobdir.", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "vizgenpostprocessing/runsegmentationontile": "The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool.", "bftools/showinf": "Extract OME xml data from OME-tif", "entrezdirect/esummary": "Queries an NCBI database using Unique Identifier(s)"}}, "target": "blobtk/create", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_37", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_31", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_4_3", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "template": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end oncology RNA-seq reads for chimeric transcript discovery?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_fusioncatcher_fusioncatcher_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data (tools: fusioncatcher)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "fusioninspector": "Validation of Fusion Transcript Predictions", "fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "dastool/scaffolds2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "purecn/run": "Run PureCN workflow to normalize, segment and determine purity and ploidy"}}, "target": "fusioncatcher/fusioncatcher", "target_idx": 2}
{"id": "resource_bakta_baktadbdownload_4", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTADBDOWNLOAD", "tool": "bakta/baktadbdownload", "description": "Downloads BAKTA database from Zenodo"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTADBDOWNLOAD (Downloads BAKTA database from Zenodo) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_admixture_0", "category": "resource_profiling", "state": {"process": "ADMIXTURE", "tool": "admixture", "description": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datasets, where the individuals are unrelated (for example, the individuals in a case-control association study)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADMIXTURE (ADMIXTURE is a program for estimating ancestry in a model-based manner from larg) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_canvas_germline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPedigree-WGS mode. Although named SmallPedigree-WGS, this\nmode is recommended for single germline samples as well as small pedigrees.\nThe module accepts aligned reads (BAM), germline SNV calls, and sex-specific ploidy\ninformation, and outputs a VCF with copy number status across the genome together\nwith a coverage-and-variant-frequency file used for downstream segmentation. (tools: canvas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples).", "parabricks/minimap2": "NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference da", "ensemblvep/vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`.", "cnvkit/target": "Transform bait intervals into targets more suitable for CNVkit."}}, "target": "canvas/germline", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_21", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_channel_filter_operator_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_custom_geneticmapconvert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This R script allows to automatically detect the different genetic map format and\nconvert the input file in all the other format type. (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sushie": "Software to perform multi-ancestry SNP fine-mapping on molecular data", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "custom/geneticmapconvert": "This R script allows to automatically detect the different genetic map format and\nconvert the input file in al", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "rtgtools/vcfeval": "The VCFeval tool of RTG tools. It is used to evaluate called variants for agreement with a baseline variant se"}}, "target": "custom/geneticmapconvert", "target_idx": 2}
{"id": "mod_utils_annotation_cache_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Check the path to the annotation cache depending if local or on the cloud, or using annotation-cache itself (tools: utils_annotation_cache)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cdhit/cdhit": "Cluster protein sequences using sequence similarity", "merqury/hapmers": "A script to generate hap-mer dbs for trios", "utils_annotation_cache": "Check the path to the annotation cache depending if local or on the cloud, or using annotation-cache itself", "snpeff/snpeff": "Genetic variant annotation and functional effect prediction toolbox", "vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file"}}, "target": "utils_annotation_cache", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_4_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single HiFi BAM or FastQ?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "pipe_core10_sarek_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Tumor/normal pair exome sequencing for somatic SNV calling with Strelka2, Mutect2, and FreeBayes with VEP annotation.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": null, "viralrecon": null, "mag": null, "scrnaseq": null, "taxprofiler": null, "atacseq": null, "eager": null, "rnaseq": null, "chipseq": null, "sarek": null}}, "target": "sarek", "target_idx": 9}
{"id": "mod_pdb2pqr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g. APBS input preparation). (tools: pdb2pqr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldcomp/compress": "Efficient compression tool for protein structures", "pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g", "gatk4/indexfeaturefile": "Creates an index for a feature file, e.g. VCF or BED file.", "cnvnator/convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "foldseek/createdb": "Create a database from protein structures"}}, "target": "pdb2pqr", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral amplicon sequencing with primers)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral amplicon sequencing with primers with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bam_rseqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to run multiple commands in the RSeqC package (tools: bam_rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "bam_rseqc": "Subworkflow to run multiple commands in the RSeqC package", "macs3/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments"}}, "target": "bam_rseqc", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cageseq", "assay_type": "CAGE-seq 5-prime capped transcript end sequencing", "data_format": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns are standard for CAGE-seq 5-prime capped transcript end sequencing input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,tss_bed": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "field_constraint_sample_0_10", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "format: file-path": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "mod_agat_spstatistics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides different type of statistics in text format from a GFF/GTF annotation file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2tsv": null, "agat/convertspgff2gtf": null, "agat/spstatistics": null, "trnascanse": null, "pharmcat/phenotyper": null}}, "target": "agat/spstatistics", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_4_2", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads from tumor biopsy without matched normal?", "criteria": {"sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_starfusion_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download STAR-fusion genome resource required to run STAR-Fusion caller (tools: star-fusion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcflib_vcffixup": null, "starfusion_build": null, "bedtools_bamtobed": null, "blast_updateblastdb": null, "aria2": null}}, "target": "starfusion_build", "target_idx": 1}
{"id": "mod_angsd_gl_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculated genotype likelihoods from BAM files. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "pbccs": "Pacbio ccs - Generate Highly Accurate Single-Molecule Consensus Reads", "angsd_dosaf": "Estimate site allele frequencies from BAM files.", "angsd_gl": "Calculated genotype likelihoods from BAM files."}}, "target": "angsd_gl", "target_idx": 4}
{"id": "mod_fastqscreen_buildfromindex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build fastq screen config file from bowtie index files (tools: fastqscreen)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/build": "Extends a Kraken2 database to be compatible with Bracken", "picard/sortsam": "Sorts BAM/SAM files based on a variety of picard specific criteria", "hisat3n/build": "Build HISAT-3N index for nucleotide conversion sequencing alignment", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "fastqscreen/buildfromindex": "Build fastq screen config file from bowtie index files"}}, "target": "fastqscreen/buildfromindex", "target_idx": 4}
{"id": "mod_mummer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MUMmer is a system for rapidly aligning entire genomes (tools: mummer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "bcftools_split": "Split a vcf file into files per chromosome", "mummer": "MUMmer is a system for rapidly aligning entire genomes", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali"}}, "target": "mummer", "target_idx": 2}
{"id": "mod_wisecondorx_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find copy number aberrations (tools: wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hificnv": "Copy number variant calling from PacBio HiFi reads", "pharmcat/vcfpreprocessor": "The PharmCAT VCF Preprocessor is a script that can pre-process VCF files for PharmCAT to make sure the VCF fil", "fastq_qc_trim_filter_setstrandedness": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files,", "dragen/germline": "The DRAGEN DNA Germline Pipeline accelerates the secondary analysis of NGS data by harnessing the tremendous p", "wisecondorx/predict": "Find copy number aberrations"}}, "target": "wisecondorx/predict", "target_idx": 4}
{"id": "local_subworkflow_irma_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for IRMA (irma).", "criteria": {"Use nf-core subworkflow irma": null, "Leave them out": null, "Local subworkflow IRMA": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow IRMA", "target_idx": 2}
{"id": "mod_gatk4_createreadcountpanelofnormals_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a panel of normals (PoN) for read-count denoising given the read counts for samples in the panel. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/asereadcounter": null, "gatk4/createreadcountpanelofnormals": null, "wgsim": null, "fastqscreen/buildfromindex": null, "gatk4/analyzecovariates": null}}, "target": "gatk4/createreadcountpanelofnormals", "target_idx": 1}
{"id": "noul_confusing_combine_with_mix_semantics_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_bowtie_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create bowtie index for reference genome (tools: bowtie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_collectvariantcallingmetrics": "Collects per-sample and aggregate (spanning all samples) metrics from the provided VCF file", "bowtie_build": "Create bowtie index for reference genome", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "bowtie2_build": "Builds bowtie index for reference genome", "ribowaltz": "Calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data"}}, "target": "bowtie_build", "target_idx": 1}
{"id": "mod_braker3_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gene prediction in novel genomes using RNA-seq and protein homology information (tools: braker3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "variancepartition_dream": "Runs a differential expression analysis with dream() from variancePartition R package", "braker3": "Gene prediction in novel genomes using RNA-seq and protein homology information", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs"}}, "target": "braker3", "target_idx": 2}
{"id": "mod_ffq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA. (tools: ffq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA.", "fastqdl": "Download FASTQ files from SRA or ENA repositories.", "rpbp/getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF"}}, "target": "ffq", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_23", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_fastq_2_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_1_38", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_38", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_snippy_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rapid haploid variant calling (tools: snippy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt_stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "ferrohgvs_normalize": "Normalize HGVS variant descriptions to canonical form with ferro", "graphtyper_genotype": "Tools for population-scale genotyping using pangenome graphs.", "snippy_run": "Rapid haploid variant calling", "htodemux": "Demultiplex samples based on data from cell hashing."}}, "target": "snippy_run", "target_idx": 3}
{"id": "mod_graphtyper_vcfconcatenate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tools for population-scale genotyping using pangenome graphs. (tools: graphtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat/cat": "A module for concatenation of gzipped or uncompressed files", "agat/sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file", "vcf_annotate_ensemblvep_snpeff": "Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkf", "csvtk/concat": "Concatenate two or more CSV (or TSV) tables into a single table", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs."}}, "target": "graphtyper/vcfconcatenate", "target_idx": 4}
{"id": "mod_pairtools_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split a .pairsam file into .pairs and .sam. (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools/split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bedtools/split": "Split BED files into several smaller BED files", "helitronscanner/draw": "HelitronScanner draw tool for Helitron transposons in genomes", "helitronscanner/scan": "HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes", "pairtools/split": "Split a .pairsam file into .pairs and .sam."}}, "target": "pairtools/split", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_2_39", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_icountmini_segment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Formats a GTF file for use with iCount sigxls (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"somalier_ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "svync": "A tool to standardize VCF files from structural variant callers", "icountmini_peaks": "Runs iCount peaks on a BED file of crosslinks", "icountmini_segment": "Formats a GTF file for use with iCount sigxls", "icountmini_metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks."}}, "target": "icountmini_segment", "target_idx": 3}
{"id": "mod_angsd_soapsnpcalibration_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd/realsfs": "Estimate site frequency spectrum from site allele frequencies", "bcftools/convert": "Converts certain output formats to VCF", "angsd/soapsnpcalibration": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments.", "cache_download_ensemblvep_snpeff": "downlad annotation cache for snpeff and ensemblvep", "bam_docounts_contamination_angsd": "Calculate contamination of the X-chromosome with ANGSD"}}, "target": "angsd/soapsnpcalibration", "target_idx": 2}
{"id": "mod_porechop_porechop_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adapter removal and demultiplexing of Oxford Nanopore reads (tools: porechop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"porechop_porechop": "Adapter removal and demultiplexing of Oxford Nanopore reads", "cutadapt": "Removes adapter sequences from sequencing reads", "hifiadapterfilt_hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "biscuit_biscuitblaster": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit", "htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst"}}, "target": "porechop_porechop", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_24", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "core_tool_gatk_haplotypecaller_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Germline SNP and Indel variant calling via local de novo haplotype assembly across active genomic regions.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"strelka2": null, "deepvariant": null, "freebayes": null, "gatk_haplotypecaller": null, "mutect2": null}}, "target": "gatk_haplotypecaller", "target_idx": 3}
{"id": "resource_biscuit_qc_4", "category": "resource_profiling", "state": {"process": "BISCUIT_QC", "tool": "biscuit/qc", "description": "Perform basic quality control on a BAM file generated with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_QC (Perform basic quality control on a BAM file generated with Biscuit) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_hamronization_deeparg_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize DeepARG outputs using the hAMRonization specification (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization_deeparg": null, "deeptools_plotprofile": null, "argnorm": null, "hamronization_amrfinderplus": null, "cmseq_polymut": null}}, "target": "hamronization_deeparg", "target_idx": 0}
{"id": "resource_bowtie2_build_2", "category": "resource_profiling", "state": {"process": "BOWTIE2_BUILD", "tool": "bowtie2/build", "description": "Builds bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_BUILD (Builds bowtie index for reference genome) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_leafcutter_clusterregtools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alternative splicing analysis (tools: leafcutter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "leafcutter/clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter", "hisat2/extractsplicesites": "Extracts splicing sites from a gtf files", "pairtools/parse": "Find ligation junctions in .sam, make .pairs", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications"}}, "target": "leafcutter/clusterregtools", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wes_pe_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Paired-end Whole Exome Sequencing (WES) target capture", "data_format": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from Agilent/Twist exome target capture?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_funcscan_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze (Meta-)genome screening for functional and natural product gene sequences. Topics: amp, amr, antibiotic-resistance, antimicrobial-peptides, antimicrobial-resistance-genes, arg. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]"}}, "target": "funcscan", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_44", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_hmmer_hmmpress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: compress and index profile database for hmmscan (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmfetch": "extract hmm from hmm database file or create index for hmm database", "hmmer_hmmpress": "compress and index profile database for hmmscan", "hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment", "cnvkit_batch": "Copy number variant detection from high-throughput sequencing data", "singlem_dbdownload": "Download the SingleM metapackage database used for metagenome profiling"}}, "target": "hmmer_hmmpress", "target_idx": 1}
{"id": "mod_popscle_dscpileup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode. (tools: popscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hasheddrops": "Generating cell hashing calls from a matrix of count data.", "vsearch/dereplicate": "Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same l", "popscle/demuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "popscle/dscpileup": "Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode.", "fastq_extract_kraken_krakentools": "Extract classified Kraken2 reads by taxonomic id"}}, "target": "popscle/dscpileup", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_bam_3_1", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic tumor-normal calling from pre-aligned BAM files with entry step MUTECT2.", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,bam": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_2_28", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_6_4", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Genome analysis from reference-compressed CRAM files input samplesheet?", "criteria": {"sample,cram": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "resource_amulety_translate_2", "category": "resource_profiling", "state": {"process": "AMULETY_TRANSLATE", "tool": "amulety/translate", "description": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_TRANSLATE (A module to translate BCR and TCR nucleotide sequences into amino acid sequences) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_hhsuite_reformat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reformat a Multiple Sequence Alignment (MSA) file (tools: hhsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_genotypegvcfs": "Perform joint genotyping on one or more samples pre-called with HaplotypeCaller.", "cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity", "hmmer_eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie", "hhsuite_reformat": "Reformat a Multiple Sequence Alignment (MSA) file", "clustalo_align": "Align sequences using Clustal Omega"}}, "target": "hhsuite_reformat", "target_idx": 3}
{"id": "resource_bcftools_split_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SPLIT", "tool": "bcftools/split", "description": "Split a vcf file into files per chromosome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SPLIT (Split a vcf file into files per chromosome) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_2_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ", "pipeline": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_bam_markduplicates_picard_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats (tools: bam_markduplicates_picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dupblaster": "Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline ", "bam_markduplicates_picard": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats", "controlfreec_freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "gatk4spark_markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "clippy": "Runs the Clippy CLIP peak caller"}}, "target": "bam_markduplicates_picard", "target_idx": 1}
{"id": "resource_biscuit_epiread_4", "category": "resource_profiling", "state": {"process": "BISCUIT_EPIREAD", "tool": "biscuit/epiread", "description": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_EPIREAD (Summarizes read-level methylation (and optionally SNV) information from a\nBiscui) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_6_0", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_plink_genome_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates identity-by-descent over autosomal SNPs (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_genome": "Calculates identity-by-descent over autosomal SNPs", "plink_indeppairwise": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of varia", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "plink_extract": "Subset plink bfiles with a text file of variant identifiers", "metabat2_metabat2": "Metagenome binning of contigs"}}, "target": "plink_genome", "target_idx": 0}
{"id": "resource_blast_blastn_2", "category": "resource_profiling", "state": {"process": "BLAST_BLASTN", "tool": "blast/blastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_ctree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clone trees for Cancer Evolution studies from bulk sequencing data. (tools: ctree)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/sort": null, "ctree": null, "pbsv/discover": null, "spring/compress": null, "bamtofastq10x": null}}, "target": "ctree", "target_idx": 1}
{"id": "schema_std_readsimulator_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/readsimulator", "description": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/readsimulator?", "criteria": {"sample,seed": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,seed", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_4_2", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end FASTQ reads per library?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_5_2", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen", "pipeline": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/dualrnaseq, determine the input samplesheet column structure for: Dual RNA-seq simultaneous host and pathogen transcriptomics.", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_5_4", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Metagenomic MAG assembly with comparative groups.", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_3_0", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ATAC-seq chromatin accessibility with biological replicates with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "local_subworkflow_positionsofint_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should this step (custom/positionsofint) be packaged: Position of interest depth extraction?", "criteria": {"Leave them out": null, "Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 1}
{"id": "mod_rmarkdownnotebook_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render an rmarkdown notebook. Supports parametrization. (tools: rmarkdown)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rmarkdownnotebook": null, "umitools_prepareforrsem": null, "quartonotebook": null, "jupyternotebook": null, "mafft_align": null}}, "target": "rmarkdownnotebook", "target_idx": 0}
{"id": "field_constraint_bam_2_4", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "noul_mix_operator_async_emission_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_pbptyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assign PBP type of Streptococcus pneumoniae assemblies (tools: pbptyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"telescope_assign": "The telescope assign program finds overlapping reads between an alignment (SAM/BAM) and an annotation (GTF) th", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "minimac4_compressref": "Compression of a reference panel for genotype imputation to `.msav` format", "pbptyper": "Assign PBP type of Streptococcus pneumoniae assemblies"}}, "target": "pbptyper", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wes_pe_0_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_rpbp_getperiodiclengthsoffsets_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF-level scoring.\nDrops read lengths whose metagene profile is too sparsely populated,\nor whose periodicity Bayes factor is too low / too uncertain, so that\ndownstream P-site counting only uses read lengths with a clean\n3-nucleotide signal.\n\nWraps Rp-Bp's `get_periodic_lengths_and_offsets` Python helper directly.\nThresholds are configured via named flags in `ext.args`:\n`--min-count` (default: 1000), `--min-bf-mean` (default: 5),\n`--max-bf-var` (default: no limit), `--min-bf-likelihood` (default: 0.5).\nDefaults mirror `rpbp.defaults.metagene_options`. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr_logratio": null, "rpbp_estimateorfbayesfactors": null, "rpbp_getperiodiclengthsoffsets": null, "rpbp_selectfinalpredictionset": null, "tcoffee_tcs": null}}, "target": "rpbp_getperiodiclengthsoffsets", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_5_4", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cageseq, determine the input samplesheet column structure for: CAGE-seq 5-prime capped transcript end sequencing.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,tss_bed": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "schema_std_omicsgenetraitassociation_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/omicsgenetraitassociation", "assay": "omicsgenetraitassociation pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/omicsgenetraitassociation (A nextflow pipeline which integrates multiple omic data stre)?", "criteria": {"sample,id,data_path,fastq_dir,cytaimage": null, "seeds,network,perturbed_networks": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "sample,trait,pascal,twas,additional_sources", "target_idx": 3}
{"id": "intent_ask_question_11", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "ask_question": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_bedtools_jaccard_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate Jaccard statistic b/w two feature files. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": null, "gridss/annotate": null, "atlas/call": null, "bedtools/jaccard": null, "fgumi/clip": null}}, "target": "bedtools/jaccard", "target_idx": 3}
{"id": "noul_single_hyphen_cli_params_error_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_nanoseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Nanopore demultiplexing, QC and alignment pipeline. Topics: alignment, demultiplexing, nanopore, qc. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp"}}, "target": "nanoseq", "target_idx": 1}
{"id": "mod_bakta_bakta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotation of bacterial genomes (isolates, MAGs) and plasmids (tools: bakta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_splitncigarreads": "Splits reads that contain Ns in their cigar string", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "mageck_count": "mageck count for functional genomics, reads are usually mapped to a specific sgRNA", "bakta_bakta": "Annotation of bacterial genomes (isolates, MAGs) and plasmids"}}, "target": "bakta_bakta", "target_idx": 4}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_11", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_core10_chipseq_1_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Histone modification and TF ChIP-seq peak calling with MACS2, HOMER motif enrichment, and differential binding analysis.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"atacseq": null, "ampliseq": null, "eager": null, "taxprofiler": null, "rnaseq": null, "sarek": null, "chipseq": null, "scrnaseq": null, "mag": null, "viralrecon": null}}, "target": "chipseq", "target_idx": 6}
{"id": "noul_dynamic_resource_allocation_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_channel_factory_inside_process_body_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_14", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_yara_mapper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using YARA (tools: yara)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yara_mapper": "Align reads to a reference genome using YARA", "tabix_tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,", "pychopper": "Identify, orient and trim nanopore cDNA reads", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}}, "target": "yara_mapper", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_create_umi_consensus_fgbio_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_CREATE_UMI_CONSENSUS_FGBIO", "modules": ["bwa/index", "bwa/mem", "bwamem2/mem", "bwamem2/index", "fgbio/fastqtobam", "fgbio/groupreadsbyumi", "fgbio/callmolecularconsensusreads", "fgbio/callduplexconsensusreads", "fgbio/filterconsensusreads", "samblaster", "samtools/bam2fq", "samtools/sort", "samtools/index", "samtools/fastq", "fgbio/zipperbams"], "description": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads"}, "question": {"type": "choice", "instructions": "How should FASTQ_CREATE_UMI_CONSENSUS_FGBIO (bwa/index, bwa/mem, bwamem2/mem, bwamem2/index, fgbio/fastqtobam, fgbio/groupreadsbyumi, fgbio/callmolecularconsensusreads, fgbio/callduplexconsensusreads, fgbio/filterconsensusreads, samblaster, samtools/bam2fq, samtools/sort, samtools/index, samtools/fastq, fgbio/zipperbams) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_CREATE_UMI_CONSENSUS_FGBIO": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_create_umi_consensus_fgbio": null}}, "target": "Use nf-core subworkflow fastq_create_umi_consensus_fgbio", "target_idx": 3}
{"id": "mod_baysor_preview_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract neighborhood composition vectors (NVCs) from a dataset. (tools: baysor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "baysor/preview": "Extract neighborhood composition vectors (NVCs) from a dataset.", "rhocall/viz": "Call regions of homozygosity and make tentative UPD calls", "rtgtools/bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "blat": "Queries a sequence subject"}}, "target": "baysor/preview", "target_idx": 1}
{"id": "schema_std_epitopeprediction_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/epitopeprediction. Description: A bioinformatics best-practice analysis pipeline for epitope prediction and annotation.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/epitopeprediction.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,barcode": null, "sample,id,data_path,fastq_dir,cytaimage": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,alleles,mhc_class,filename", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_wgs_7_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "template": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "schema_std_mhcquant_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/mhcquant. Description: Identify and quantify MHC eluted peptides from mass spectrometry raw data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/mhcquant.", "criteria": {"gene_name,alignment,tree,suite,tool": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,fasta,protein,gbk,gff": null}}, "target": "ID,Sample,Condition,ReplicateFileName,Fasta", "target_idx": 1}
{"id": "pipe_all101_rnaseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.. Topics: rna, rna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": null, "stableexpression": null, "rnaseq": null, "callingcards": null, "demo": null, "epitopeprediction": null, "bactmap": null, "rnasplice": null, "dualrnaseq": null, "lsmquant": null}}, "target": "rnaseq", "target_idx": 2}
{"id": "mod_cnvpytor_partition_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate segmentation for specified bin size (multiple bin sizes separate by space) (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ilastik_pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "proovframe_fix": "frame-shift correction for long read (meta)genomics - fix frameshifts in reads", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples).", "canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "cnvpytor_partition": "Calculate segmentation for specified bin size (multiple bin sizes separate by space)"}}, "target": "cnvpytor_partition", "target_idx": 4}
{"id": "noul_mix_operator_async_emission_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "schema_std_ampliseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay": "ampliseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/ampliseq (Amplicon sequencing analysis workflow using DADA2 and QIIME2)?", "criteria": {"sample,seq_data,pbi,start_from": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,id,data_path,fastq_dir,cytaimage": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample,fastq_1,fastq_2,sampleID,forwardReads", "target_idx": 1}
{"id": "pipe_all101_sarek_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing. Topics: annotation, cancer, gatk4, genomics, germline, pre-processing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralintegration": null, "demo": null, "variantbenchmarking": null, "sarek": null, "bacass": null, "viralrecon": null, "ribomsqc": null, "pathogensurveillance": null, "chipseq": null, "hic": null}}, "target": "sarek", "target_idx": 3}
{"id": "field_constraint_sex_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"pattern: ^\\S+\\.gz$": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_39", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "pipe_all101_fastquorum_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs). Topics: consensus, umi, umis, unique-molecular-identifier. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hic": null, "pathogensurveillance": null, "multiplesequencealign": null, "mnaseseq": null, "denovotranscript": null, "fastquorum": null, "chipseq": null, "differentialabundance": null}}, "target": "fastquorum", "target_idx": 5}
{"id": "mod_snpsift_annmemcreate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create memory-optimized SnpSift vardb databases from VCF files for use with SnpSift annMem annotation.\nConverts VCF files (e.g. ClinVar, dbSNP, Cosmic) into indexed dataframes for fast lookup. (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/annotate": "Add or remove annotations.", "infernal/cmsearch": "Search covariance models against a sequence database", "deacon/indexunion": "Combine multiple deacon indexes (A ∪ B ...)", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "snpsift/annmemcreate": "Create memory-optimized SnpSift vardb databases from VCF files for use with SnpSift annMem annotation.\nConvert"}}, "target": "snpsift/annmemcreate", "target_idx": 4}
{"id": "mod_tmb_pytmb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool. (tools: tmb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"evigene/tr2aacds": null, "openms/idscoreswitcher": null, "plink2/score": null, "yara/index": null, "tmb/pytmb": null}}, "target": "tmb/pytmb", "target_idx": 4}
{"id": "samplesheet_arch_epigenomics_hic_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/hic --input samplesheet.csv (Assay: Hi-C chromosome conformation capture mapping)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hi-C chromosome conformation capture mapping with entry step FASTQC.", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,matrix,contacts": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "local_subworkflow_preparereports_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should this step (custom/preparereports, multiqc) be packaged: Custom aggregation and MultiQC reporting?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPAREREPORTS": null, "Use nf-core subworkflow preparereports": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_7", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_44", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_10", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_4_3", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Circulating tumor DNA FASTQs across patient clinical draw intervals?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_rrnatranscripts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ribosomal RNA extraction from a GTF file. (tools: rrnatranscripts)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "motus/downloaddb": "Download the mOTUs database", "sylph/profile": "Sylph profile command for taxonoming profiling", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "rrnatranscripts": "Ribosomal RNA extraction from a GTF file."}}, "target": "rrnatranscripts", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_se_0_2", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "subworkflow_pkg_bam_rseqc_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_RSEQC", "modules": ["rseqc", "rseqc/tin", "rseqc/readduplication", "rseqc/readdistribution", "rseqc/junctionsaturation", "rseqc/junctionannotation", "rseqc/innerdistance", "rseqc/inferexperiment", "rseqc/bamstat"], "description": "Subworkflow to run multiple commands in the RSeqC package"}, "question": {"type": "choice", "instructions": "How should BAM_RSEQC (rseqc, rseqc/tin, rseqc/readduplication, rseqc/readdistribution, rseqc/junctionsaturation, rseqc/junctionannotation, rseqc/innerdistance, rseqc/inferexperiment, rseqc/bamstat) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_rseqc": null, "Local subworkflow BAM_RSEQC": null}}, "target": "Use nf-core subworkflow bam_rseqc", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_3", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_freebayes_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A haplotype-based variant detector (tools: freebayes)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngscheckmate_fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "pbjasmine": "Identify specific base modifications in PacBio HiFi reads by analyzing polymerase kinetic signatures", "freebayes": "A haplotype-based variant detector", "multivcfanalyzer": "SNP table generator from GATK UnifiedGenotyper with functionality geared for aDNA", "gatk4_printreads": "Print reads in the SAM/BAM/CRAM file"}}, "target": "freebayes", "target_idx": 2}
{"id": "samplesheet_arch_scrna_multiome_6_4", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Multiome single-cell joint RNA and ATAC chromatin input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,rna_fastq,atac_fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "mod_verifybamid_verifybamid_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure high quality sequence reads and reliable downstream analysis. (tools: verifybamid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_applybqsr": null, "checkm2/databasedownload": null, "verifybamid/verifybamid": null, "bam_impute_stitch": null, "checkm/qa": null}}, "target": "verifybamid/verifybamid", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_17", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_gatk4_filtervarianttranches_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply tranche filtering (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"maltextract": "Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "bcftools_pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "gatk4_filtervarianttranches": "Apply tranche filtering", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables"}}, "target": "gatk4_filtervarianttranches", "target_idx": 3}
{"id": "samplesheet_arch_amplicon_16s_paired_1_2", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,otu_table": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_macsyfinder_search_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search for macromolecular systems in protein datasets using MacSyFinder (tools: macsyfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macsyfinder/search": "Search for macromolecular systems in protein datasets using MacSyFinder", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "shigatyper": "Determine Shigella serotype from Illumina or Oxford Nanopore reads", "pbmm2/align": "Alignment with PacBio's minimap2 frontend", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "macsyfinder/search", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_7_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_42", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_bamtools_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files. (tools: bamtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bamtools_stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "ascat": "copy number profiles of tumour cells.", "slamdunk_map": "Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings.", "yahs": "Performs assembly scaffolding using YaHS"}}, "target": "bamtools_split", "target_idx": 0}
{"id": "mod_bwameth_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of BS-Seq reads using bwameth (tools: bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "bwameth/align": "Performs alignment of BS-Seq reads using bwameth", "tmb/pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "bwameth/index": "Performs indexing of c2t converted reference genome", "parabricks/fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to "}}, "target": "bwameth/align", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_newick_epang_gappa_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_NEWICK_EPANG_GAPPA", "modules": ["hmmer/hmmbuild", "hmmer/hmmalign", "hmmer/eslalimask", "hmmer/eslreformat", "clustalo/align", "mafft/align", "epang/place", "epang/split", "gappa/examinegraft", "gappa/examineassign", "gappa/examineheattree"], "description": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in nf-core/phyloplace."}, "question": {"type": "choice", "instructions": "How should FASTA_NEWICK_EPANG_GAPPA (hmmer/hmmbuild, hmmer/hmmalign, hmmer/eslalimask, hmmer/eslreformat, clustalo/align, mafft/align, epang/place, epang/split, gappa/examinegraft, gappa/examineassign, gappa/examineheattree) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_NEWICK_EPANG_GAPPA": null, "Leave them out": null, "Use nf-core subworkflow fasta_newick_epang_gappa": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_newick_epang_gappa", "target_idx": 2}
{"id": "core_tool_kraken2_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Exact k-mer matching taxonomic classifier mapping metagenomic reads to bacterial and viral reference genomes with lowest common ancestor algorithm.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"diamond": "Protein aligner", "metaphlan": "Marker gene classifier", "kraken2": "Taxonomic sequence classification system that uses exact k-mer matches", "motus": "Marker gene classifier", "centrifuge": "Taxonomic classifier"}}, "target": "kraken2", "target_idx": 2}
{"id": "mod_stardist_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cell and nuclear segmentation with star-convex shapes (tools: stardist)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"artic/minion": "Run the alignment/variant-call/consensus logic of the artic pipeline", "stardist": "Cell and nuclear segmentation with star-convex shapes", "xeniumranger/rename": "The xeniumranger rename module allows you to change the sample region_name and cassette_name throughout all th", "ilastik/multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell"}}, "target": "stardist", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_17", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_htslib_bgziptabix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multi-purpose module to compress, decompress and index files using bgzip and tabix. (tools: htslib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "pigz_compress": "Compresses files with pigz.", "amulety_balmpaired": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety.", "htslib_bgziptabix": "Multi-purpose module to compress, decompress and index files using bgzip and tabix."}}, "target": "htslib_bgziptabix", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_2_29", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_2_17", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "local_subworkflow_prepilluminareads_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should PREPILLUMINAREADS (trimmomatic) be built?", "criteria": {"Local subworkflow PREPILLUMINAREADS": null, "Use nf-core subworkflow prepilluminareads": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 0}
{"id": "pipe_all101_raredisease_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Call and score variants from WGS/WES of rare disease patients.. Topics: diagnostics, rare-disease, snv, structural-variants, variant-annotation, variant-calling. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pacvar": null, "molkart": null, "chipseq": null, "seqsubmit": null, "raredisease": null, "reportho": null, "diaproteomics": null, "metapep": null, "lsmquant": null, "epitopeprediction": null}}, "target": "raredisease", "target_idx": 4}
{"id": "resource_agat_convertspgff2gtf_1", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2GTF", "tool": "agat/convertspgff2gtf", "description": "Converts a GFF/GTF file into a proper GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2GTF (Converts a GFF/GTF file into a proper GTF file) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bismark_coverage2cytosine_0", "category": "resource_profiling", "state": {"process": "BISMARK_COVERAGE2CYTOSINE", "tool": "bismark/coverage2cytosine", "description": "Relates methylation calls back to genomic cytosine contexts."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_COVERAGE2CYTOSINE (Relates methylation calls back to genomic cytosine contexts.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_agat_convertspgff2tsv_1", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2TSV", "tool": "agat/convertspgff2tsv", "description": "Converts a GFF/GTF file into a TSV file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2TSV (Converts a GFF/GTF file into a TSV file) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_mapad_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create mapAD index for reference genome (tools: mapad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "biscuit/index": "Indexes a reference genome for use with Biscuit", "mapad/index": "Create mapAD index for reference genome", "parabricks/applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "methyldackel/mbias": "Generates methylation bias plots from alignments"}}, "target": "mapad/index", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_preprocess_seqkit_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_PREPROCESS_SEQKIT", "modules": ["fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup"], "description": "Subworkflow that preprocesses FASTQ files"}, "question": {"type": "choice", "instructions": "How should FASTQ_PREPROCESS_SEQKIT (fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_preprocess_seqkit": null, "Leave them out": null, "Local subworkflow FASTQ_PREPROCESS_SEQKIT": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_preprocess_seqkit", "target_idx": 0}
{"id": "mod_gunzip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses and decompresses files. (tools: gunzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunzip": "Compresses and decompresses files.", "crabz/compress": "Compress files with crabz", "foldcomp/decompress": "Decompression tool for foldcomp compressed structures", "cobs/classicconstruct": "Builds a classic bloom filter COBS index", "bam_create_som_pon_gatk": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a geno"}}, "target": "gunzip", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_34", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_minibwa_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a minibwa index for a reference genome (tools: minibwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/tsv2exprofiledb": "Conversion of expandable profile to databases to the MMseqs2 databases format", "freyja/demix": "specify the relative abundance of each known haplotype", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "bowtie/build": "Create bowtie index for reference genome", "minibwa/index": "Create a minibwa index for a reference genome"}}, "target": "minibwa/index", "target_idx": 4}
{"id": "mod_vamb_bin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Variational autoencoder for metagenomic binning (tools: vamb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"comebin_runcomebin": null, "vamb_bin": null, "ensemblvep_vep": null, "plasmidid": null, "ampcombi2_cluster": null}}, "target": "vamb_bin", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_0_3", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_12", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "pipe_all101_eager_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A fully reproducible and state-of-the-art ancient DNA analysis pipeline. Topics: adna, ancient-dna-analysis, ancientdna, genome, metagenomics, pathogen-genomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": null, "atacseq": null, "eager": null, "epitopeprediction": null, "viralmetagenome": null, "magmap": null, "isoseq": null, "fastquorum": null, "fetchngs": null, "mag": null}}, "target": "eager", "target_idx": 2}
{"id": "mod_plink2_score_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a scoring system to each sample in a plink 2 fileset (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/score": null, "plink2/indeppairwise": null, "helitronscanner/draw": null, "biscuit/index": null, "plink2/pmerge": null}}, "target": "plink2/score", "target_idx": 0}
{"id": "mod_polypolish_polish_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Polishing genome assemblies with short reads. (tools: polypolish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"modkit_callmods": "Call mods from a modbam, creates a new modbam with probabilities set to 100% if a base modification is called ", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "modkit_bedmethyltobigwig": "Convert a bedMethyl file to bigWig format using modkit", "expansionhunter": "Estimate repeat sizes using NGS data", "polypolish_polish": "Polishing genome assemblies with short reads."}}, "target": "polypolish_polish", "target_idx": 4}
{"id": "field_constraint_phenotype_0_11", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"format: file-path": null, "enum: [normal, tumor]": null, "type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_9", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_finaletoolkit_endmotifs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Measure the frequency of 5' k-mer end motifs. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit_endmotifs": "Measure the frequency of 5' k-mer end motifs.", "fastq_fastqc_umitools_fastp": "Read QC, UMI extraction and trimming", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "pydamage_filter": "Damage parameter estimation for ancient DNA", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "finaletoolkit_endmotifs", "target_idx": 0}
{"id": "schema_std_lsmquant_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/lsmquant", "assay": "lsmquant pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/lsmquant (A pipeline for processing and analysis of light-sheet micros)?", "criteria": {"sample_id,mapped,index,file_type": null, "sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "sample,fastq_1,fastq_2,rundir,tags": null}}, "target": "sample_id,img_directory,parameter_file", "target_idx": 1}
{"id": "subworkflow_pkg_bam_stats_mirna_mirtop_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STATS_MIRNA_MIRTOP", "modules": ["mirtop/gff", "mirtop/counts", "mirtop/export", "mirtop/stats"], "description": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 format."}, "question": {"type": "choice", "instructions": "How should BAM_STATS_MIRNA_MIRTOP (mirtop/gff, mirtop/counts, mirtop/export, mirtop/stats) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_STATS_MIRNA_MIRTOP": null, "Use nf-core subworkflow bam_stats_mirna_mirtop": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_stats_mirna_mirtop", "target_idx": 2}
{"id": "mod_checkm2_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM2 bin quality prediction (tools: checkm2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "checkv/endtoend": "Assess the quality of metagenome-assembled viral genomes.", "checkm2/databasedownload": "CheckM2 database download", "bwa/aln": "Find SA coordinates of the input reads for bwa short-read mapping", "checkm2/predict": "CheckM2 bin quality prediction"}}, "target": "checkm2/predict", "target_idx": 4}
{"id": "mod_emu_abundance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A taxonomic profiler for metagenomic 16S data optimized for error prone long reads. (tools: emu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"decoupler/decoupler": "decoupler is a package containing different statistical methods\nto extract biological activities from omics da", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "emu/abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads.", "cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "emu/abundance", "target_idx": 2}
{"id": "noul_subworkflow_structural_blocks_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_1_2", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_4_1", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering?", "criteria": {"sample,rrna_fasta": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "mod_skani_sketch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Storing skani sketches/indices on disk. (tools: skani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "fgumi_downsample": "Downsample a BAM by UMI family using streaming with fgumi", "skani_sketch": "Storing skani sketches/indices on disk.", "skani_search": "Memory-efficient ANI database queries with skani.", "grabix_check": "Checks if the input file is bgzip compressed or not"}}, "target": "skani_sketch", "target_idx": 2}
{"id": "mod_fastq_complexity_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform low-complexity filtering of FASTQ reads using a selectable tool.\nOne of PRINSEQ++, BBDuk, or fastp is executed based on the provided tool name.\nOnly complexity filtering is applied; no adapter trimming, read merging, or\nquality trimming is performed. (tools: fastq_complexity_filter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sawfish_discover": "SV candidate discovery from PacBio HiFi data", "ariba_getref": "Download and prepare database for Ariba analysis", "metaphlan_makedb": "Build MetaPhlAn database for taxonomic profiling.", "fastq_complexity_filter": "Perform low-complexity filtering of FASTQ reads using a selectable tool.\nOne of PRINSEQ++, BBDuk, or fastp is ", "ariba_run": "Query input FASTQs against Ariba formatted databases"}}, "target": "fastq_complexity_filter", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_4_3", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "template": "nf-core/eager"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_36", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_severus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Severus is a somatic structural variation (SV) caller for long reads (both PacBio and ONT) (tools: severus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last/postmask": "Post-alignment masking", "pbsv/discover": "pbsv - PacBio structural variant (SV) signature discovery tool", "rtgtools/svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs", "mageck/count": "mageck count for functional genomics, reads are usually mapped to a specific sgRNA", "severus": "Severus is a somatic structural variation (SV) caller for long reads (both PacBio and ONT)"}}, "target": "severus", "target_idx": 4}
{"id": "subworkflow_pkg_vcf_impute_minimac4_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_MINIMAC4", "modules": ["minimac4/compressref", "minimac4/impute", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute VCF files using MINIMAC4 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_MINIMAC4 (minimac4/compressref, minimac4/impute, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Local subworkflow VCF_IMPUTE_MINIMAC4": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow vcf_impute_minimac4": null}}, "target": "Use nf-core subworkflow vcf_impute_minimac4", "target_idx": 3}
{"id": "mod_dupradar_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assessment of duplication rates in RNA-Seq datasets (tools: dupradar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing/startocancerintrons": null, "dupradar": null, "sickle": null, "cooler/zoomify": null, "ctatsplicing/prepgenomelib": null}}, "target": "dupradar", "target_idx": 1}
{"id": "mod_bracken_combinebrackenoutputs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine output of metagenomic samples analyzed by bracken. (tools: bracken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "decoupler/decoupler": "decoupler is a package containing different statistical methods\nto extract biological activities from omics da", "tagbam": "A tool for tagging BAM files.", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "bracken/build": "Extends a Kraken2 database to be compatible with Bracken"}}, "target": "bracken/combinebrackenoutputs", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_22", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_biscuit_pileup_0", "category": "resource_profiling", "state": {"process": "BISCUIT_PILEUP", "tool": "biscuit/pileup", "description": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_PILEUP (Computes cytosine methylation and callable SNV mutations, optionally in referenc) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_taxprofiler_shotgun_4_3", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "template": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Short or long reads with run accession and library instrument platform?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_foldmason_msa2lddtreport_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Renders a visualization report using foldmason (tools: foldmason)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whatshap/phase": "Phase variants in a VCF file using long-read sequencing data", "foldmason/msa2lddtreport": "Renders a visualization report using foldmason", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "controlfreec/freec2bed": "Plot Freec output", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins"}}, "target": "foldmason/msa2lddtreport", "target_idx": 1}
{"id": "mod_kleborate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species complex (KpSC). (tools: kleborate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kleborate": "Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species", "abacas": "Contiguate draft genome assembly", "assemblyscan": "Assembly summary statistics in JSON format", "deeptools/multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "staphscan": "staphscan is a tool to screen genome assemblies of Staphylococcus aureus"}}, "target": "kleborate", "target_idx": 0}
{"id": "mod_osfclient_fetch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A python library and a command-line client for up- and downloading files to and from your Open Science Framework projects (tools: osfclient)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fcsgx/fetchdb": "Fetches the NCBI FCS-GX database using a provided manifest URL", "melon": "Performs taxonomic profiling of long metagenomic reads against the melon database", "osfclient/fetch": "A python library and a command-line client for up- and downloading files to and from your Open Science Framewo", "fastk/fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA."}}, "target": "osfclient/fetch", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_4", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_4_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ", "pipeline": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single HiFi BAM or FastQ?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_adapterremoval_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim sequencing adapters and collapse overlapping reads (tools: adapterremoval)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_bbduk": "Adapter and quality trimming of sequencing reads", "ripgrep": "ripgrep recursively searches directories for a regex pattern", "fusionreport_download": "Build DB for fusionreport", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "cutadapt": "Removes adapter sequences from sequencing reads"}}, "target": "adapterremoval", "target_idx": 3}
{"id": "mod_mitorsaw_haplotype_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mitorsaw analyses mitochondrial variants and identifies heteroplasmy and homoplasmy (tools: mitorsaw)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mitorsaw/haplotype": "Mitorsaw analyses mitochondrial variants and identifies heteroplasmy and homoplasmy", "rpbp/selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ", "fgumi/merge": "Merge pre-sorted BAM files into a single sorted BAM", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "gatk4/mutect2": "Call somatic SNVs and indels via local assembly of haplotypes."}}, "target": "mitorsaw/haplotype", "target_idx": 0}
{"id": "mod_bbmap_bbsplit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split sequencing reads by mapping them to multiple references simultaneously (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "wfmash": "a pangenome-scale aligner", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "bedtools_bamtobed": "Converts a bam file to a bed12 file.", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap"}}, "target": "bbmap_bbsplit", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic tumor-normal calling from pre-aligned BAM files)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic tumor-normal calling from pre-aligned BAM files.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Tumor-only somatic variant calling without matched normal. Input files: Paired-end FASTQ reads from tumor biopsy without matched normal.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_gatk4_selectvariants_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select a subset of variants from a VCF file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anndata_getsize": null, "elprep_filter": null, "gatk4_analyzecovariates": null, "gatk4_selectvariants": null, "gatk4_asereadcounter": null}}, "target": "gatk4_selectvariants", "target_idx": 3}
{"id": "mod_bcftools_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts certain output formats to VCF (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_convert": "Converts certain output formats to VCF", "bcftools_concat": "Concatenate VCF files", "stadeniolib_scramble": "Advanced sequence file format conversions", "bcftools_pluginfilltags": "Compute and fill various INFO tags", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables"}}, "target": "bcftools_convert", "target_idx": 0}
{"id": "noul_deprecated_dsl1_set_keyword_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_rnadnavar_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for rnadnavar. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]"}}, "target": "rnadnavar", "target_idx": 1}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_strelka_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA", "modules": ["gatk4/mergevcfs", "strelka/somatic"], "description": "Perform variant calling on a paired tumor normal set of samples using strelka somatic mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA (gatk4/mergevcfs, strelka/somatic) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka": null, "Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka", "target_idx": 0}
{"id": "mod_gappa_examineheattree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: colours a phylogeny with placement densities (tools: gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "pharmcat/matcher": "The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to", "gappa/examineheattree": "colours a phylogeny with placement densities", "cafe": "Analysis of gene family evolution", "epang/split": "splits an alignment into reference and query parts"}}, "target": "gappa/examineheattree", "target_idx": 2}
{"id": "mod_vcfexpress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter a VCF/BCF and optionally print by template expression. If no template is given the output will be VCF/BCF (tools: vcfexpress)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_coverage": "produces a histogram or table of coverage per chromosome", "atlas_call": "generate VCF file from a BAM file using various calling methods", "vcfexpress": "Filter a VCF/BCF and optionally print by template expression. If no template is given the output will be VCF/B", "cleanifier_filter": "Fast, lightweight contamination removal from microbiome data (FASTQ) using a probabilistic Cuckoo filter or Cu", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "vcfexpress", "target_idx": 2}
{"id": "resource_biscuit_epiread_2", "category": "resource_profiling", "state": {"process": "BISCUIT_EPIREAD", "tool": "biscuit/epiread", "description": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_EPIREAD (Summarizes read-level methylation (and optionally SNV) information from a\nBiscui) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_eager_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A fully reproducible and state-of-the-art ancient DNA analysis pipeline. Topics: adna, ancient-dna-analysis, ancientdna, genome, metagenomics, pathogen-genomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"eager": null, "reportho": null, "ampliseq": null, "methylseq": null, "taxprofiler": null}}, "target": "eager", "target_idx": 0}
{"id": "pipe_all101_airrflow_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework. Topics: airr, b-cell, immcantation, immunorepertoire, repseq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sarek": null, "phyloplace": null, "airrflow": null, "drop": null, "taxprofiler": null, "pacvar": null, "fastquorum": null, "scrnaseq": null}}, "target": "airrflow", "target_idx": 2}
{"id": "resource_blast_blastn_3", "category": "resource_profiling", "state": {"process": "BLAST_BLASTN", "tool": "blast/blastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_seqfu_derep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in the sequence header. Can dereplicate already dereplicated FASTA files, summing the numbers found in the headers. (tools: seqfu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_cnv_wisecondorx": "A subworkflow for calling CNVs using WisecondorX", "untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "seqfu_derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}}, "target": "seqfu_derep", "target_idx": 3}
{"id": "resource_busco_phylogenomics_4", "category": "resource_profiling", "state": {"process": "BUSCO_PHYLOGENOMICS", "tool": "busco/phylogenomics", "description": "Construct species phylogenies using BUSCO proteins"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PHYLOGENOMICS (Construct species phylogenies using BUSCO proteins) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should this step (custom/variantsofint) be packaged: Variant filtering and clinical annotation aggregation?", "criteria": {"Local subworkflow VARIANTSOFINT": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow variantsofint": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 0}
{"id": "field_constraint_sex_0_6", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"pattern: ^\\S+\\.gz$": null, "format: file-path": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_13", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "subworkflow_pkg_bam_impute_quilt2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_QUILT2", "modules": ["quilt/quilt2", "glimpse2/ligate", "bcftools/index"], "description": "Impute low-coverage BAM or CRAM inputs with QUILT2 and ligate chunked outputs per chromosome."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_QUILT2 (quilt/quilt2, glimpse2/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_impute_quilt2": null, "Leave them out": null, "Local subworkflow BAM_IMPUTE_QUILT2": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_impute_quilt2", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Genome analysis from reference-compressed CRAM files", "data_format": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns are standard for Genome analysis from reference-compressed CRAM files input samplesheet?", "criteria": {"sample,cram,crai": null, "sample,cram": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 0}
{"id": "pipe_all101_scnanoseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for 10xgenomics analysis? Specific context: Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics. Topics: 10xgenomics, long-read-sequencing, nanopore, rna-seq, rnaseq, scrna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "seqsubmit": "nf-core pipeline for data submission to ENA", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples"}}, "target": "scnanoseq", "target_idx": 4}
{"id": "mod_gatk4_filterintervals_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters intervals based on annotations and/or count statistics. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"treerecs": "Treerecs is an open-source (species- and gene-) tree reconciliation software distributed under the GNU AGPL li", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "bcftools/filter": "Filters VCF files", "gatk4/filterintervals": "Filters intervals based on annotations and/or count statistics."}}, "target": "gatk4/filterintervals", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_0_22", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_14", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_15", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "pipe_all101_drop_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "drop", "target_idx": 3}
{"id": "core_tool_salmon_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Transcript-level abundance estimation and pseudo-alignment directly from raw paired-end RNA-seq FASTQ reads without full genome mapping.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"rsem": "Quantification of transcript abundances", "featurecounts": "Count mapped reads for genomic features", "samtools": "Utilities for manipulating SAM/BAM files", "salmon": "Highly accurate and fast transcript-level quantification from RNA-seq reads", "kallisto": "Near-optimal RNA-seq quantification"}}, "target": "salmon", "target_idx": 3}
{"id": "mod_cooler_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple coolers with identical axes (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler/merge": "Merge multiple coolers with identical axes", "gatk4/mergemutectstats": "Merges mutect2 stats generated on different intervals/regions", "biobambam/bammerge": "Merge a list of sorted bam files", "bedtools/merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "mgikit/demultiplex": "Demultiplex MGI fastq files"}}, "target": "cooler/merge", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_7_1", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fast5": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "field_constraint_bam_1_4", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "resource_anndata_getsize_0", "category": "resource_profiling", "state": {"process": "ANNDATA_GETSIZE", "tool": "anndata/getsize", "description": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_GETSIZE (Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_28", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for Fungal ITS1/ITS2 marker gene amplicon surveillance. Input files: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_hmtnote_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Human mitochondrial variants annotation using HmtVar. Contains .plk file with annotation, so can be run offline (tools: hmtnote)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mtnucratio": "A small Java tool to calculate ratios between MT and nuclear sequencing reads in a given BAM file.", "hmtnote/annotate": "Human mitochondrial variants annotation using HmtVar. Contains .plk file with annotation, so can be run offlin", "pycoqc": "write your description here", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "hmtnote/annotate", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_4_1", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_0_41", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_bamtools_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files. (tools: bamtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec/makegraph2": "Plot Freec output", "fgumi/fastq": "Convert a BAM file to interleaved FASTQ format with fgumi", "bamtools/split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "ascat": "copy number profiles of tumour cells.", "bamtools/stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "bamtools/split", "target_idx": 2}
{"id": "mod_gappa_examinegraft_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Grafts query sequences from phylogenetic placement on the reference tree (tools: gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk/sort": "Sort  CSV (or TSV) tables", "numorph/intensity": "performs shading correction and intensity normalization between tile stacks", "gappa/examinegraft": "Grafts query sequences from phylogenetic placement on the reference tree", "fastme": "Distance-based phylogeny with FastME", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast "}}, "target": "gappa/examinegraft", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_5_3", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/metatdenovo, determine the input samplesheet column structure for: Environmental community metatranscriptomics de novo assembly.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null, "sample,rrna_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "pipe_all101_rnastructurome_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data. Topics: dms, map, rna-structure, rnacentral, rnaframework, rt-stop. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]"}}, "target": "rnastructurome", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_34", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_phyloflash_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illumina (meta)genomic dataset. (tools: phyloflash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"phyloflash": "phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illum", "deepbgc/pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "raw2ometiff": "write your description here"}}, "target": "phyloflash", "target_idx": 0}
{"id": "field_constraint_status_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "resource_busco_generateplot_4", "category": "resource_profiling", "state": {"process": "BUSCO_GENERATEPLOT", "tool": "busco/generateplot", "description": "BUSCO plot generation tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_GENERATEPLOT (BUSCO plot generation tool) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_4_2", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 1}
{"id": "resource_atlasgeneannotationmanipulation_gtf2featureannotation_1", "category": "resource_profiling", "state": {"process": "ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION", "tool": "atlasgeneannotationmanipulation/gtf2featureannotation", "description": "Generate tables of feature metadata from GTF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION (Generate tables of feature metadata from GTF files) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_2_0", "category": "samplesheet_schema", "state": {"technology": "Spatial In Situ", "workflow_entry": "INPUT_CHECK", "library_inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_41", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "subworkflow_pkg_tiff_segmentation_vpt_0", "category": "subworkflow_packaging", "state": {"subworkflow": "TIFF_SEGMENTATION_VPT", "modules": ["vizgenpostprocessing/preparesegmentation", "vizgenpostprocessing/runsegmentationontile", "vizgenpostprocessing/compiletilesegmentation"], "description": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool"}, "question": {"type": "choice", "instructions": "How should TIFF_SEGMENTATION_VPT (vizgenpostprocessing/preparesegmentation, vizgenpostprocessing/runsegmentationontile, vizgenpostprocessing/compiletilesegmentation) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow TIFF_SEGMENTATION_VPT": null, "Use nf-core subworkflow tiff_segmentation_vpt": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow tiff_segmentation_vpt", "target_idx": 2}
{"id": "mod_paragraph_multigrmpy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genotype structural variants using paragraph and grmpy (tools: paragraph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/call": null, "fcs/fcsgx": null, "paragraph/multigrmpy": null, "isoseq3/tag": null, "annotsv/annotsv": null}}, "target": "paragraph/multigrmpy", "target_idx": 2}
{"id": "mod_rseqc_tin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate TIN (transcript integrity number) from RNA-seq reads (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "purgedups/splitfa": "Split fasta file by 'N's to aid in self alignment for duplicate purging", "dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "rseqc/tin": "Calculate TIN (transcript integrity number) from RNA-seq reads", "leviosam2/index": "Index chain files for lift over"}}, "target": "rseqc/tin", "target_idx": 3}
{"id": "mod_cat_cat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module for concatenation of gzipped or uncompressed files (tools: cat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qsv_cat": null, "crabz_compress": null, "cat_cat": null, "opt_stat": null, "mobsuite_typer": null}}, "target": "cat_cat", "target_idx": 2}
{"id": "resource_bwa_index_5", "category": "resource_profiling", "state": {"process": "BWA_INDEX", "tool": "bwa/index", "description": "Create BWA index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_INDEX (Create BWA index for reference genome) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_0_2", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_smartseq_plate_based_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq)", "question": {"type": "choice", "instructions": "Which columns are standard for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq input samplesheet?", "criteria": {"sample,well,fastq": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_cnvkit_antitarget_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Derive off-target (“antitarget”) bins from target regions. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_annotate_ensemblvep": null, "cnvnator_cnvnator": null, "cnvkit_access": null, "tmb_pytmb": null, "cnvkit_antitarget": null}}, "target": "cnvkit_antitarget", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_4", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_antismash_antismashlitedownloaddatabases_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs. (tools: antismash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_plotvcfstats": "Plots the output of bcftools stats", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "last_mafconvert": "Converts MAF alignments in another format.", "deepbgc_pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "antismash_antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt"}}, "target": "antismash_antismashlitedownloaddatabases", "target_idx": 4}
{"id": "mod_sistr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serovar prediction of salmonella assemblies (tools: sistr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sistr": "Serovar prediction of salmonella assemblies", "bcftools/merge": "Merge VCF files", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "sistr", "target_idx": 0}
{"id": "field_constraint_fastq_1_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "resource_bamcmp_4", "category": "resource_profiling", "state": {"process": "BAMCMP", "tool": "bamcmp", "description": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For instance, filtering out mouse reads from patient derived xenograft mouse models (PDX)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCMP (Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_pixelator_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pixelator. Description: Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pixelator.", "criteria": {"patient,sample,fastq_1,fastq_2,bam": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "sample_id,bam,vcf,library_id,lane": null, "sample,fastq_1,fastq_2,rundir,tags": null}}, "target": "sample,fastq_1,fastq_2,pool,hash_index", "target_idx": 1}
{"id": "subworkflow_pkg_bam_impute_quilt2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_QUILT2", "modules": ["quilt/quilt2", "glimpse2/ligate", "bcftools/index"], "description": "Impute low-coverage BAM or CRAM inputs with QUILT2 and ligate chunked outputs per chromosome."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_QUILT2 (quilt/quilt2, glimpse2/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_impute_quilt2": null, "Local subworkflow BAM_IMPUTE_QUILT2": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_impute_quilt2", "target_idx": 0}
{"id": "schema_std_spatialaxe_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "description": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/spatialaxe?", "criteria": {"sample_id,idat_red,idat_green,group": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample,bundle,image": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "sample,bundle,image", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_named_output_channel_access_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_sex_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "format: file-path": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_1_2", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_status_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"format: file-path": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "schema_std_riboseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "description": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/riboseq?", "criteria": {"patient,sample,fastq_1,fastq_2,bam": null, "sample,run,group,short_reads_1,short_reads_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,fastq_1,fastq_2,strandedness,type", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_se_0_0", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "mod_bedtools_maskfasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: masks sequences in a FASTA file based on intervals defined in a feature file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/maskfasta": "masks sequences in a FASTA file based on intervals defined in a feature file.", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "purecn/run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "ucsc/wigtobigwig": "Convert ascii format wig file to binary big wig format"}}, "target": "bedtools/maskfasta", "target_idx": 0}
{"id": "mod_gapseq_requestdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download gapseq reference sequence database for metabolic pathway prediction (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"toulligqc": "A post sequencing QC tool for Oxford Nanopore sequencers", "gapseq_requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "prinseqplusplus": "PRINSEQ++ is a C++ implementation of the prinseq-lite.pl program. It can be used to filter, reformat or trim g", "blast_makeblastdb": "Builds a BLAST database", "blast_blastdbcmd": "Retrieve entries from a BLAST database"}}, "target": "gapseq_requestdb", "target_idx": 1}
{"id": "mod_mirdeep2_mirdeep2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs. It integrates the mapping of sequencing reads to the genome and predicts miRNA precursors and mature miRNAs. (tools: mirdeep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop/export": null, "mirdeep2/mirdeep2": null, "tidk/search": null, "mirdeep2/mapper": null, "numorph/resample": null}}, "target": "mirdeep2/mirdeep2", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_0", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_10", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_bcftools_rohviz_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualise the output of bcftools roh (tools: roh-viz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bammarkduplicates2": "Locate and tag duplicate reads in a BAM file", "drep_dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome", "amulety_embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "bcftools_rohviz": "Visualise the output of bcftools roh", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}}, "target": "bcftools_rohviz", "target_idx": 3}
{"id": "mod_flye_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: De novo assembler for single molecule sequencing reads (tools: flye)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "mobsuite/typer": "Bacterial plasmid typing and mobility prediction", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "controlfreec/freec2circos": "Format Freec output to circos input format", "flye": "De novo assembler for single molecule sequencing reads"}}, "target": "flye", "target_idx": 4}
{"id": "resource_bbmap_bbmerge_4", "category": "resource_profiling", "state": {"process": "BBMAP_BBMERGE", "tool": "bbmap/bbmerge", "description": "Merging overlapping paired reads into a single read."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBMERGE (Merging overlapping paired reads into a single read.) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_yahs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs assembly scaffolding using YaHS (tools: yahs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"longstitch": "\"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - ", "tabix/tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,", "ragtag/scaffold": "Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. G", "yahs": "Performs assembly scaffolding using YaHS", "sentieon/staralign": "Align reads to a reference genome using Sentieon STAR"}}, "target": "yahs", "target_idx": 3}
{"id": "mod_shapeit5_phaserare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to phase rare variants onto a scaffold of common variants (output of phase_common / ligate).\nRequire feature AVX2. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse2/splitreference": null, "elprep/fastatoelfasta": null, "fastq_taxonomic_profile_metaphlan": null, "hiphase": null, "shapeit5/phaserare": null}}, "target": "shapeit5/phaserare", "target_idx": 4}
{"id": "noul_deprecated_dsl1_set_keyword_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_blast_blastdbcmd_5", "category": "resource_profiling", "state": {"process": "BLAST_BLASTDBCMD", "tool": "blast/blastdbcmd", "description": "Retrieve entries from a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTDBCMD (Retrieve entries from a BLAST database) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_methylseq_bisulfite_0_0", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs", "pipeline": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,cpg,methylation": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/dualrnaseq", "assay_type": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "data_format": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null, "sample,host_fasta": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_5", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_1_3", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_slamseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze SLAMSeq processing and analysis pipeline. Topics: differential-expression, quantseq, slamseq, transcriptomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": null, "viralintegration": null, "mnaseseq": null, "rnafusion": null, "readsimulator": null, "createpanelrefs": null, "slamseq": null, "mag": null, "metaboigniter": null, "lsmquant": null}}, "target": "slamseq", "target_idx": 6}
{"id": "mod_parabricks_fq2bammeth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to a reference genome, performing local alignment, and producing alignment for different parts of the query sequence (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_references": "Functionality for dealing with references that may be useful for any Nextflow pipeline", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "busco_busco": "Benchmarking Universal Single Copy Orthologs", "parabricks_fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap"}}, "target": "parabricks_fq2bammeth", "target_idx": 3}
{"id": "mod_rastair_mbias_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assess C->T conversion as a readout for methylation on a per-read-position basis. (tools: rastair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/align": null, "bismark/report": null, "rastair/mbias": null, "gtdbtk/gtdbtoncbimajorityvote": null, "hamronization/summarize": null}}, "target": "rastair/mbias", "target_idx": 2}
{"id": "mod_catpack_addnames_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack_addnames": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "delly_call": "Call structural variants", "catpack_summarise": "Summarises results from CAT/BAT/RAT classification steps", "catpack_reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "sylph_sketchgenomes": "Sylph profile command for taxonoming profiling of genomes"}}, "target": "catpack_addnames", "target_idx": 0}
{"id": "pipe_all101_pixelator_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for molecular-pixelation analysis? Specific context: Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB). Topics: molecular-pixelation, pixelator, pixelgen-technologies, proteins, single-cell, single-cell-omics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step"}}, "target": "pixelator", "target_idx": 7}
{"id": "mod_genotyphi_parse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genotype Salmonella Typhi from Mykrobe results (tools: genotyphi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genotyphi/parse": "Genotype Salmonella Typhi from Mykrobe results", "hamronization/amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "bcftools/pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "beagle5/beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "deepvariant/postprocessvariants": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat"}}, "target": "genotyphi/parse", "target_idx": 0}
{"id": "resource_bracken_build_5", "category": "resource_profiling", "state": {"process": "BRACKEN_BUILD", "tool": "bracken/build", "description": "Extends a Kraken2 database to be compatible with Bracken"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BUILD (Extends a Kraken2 database to be compatible with Bracken) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_0_3", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_0_0", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,well,fastq": null, "sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_deepvariant_makeexamples_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transforms the input alignments to a format suitable for the deep neural network variant caller (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepvariant_makeexamples": null, "aardvark_merge": null, "catpack_summarise": null, "fasta_bgzip_index_dict_samtools": null, "bcftools_concat": null}}, "target": "deepvariant_makeexamples", "target_idx": 0}
{"id": "mod_macse_refinealignment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: improves the input nucleotide alignment in a codon-aware manner (tools: macse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metaphlan3/metaphlan3": null, "emboss/cons": null, "muscle5/super5": null, "macse/refinealignment": null, "ucsc/bigwigaverageoverbed": null}}, "target": "macse/refinealignment", "target_idx": 3}
{"id": "core_tool_kallisto_bustools_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Ultra-fast pseudoalignment and barcode/UMI processing for single-cell RNA-seq generating bustools count matrices.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"cellranger": "10x Chromium pipeline", "alevin": "Salmon single-cell", "kallisto_bustools": "Kallisto bustools workflow for rapid single-cell RNA-seq quantification and UMI counting", "salmon": "Bulk quantifier", "starsolo": "STAR single-cell"}}, "target": "kallisto_bustools", "target_idx": 2}
{"id": "intent_ask_question_22", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "mod_checkv_downloaddatabase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct the database necessary for checkv's quality assessment (tools: checkv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem3_gem3indexer": "Create a GEM index from a FASTA file", "checkm_lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "checkv_downloaddatabase": "Construct the database necessary for checkv's quality assessment", "hmmer_eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "checkv_endtoend": "Assess the quality of metagenome-assembled viral genomes."}}, "target": "checkv_downloaddatabase", "target_idx": 2}
{"id": "pipe_all101_differentialabundance_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq. Topics: atac-seq, chip-seq, deseq2, differential-abundance, differential-expression, gsea. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": null, "proteinfold": null, "differentialabundance": null, "mag": null, "proteinannotator": null, "nascent": null, "pairgenomealign": null, "proteinfamilies": null, "kmermaid": null, "drugresponseeval": null}}, "target": "differentialabundance", "target_idx": 2}
{"id": "resource_bwafastalign_index_0", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_INDEX", "tool": "bwafastalign/index", "description": "Create BWA-FASTALIGN index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_INDEX (Create BWA-FASTALIGN index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_high", "target_idx": 0}
{"id": "field_constraint_fastq_2_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "pipe_all101_viralrecon_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Assembly and intrahost/low-frequency variant calling for viral samples. Topics: amplicon, artic, assembly, covid-19, covid19, illumina. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": null, "methylseq": null, "coproid": null, "circdna": null, "variantbenchmarking": null, "epitopeprediction": null, "smrnaseq": null, "rnavar": null, "imcyto": null, "viralrecon": null}}, "target": "viralrecon", "target_idx": 9}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_4_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FastQ reads per sample?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_agat_spflagshortintrons_2", "category": "resource_profiling", "state": {"process": "AGAT_SPFLAGSHORTINTRONS", "tool": "agat/spflagshortintrons", "description": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting the data to EBI.\n(Typical EBI error message: ********ERROR: Intron usually expected to be at least 10 nt long. Please check the accuracy)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFLAGSHORTINTRONS (The script flags the short introns with the attribute <pseudo>. Is is usefull to) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_openms_decoydatabase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a decoy peptide database from a standard FASTA database. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lofreq/viterbi": "Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are availabl", "antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "parabricks/minimap2": "NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference da", "openms/decoydatabase": "Create a decoy peptide database from a standard FASTA database.", "blast/makeblastdb": "Builds a BLAST database"}}, "target": "openms/decoydatabase", "target_idx": 3}
{"id": "mod_minimap2_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: minimap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "bcftools_reheader": "Reheader a VCF file", "gatk4_samtofastq": "Converts BAM/SAM file to FastQ format", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "minimap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences"}}, "target": "minimap2_align", "target_idx": 4}
{"id": "samplesheet_arch_cutandrun_pe_3_0", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CUT&RUN / CUT&TAG chromatin profiling with IgG control with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "subworkflow_pkg_bam_subsampledepth_samtools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SUBSAMPLEDEPTH_SAMTOOLS", "modules": ["samtools/coverage", "samtools/view"], "description": "Subsample a BAM/CRAM/SAM file using samtools to a given mean depth."}, "question": {"type": "choice", "instructions": "How should BAM_SUBSAMPLEDEPTH_SAMTOOLS (samtools/coverage, samtools/view) be structured in DSL2?", "criteria": {"Local subworkflow BAM_SUBSAMPLEDEPTH_SAMTOOLS": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_subsampledepth_samtools": null}}, "target": "Use nf-core subworkflow bam_subsampledepth_samtools", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_32", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_controlfreec_freec_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number and genotype annotation from whole genome and whole exome sequencing data (tools: controlfreec/freec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec_freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "bedtools_genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a", "controlfreec_assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "bam_variant_calling_sort_freebayes_bcftools": "Call variants using freebayes, then sort and index", "cnvnator_convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format."}}, "target": "controlfreec_freec", "target_idx": 0}
{"id": "mod_differential_functional_enrichment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run functional analysis on differential abundance analysis output (tools: differential_functional_enrichment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylph/profile": null, "anota2seq/anota2seqrun": null, "shinyngs/staticdifferential": null, "dotseq/dotseq": null, "differential_functional_enrichment": null}}, "target": "differential_functional_enrichment", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_1_13", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bedtools_intersect_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_INTERSECT", "tool": "bedtools/intersect", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_INTERSECT (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_survivor_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter a vcf file based on size and/or regions to ignore (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiara/tiara": "Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle", "mirtop/stats": "mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category.", "survivor/stats": "Report multiple stats over a VCF file", "survivor/filter": "Filter a vcf file based on size and/or regions to ignore", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "survivor/filter", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_23", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_21", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_artic_aligntrim_5", "category": "resource_profiling", "state": {"process": "ARTIC_ALIGNTRIM", "tool": "artic/aligntrim", "description": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_ALIGNTRIM (Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme ) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_percolator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rescore peptide-spectrum matches and estimate false discovery rates using the Percolator semi-supervised learning algorithm. (tools: percolator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"percolator": "Rescore peptide-spectrum matches and estimate false discovery rates using the Percolator semi-supervised learn", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "diamond/cluster": "calculate clusters of highly similar sequences", "humann3/regroup": "Regrouping genes to other functional categories", "spaceranger/mkgtf": "Module to build a filtered GTF needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkgtf comman"}}, "target": "percolator", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_autocycler_subsample_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downsample long-read sequencing data to the requested coverage using Autocycler. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_consensus_autocycler": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler", "autocycler_resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "sawfish_discover": "SV candidate discovery from PacBio HiFi data", "autocycler_subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "yara_index": "Builds a YARA index for a reference genome"}}, "target": "autocycler_subsample", "target_idx": 3}
{"id": "mod_coverm_contig_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Map reads to contigs and estimate coverage (tools: coverm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv_annotsv": "Annotation and Ranking of Structural Variation", "coptr_merge": "Merge reads that were mapped to multiple indices", "amulety_antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety.", "coverm_contig": "Map reads to contigs and estimate coverage", "coverm_genome": "Calculate read coverage per-genome"}}, "target": "coverm_contig", "target_idx": 3}
{"id": "mod_coptr_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexes a directory of fasta files for use with CoPTR (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr/map": "Maps the reads to the reference database", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "coptr/index": "Indexes a directory of fasta files for use with CoPTR", "yara/mapper": "Align reads to a reference genome using YARA", "arcashla/extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}}, "target": "coptr/index", "target_idx": 2}
{"id": "schema_std_lsmquant_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/lsmquant", "assay": "lsmquant pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/lsmquant (A pipeline for processing and analysis of light-sheet micros)?", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "sample,type,level,msfile": null, "sample,bam,pbi,fail,repeat_id": null, "sample_id,img_directory,parameter_file": null}}, "target": "sample_id,img_directory,parameter_file", "target_idx": 3}
{"id": "resource_biscuit_qc_0", "category": "resource_profiling", "state": {"process": "BISCUIT_QC", "tool": "biscuit/qc", "description": "Perform basic quality control on a BAM file generated with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_QC (Perform basic quality control on a BAM file generated with Biscuit) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_3", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_15", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_2_37", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_4_4", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads?", "criteria": {"sample,unite_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_fastq_fetch_clean_hostile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files (tools: fastq_fetch_clean_hostile)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hostile_fetch": "Downloads required reference genomes for Hostile", "fastq_fetch_clean_hostile": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files", "hostile_clean": "Removes host reads from short- and long-read FASTQ sequencing files", "magus_align": "Multiple Sequence Alignment using Graph Clustering", "vsearch_fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format."}}, "target": "fastq_fetch_clean_hostile", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_29", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_channel_filter_operator_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_maltextract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening (tools: maltextract)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"savana_classify": "Classify structural variants using SAVANA", "malt_build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "fastq_fastqc_umitools_trimgalore": "Read QC, UMI extraction and trimming", "maltextract": "Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "maltextract", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_43", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "field_constraint_sex_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"format: file-path": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_6_0", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for 16S rRNA / ITS microbiome amplicon profiling input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,primer_fwd,primer_rev": null, "sample,fastq_1,fastq_2": null, "sample,otu_table": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_openms_decoydatabase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a decoy peptide database from a standard FASTA database. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_decoydatabase": "Create a decoy peptide database from a standard FASTA database.", "antismash_antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "blast_makeblastdb": "Builds a BLAST database", "amplify_predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "krakentools_kreport2krona": "Takes a Kraken report file and prints out a krona-compatible TEXT file"}}, "target": "openms_decoydatabase", "target_idx": 0}
{"id": "field_constraint_expected_cells_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_extract_kraken_krakentools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS", "modules": ["kraken2/kraken2", "krakentools/extractkrakenreads"], "description": "Extract classified Kraken2 reads by taxonomic id"}, "question": {"type": "choice", "instructions": "How should FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS (kraken2/kraken2, krakentools/extractkrakenreads) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_extract_kraken_krakentools": null, "Local subworkflow FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_extract_kraken_krakentools", "target_idx": 1}
{"id": "local_subworkflow_prepontreads_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPONTREADS (porechop, nanoplot).", "criteria": {"Leave them out": null, "Local subworkflow PREPONTREADS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 1}
{"id": "mod_fastq_align_dedup_bwamem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate (tools: fastq_align_dedup_bwamem)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": null, "llamacpppython/run": null, "fasta_index_methylseq": null, "ampir": null, "fastq_align_dedup_bwamem": null}}, "target": "fastq_align_dedup_bwamem", "target_idx": 4}
{"id": "intent_ask_question_1", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "prepare_data": null, "ask_question": null}}, "target": "ask_question", "target_idx": 3}
{"id": "mod_bismark_report_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects bismark alignment reports (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_bamcmp_bwa": null, "cnvkit/reference": null, "bismark/align": null, "bismark/report": null, "bismark/methylationextractor": null}}, "target": "bismark/report", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_2_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "mod_pairtools_select_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select pairs according to given condition by options.args (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools/flip": "Flip pairs to get an upper-triangular matrix", "pairtools/select": "Select pairs according to given condition by options.args", "pairtools/merge": "Merge multiple pairs/pairsam files", "gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA", "purecn/run": "Run PureCN workflow to normalize, segment and determine purity and ploidy"}}, "target": "pairtools/select", "target_idx": 1}
{"id": "noul_named_process_output_emits_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_3_1", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Longitudinal cancer monitoring across multiple timepoints with entry step FASTQC.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_semibin_singleeasybin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: metagenomic binning with self-supervised learning (tools: semibin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biohansel": null, "concoct_cutupfasta": null, "semibin_singleeasybin": null, "ffq": null, "concoct_concoct": null}}, "target": "semibin_singleeasybin", "target_idx": 2}
{"id": "noul_publishdir_directive_usage_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_fcs_fcsadaptor_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run NCBI's FCS adaptor on assembled genomes (tools: fcs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ale": "ALE: assembly likelihood estimator.", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "fcs_fcsadaptor": "Run NCBI's FCS adaptor on assembled genomes", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "fcs_fcsadaptor", "target_idx": 3}
{"id": "samplesheet_arch_ont_demux_barcodes_7_2", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_33", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_segul_aligntrim_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim multiple sequence alignments by filtering columns based on missing data proportion or parsimony informative sites using SEGUL. (tools: segul)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"htodemux": "Demultiplex samples based on data from cell hashing.", "bwa/mem": "Performs fastq alignment to a fasta reference using BWA", "foldcomp/compress": "Efficient compression tool for protein structures", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins", "segul/aligntrim": "Trim multiple sequence alignments by filtering columns based on missing data proportion or parsimony informati"}}, "target": "segul/aligntrim", "target_idx": 4}
{"id": "pipe_all101_phaseimpute_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for genomics. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi"}}, "target": "phaseimpute", "target_idx": 0}
{"id": "mod_deepmased_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED features to predict per-contig assembly error scores. (tools: deepmased)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "deepmased_predict": "DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED", "seqkit_concat": "Concatenating multiple uncompressed sequence files together", "cmseq_polymut": "Calculates polymorphic site rates over protein coding genes"}}, "target": "deepmased_predict", "target_idx": 2}
{"id": "pipe_core10_sarek_2_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? GATK best-practices germline and somatic variant calling on human WGS/WES datasets.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"mag": null, "eager": null, "ampliseq": null, "viralrecon": null, "taxprofiler": null, "atacseq": null, "sarek": null, "scrnaseq": null, "rnaseq": null, "chipseq": null}}, "target": "sarek", "target_idx": 6}
{"id": "intent_ask_question_16", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "ask_question", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_5_3", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cutandrun, determine the input samplesheet column structure for: CUT&RUN / CUT&TAG chromatin profiling with IgG control.", "criteria": {"sample,bam": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "mod_paraphase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: HiFi-based caller for highly homologous genes (tools: paraphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "bedtools/unionbedg": "Combines multiple BedGraph files into a single file", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "paraphase": "HiFi-based caller for highly homologous genes", "picard/collectwgsmetrics": "Collect metrics about coverage and performance of whole genome sequencing (WGS) experiments."}}, "target": "paraphase", "target_idx": 3}
{"id": "samplesheet_arch_germline_lane_split_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Multi-lane Illumina sequencing run of clinical samples)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_10", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_0", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wgs_pe_2_4", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_autocycler_combine_5", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMBINE", "tool": "autocycler/combine", "description": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMBINE (Merge resolved cluster assemblies into final consensus outputs with Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_custom_dumpsoftwareversions_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Custom module used to dump software versions within the nf-core pipeline template (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_dumpsoftwareversions": "Custom module used to dump software versions within the nf-core pipeline template", "fasta_build_add_kraken2_bracken": "KRAKEN2 and BRACKEN build custom database subworkflow", "cooler_dump": "Dump a cooler’s data to a text stream.", "haplogrep3_classify": "classification into haplogroups", "picard_meanqualitybycycle": "Collect metrics about the mean quality by cycle of a paired-end library."}}, "target": "custom_dumpsoftwareversions", "target_idx": 0}
{"id": "mod_tetranscripts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs TEtranscripts which summarises transposable element content of a bam file. (tools: tetranscripts)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tetranscripts": "Runs TEtranscripts which summarises transposable element content of a bam file.", "orftable_fasta_gtf_buildorfcatalogue": "Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller\nORF prediction tables. Chains:\n\n  1. `", "anndata/barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "motus/profile": "Taxonomic meta-omics profiling using universal marker genes"}}, "target": "tetranscripts", "target_idx": 0}
{"id": "pipe_all101_hlatyping_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for dna analysis? Specific context: Precision HLA typing from next-generation sequencing data. Topics: dna, hla, hla-typing, immunology, optitype, personalized-medicine. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "callingcards": "A pipeline for processing calling cards data", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders"}}, "target": "hlatyping", "target_idx": 4}
{"id": "noul_channel_filter_operator_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_rundbcan_easysubstrate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZymes) from genomic data using the dbCAN annotation tool. (tools: dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_create_umi_consensus_fgbio": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads\nconvert them to unmapped B", "bcftools_pluginvcf2table": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output", "aria2": "CLI Download utility", "rundbcan_easysubstrate": "Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzyme", "rundbcan_easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ"}}, "target": "rundbcan_easysubstrate", "target_idx": 3}
{"id": "mod_metaspace_converter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Export METASPACE datasets to AnnData and SpatialData objects (tools: metaspace_converter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"datavzrd": "Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables.", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects", "samtools_cat": "Concatenate BAM or CRAM file", "anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file"}}, "target": "metaspace_converter", "target_idx": 1}
{"id": "pipe_all101_detaxizer_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for de-identification analysis? Specific context: A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.. Topics: de-identification, decontamination, edna, fastq, filter, long-reads. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]"}}, "target": "detaxizer", "target_idx": 1}
{"id": "noul_dynamic_resource_allocation_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_checkm_qa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. (tools: checkm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm/qa": null, "assemblyscan": null, "gunc/mergecheckm": null, "checkm/lineagewf": null, "checkv/endtoend": null}}, "target": "checkm/qa", "target_idx": 0}
{"id": "field_constraint_sex_1_5", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "mod_mafft_guidetree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Guide tree rendering using MAFFT (tools: mafft)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "macsyfinder_search": "Search for macromolecular systems in protein datasets using MacSyFinder", "proteinortho": "Proteinortho is a tool to detect orthologous genes within different species.", "mafft_guidetree": "Guide tree rendering using MAFFT", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "mafft_guidetree", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_27", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "schema_std_rnaseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay": "rnaseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnaseq (RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or)?", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "id,fasta,query": null}}, "target": "sample,fastq_1,fastq_2,strandedness,seq_platform", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_8_3", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "template": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_0_4", "category": "samplesheet_schema", "state": {"technology": "Microbial Assembly", "workflow_entry": "FASTQC", "library_inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_annotate_snpeff_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_SNPEFF", "modules": ["snpeff", "snpeff/snpeff", "htslib/bgziptabix"], "description": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_SNPEFF (snpeff, snpeff/snpeff, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_annotate_snpeff": null, "Keep the modules in the main workflow": null, "Local subworkflow VCF_ANNOTATE_SNPEFF": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_annotate_snpeff", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pre-aligned BAM variant calling pipeline. Input files: Aligned BAM files.", "question": {"type": "choice", "instructions": "Which columns are standard for Pre-aligned BAM variant calling pipeline input samplesheet?", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "field_constraint_phenotype_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_10", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_gunc_downloaddb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes (tools: gunc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "fasta_bgzip_index_dict_samtools": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA f", "blast_updateblastdb": "Downloads a BLAST database from NCBI", "gunc_downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "gatk4_revertsam": "Reverts SAM or BAM files to a previous state."}}, "target": "gunc_downloaddb", "target_idx": 3}
{"id": "resource_bamtofastq10x_2", "category": "resource_profiling", "state": {"process": "BAMTOFASTQ10X", "tool": "bamtofastq10x", "description": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Long Ranger back to FASTQ files that can be used as inputs to re-run analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOFASTQ10X (Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_pangenome_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for pangenome analysis? Specific context: Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609.. Topics: pangenome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "callingcards": "A pipeline for processing calling cards data", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i"}}, "target": "pangenome", "target_idx": 5}
{"id": "mod_custom_clustermetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analysis (tools: scikit-learn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/cluster": "Cluster replicons in compressed assemblies with Autocycler.", "pridepy/fetchsdrf": "Fetch an SDRF file from the PRIDE Archive for a given project accession.", "allelecounter": "Generates a count of coverage of alleles", "custom/clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy"}}, "target": "custom/clustermetrics", "target_idx": 4}
{"id": "core_tool_fastqc_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Quality control metric evaluation including per-base sequence quality scores, GC content distributions, and k-mer overrepresentation for raw FASTQ data.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"multiqc": null, "nanoplot": null, "falco": null, "fastqc": null, "qualimap": null}}, "target": "fastqc", "target_idx": 3}
{"id": "resource_blat_5", "category": "resource_profiling", "state": {"process": "BLAT", "tool": "blat", "description": "Queries a sequence subject"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAT (Queries a sequence subject) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_abricate_run_5", "category": "resource_profiling", "state": {"process": "ABRICATE_RUN", "tool": "abricate/run", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_RUN (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_bam_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "resource_busco_download_5", "category": "resource_profiling", "state": {"process": "BUSCO_DOWNLOAD", "tool": "busco/download", "description": "Download database for BUSCO"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_DOWNLOAD (Download database for BUSCO) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gappa_examineassign_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: assigns taxonomy to query sequences in phylogenetic placement output (tools: gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cafe": "Analysis of gene family evolution", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O", "gappa/examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "pairtools/sort": "Sort a .pairs/.pairsam file"}}, "target": "gappa/examineassign", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_3", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_blast_tblastn_1", "category": "resource_profiling", "state": {"process": "BLAST_TBLASTN", "tool": "blast/tblastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_TBLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_3_0", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq with entry step FASTQC.", "criteria": {"plate,sample,bam": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_48", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "pipe_all101_rangeland_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for earth-observation analysis? Specific context: Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple steps to arrive at a set of trend files related to land-cover changes.. Topics: earth-observation, landsat, satellite-imagery, spectral-unmixing, trend-analysis, trends. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo"}}, "target": "rangeland", "target_idx": 3}
{"id": "mod_samtools_view_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: filter/convert SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmsearch": null, "bcftools/annotate": null, "bcftools/view": null, "bcftools/call": null, "samtools/view": null}}, "target": "samtools/view", "target_idx": 4}
{"id": "noul_named_process_output_emits_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_hisat2_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align RNA-Seq reads to a reference with HISAT2 (tools: hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "hisat2_align": "Align RNA-Seq reads to a reference with HISAT2", "clair3": "Clair3 is a germline small variant caller for long-reads", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "truvari_consistency": "Over multiple vcfs, calculate their intersection/consistency."}}, "target": "hisat2_align", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_2", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_33", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_pydamage_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Damage parameter estimation for ancient DNA (tools: pydamage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gfastats": "A single fast and exhaustive tool for summary statistics and simultaneous *fa*\n(fasta, fastq, gfa [.gz]) genom", "dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "seqtk_rename": "Rename sequence names in FASTQ or FASTA files.", "pydamage_filter": "Damage parameter estimation for ancient DNA", "endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen"}}, "target": "pydamage_filter", "target_idx": 3}
{"id": "local_subworkflow_checkirma_0_1", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should CHECKIRMA (custom/checkirma) be built?", "criteria": {"Leave them out": null, "Local subworkflow CHECKIRMA": null, "Use nf-core subworkflow checkirma": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 1}
{"id": "pipe_all101_imcyto_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for cytometry analysis? Specific context: Image Mass Cytometry analysis pipeline. Topics: cytometry, image-analysis, image-processing, image-segmentation. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "metapep": "From metagenomes to epitopes and beyond", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]"}}, "target": "imcyto", "target_idx": 4}
{"id": "pipe_all101_molkart_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). Topics: fish, image-processing, imaging, molecularcartography, segmentation, single-cell. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-"}}, "target": "molkart", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_48", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_cnvkit_segment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Infer discrete copy number segments from the given coverage table. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"medaka": null, "cnvkit_batch": null, "cnvkit_segment": null, "sourmash_index": null, "cnvkit_coverage": null}}, "target": "cnvkit_segment", "target_idx": 2}
{"id": "mod_sentieon_dedup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs the sentieon tool LocusCollector followed by Dedup. LocusCollector collects read information that is used by Dedup which in turn marks or removes duplicate reads. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqsero2": "Salmonella serotype prediction from reads and assemblies", "bwameme_mem": "Performs fastq alignment to a fasta reference using BWA-MEME", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3", "viennarna_rnafold": "Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary str", "sentieon_dedup": "Runs the sentieon tool LocusCollector followed by Dedup. LocusCollector collects read information that is used"}}, "target": "sentieon_dedup", "target_idx": 4}
{"id": "field_constraint_fastq_2_0_9", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_33", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_fgbio_copyumifromreadname_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copies the UMI at the end of a bam files read name to the RX tag. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_gtf_bam_rpbp": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). R", "fgbio/zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "fgbio/callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "fgbio/copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "tabix/bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde"}}, "target": "fgbio/copyumifromreadname", "target_idx": 3}
{"id": "resource_biomformat_convert_1", "category": "resource_profiling", "state": {"process": "BIOMFORMAT_CONVERT", "tool": "biomformat/convert", "description": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HDF5) formats are supported"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOMFORMAT_CONVERT (Convert biom table to different format.\nConversion between text tab-delimited, B) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_2_4", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery", "pipeline": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fusion_bed": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_deeptools_alignmentsieve_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool filters alignments in a BAM/CRAM file according the the specified parameters. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "last/lastal": "Aligns query sequences to target sequences indexed with lastdb", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "deeptools/alignmentsieve": "This tool filters alignments in a BAM/CRAM file according the the specified parameters."}}, "target": "deeptools/alignmentsieve", "target_idx": 4}
{"id": "mod_fgbio_fastqtobam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI barcode into the RX field of the reads (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio/fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI", "picard/fastqtosam": "Converts a FASTQ file to an unaligned BAM or SAM file.", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "genomad/download": "Download geNomad databases and related files", "bamutil/clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo"}}, "target": "fgbio/fastqtobam", "target_idx": 0}
{"id": "mod_fgbio_sortbam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts a SAM or BAM file. Several sort orders are available, including coordinate, queryname, random, and randomquery. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/splitintervals": "Split intervals into sub-interval files.", "fgbio/sortbam": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate, queryname, random, and rando", "crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "plink2/filter": "Filters plink bfiles or pfiles with filters such as maf or var", "bedtools/sort": "Sorts a feature file by chromosome and other criteria."}}, "target": "fgbio/sortbam", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_7", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_parsesdrf_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration using the `parse_sdrf\nconvert-<format>` subcommands of the sdrf-pipelines package. The chosen\n`format` selects the subcommand; the module owns the output filenames and\nemits one tuple per supported format (mhcquant, openms, maxquant, msstats,\nnormalyzerde, diann). (tools: sdrf-pipelines)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr_extract": "Computes the coverage map along the reference genome", "parsesdrf_convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration ", "pridepy_fetchsdrf": "Fetch an SDRF file from the PRIDE Archive for a given project accession.", "samtools_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "samplesheetparser_diff": "Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff cove"}}, "target": "parsesdrf_convert", "target_idx": 1}
{"id": "resource_bismark_align_0", "category": "resource_profiling", "state": {"process": "BISMARK_ALIGN", "tool": "bismark/align", "description": "Performs alignment of BS-Seq reads using bismark"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_ALIGN (Performs alignment of BS-Seq reads using bismark) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_fastq_2_1_3", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_26", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Metagenomic MAG assembly with comparative groups. Input files: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "noul_dynamic_resource_allocation_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_biobambam_bamsormadup_0", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMSORMADUP", "tool": "biobambam/bamsormadup", "description": "Parallel sorting and duplicate marking"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMSORMADUP (Parallel sorting and duplicate marking) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bedtools_maskfasta_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MASKFASTA", "tool": "bedtools/maskfasta", "description": "masks sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MASKFASTA (masks sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "local_subworkflow_prepilluminareads_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should this step (trimmomatic) be packaged: Single-step adapter trimming for Illumina reads?", "criteria": {"Leave them out": null, "Use nf-core subworkflow prepilluminareads": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPILLUMINAREADS": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 3}
{"id": "samplesheet_arch_ont_demux_barcodes_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Multiplexed Oxford Nanopore run with barcode demultiplexing)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "pipe_all101_hlatyping_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Precision HLA typing from next-generation sequencing data. Topics: dna, hla, hla-typing, immunology, optitype, personalized-medicine. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createpanelrefs": null, "imcyto": null, "hlatyping": null, "rnasplice": null, "diaproteomics": null, "longraredisease": null, "multiplesequencealign": null, "mag": null, "demultiplex": null, "stableexpression": null}}, "target": "hlatyping", "target_idx": 2}
{"id": "mod_samplesheetparser_validate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validate an Illumina SampleSheet.csv (V1 or V2) for index, adapter, and\nstructural issues. Format is auto-detected. Exits 0 if valid, 1 if errors\nare found — causing the pipeline to fail early with a clear message rather\nthan discovering demultiplexing problems downstream. (tools: samplesheet-parser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samplesheetparser_validate": "Validate an Illumina SampleSheet.csv (V1 or V2) for index, adapter, and\nstructural issues. Format is auto-dete", "foldmason_createdb": "Creates a database for Foldmason.", "artic_aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga", "cellranger_mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command."}}, "target": "samplesheetparser_validate", "target_idx": 0}
{"id": "mod_biscuit_epiread_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format. (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_biscuitblaster": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit", "fgumi_zipper": "Zip an unmapped UMI BAM together with its aligned BAM using fgumi", "biscuit_epiread": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compl", "biscuit_index": "Indexes a reference genome for use with Biscuit"}}, "target": "biscuit_epiread", "target_idx": 3}
{"id": "resource_ascat_0", "category": "resource_profiling", "state": {"process": "ASCAT", "tool": "ascat", "description": "copy number profiles of tumour cells."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASCAT (copy number profiles of tumour cells.) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_pairtools_restrict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assign restriction fragments to pairs (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools_restrict": "Assign restriction fragments to pairs", "mosdepth": "Calculates genome-wide sequencing coverage.", "methbat_profile": "Runs methbat profile command to create methylation profiles for regions of interest from CpG metrics.", "pairtools_select": "Select pairs according to given condition by options.args", "pairtools_sort": "Sort a .pairs/.pairsam file"}}, "target": "pairtools_restrict", "target_idx": 0}
{"id": "local_subworkflow_prepilluminareads_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPILLUMINAREADS (trimmomatic).", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow PREPILLUMINAREADS": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 2}
{"id": "mod_bed_scatter_bedtools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Scatters inputted BED files by the amount specified.\nThe configuration in nextflow.config should be added to your modules.config for the subworkflow to work. (tools: bed_scatter_bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "khmer/normalizebymedian": "Module that calls normalize-by-median.py from khmer. The module can take a mix of paired end (interleaved) and", "ucsc/bigwigaverageoverbed": "compute average score of bigwig over bed file", "bed_scatter_bedtools": "Scatters inputted BED files by the amount specified.\nThe configuration in nextflow.config should be added to y", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}}, "target": "bed_scatter_bedtools", "target_idx": 3}
{"id": "mod_eido_validate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validate samplesheet or PEP config against a schema (tools: validate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "eido/validate": "Validate samplesheet or PEP config against a schema", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "fargene": "tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full", "fq/lint": "fq lint is a FASTQ file pair validator."}}, "target": "eido/validate", "target_idx": 1}
{"id": "mod_bcftools_pluginsplit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split VCF by sample, creating single- or multi-sample VCFs. (tools: pluginsplit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio_splitbed": "Split features in gzipped BED format", "bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "propr_propd": "Perform differential proportionality analysis", "scanpy_hashsolo": "Probabilistic demultiplexing of cell hashing data", "bcftools_pluginsplit": "Split VCF by sample, creating single- or multi-sample VCFs."}}, "target": "bcftools_pluginsplit", "target_idx": 4}
{"id": "mod_seqtk_rename_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rename sequence names in FASTQ or FASTA files. (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sambamba/flagstat": null, "hmtnote/annotate": null, "seqtk/rename": null, "seqtk/mergepe": null, "xeniumranger/rename": null}}, "target": "seqtk/rename", "target_idx": 2}
{"id": "resource_biscuit_vcf2bed_0", "category": "resource_profiling", "state": {"process": "BISCUIT_VCF2BED", "tool": "biscuit/vcf2bed", "description": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_VCF2BED (Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compl) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_fastq_index_filter_deacon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decontaminate FastQ files by filtering reads that match a reference genome using Deacon (tools: fastq_index_filter_deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "fastq_index_filter_deacon": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon", "famsa_align": "Aligns sequences using FAMSA", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}}, "target": "fastq_index_filter_deacon", "target_idx": 1}
{"id": "mod_shapeit5_ligate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chunks of phased common variants. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariatereml": "Run bivariate REML analysis with a single dense GRM", "gatk4_haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "shapeit5_ligate": "Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chu", "gatk4_mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "bwa_samse": "Convert bwa SA coordinate file to SAM format"}}, "target": "shapeit5_ligate", "target_idx": 2}
{"id": "mod_icountmini_sigxls_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs iCount sigxls on a BED file of crosslinks (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylphtax/merge": "Merge multiple taxonomic profiles from sylphtaxt/taxprof into a tsv table", "pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "peka": "Runs PEKA CLIP peak k-mer analysis", "seqkit/split2": "Split single or paired-end fastq.gz files", "icountmini/sigxls": "Runs iCount sigxls on a BED file of crosslinks"}}, "target": "icountmini/sigxls", "target_idx": 4}
{"id": "mod_isoseq_refine_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove polyA tail and artificial concatemers (tools: isoseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "gstama_collapse": "Collapse redundant transcript models in Iso-Seq data.", "deeparg_downloaddata": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "isoseq3_tag": "Extract UMI and cell barcodes", "isoseq_refine": "Remove polyA tail and artificial concatemers"}}, "target": "isoseq_refine", "target_idx": 4}
{"id": "mod_picard_addorreplacereadgroups_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assigns all the reads in a file to a single new read-group (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_annotate": "Add or remove annotations.", "hmmcopy_readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows", "metamaps_mapdirectly": "Maps long reads to a metamaps database", "gatk4_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "picard_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group"}}, "target": "picard_addorreplacereadgroups", "target_idx": 4}
{"id": "samplesheet_arch_epigenomics_hic_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hic", "assay_type": "Hi-C chromosome conformation capture mapping", "data_format": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns are standard for Hi-C chromosome conformation capture mapping input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,matrix,contacts": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_48", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_34", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_createpanelrefs_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/createpanelrefs. Description: Generate Panel of Normals, models or other similar references from lots of samples.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/createpanelrefs.", "criteria": {"id,path": null, "sample,bam,bai,cram,crai": null, "sample,bundle,image": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null}}, "target": "sample,bam,bai,cram,crai", "target_idx": 1}
{"id": "mod_fasta_binning_concoct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs the CONCOCT workflow of contig binning (tools: fasta_binning_concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ssuissero": "Serotype prediction of Streptococcus suis assemblies", "mafft/guidetree": "Guide tree rendering using MAFFT", "clame": "binning of metagenomic sequences", "fasta_binning_concoct": "Runs the CONCOCT workflow of contig binning", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "fasta_binning_concoct", "target_idx": 3}
{"id": "mod_quartonotebook_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render a Quarto notebook, including parametrization. (tools: quartonotebook)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spaddintrons": "Add intron features to gtf/gff file without intron features.", "trnascanse": "Detection of tRNA sequences using covariance models", "pypolca/run": "Short read polisher for long read assemblies", "jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill.", "quartonotebook": "Render a Quarto notebook, including parametrization."}}, "target": "quartonotebook", "target_idx": 4}
{"id": "mod_pyclonevi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele frequencies and copy number data of single or multiple samples. (tools: pyclonevi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chewbbaca/createschema": "Create a schema to determine the allelic profiles of a genome", "manta/convertinversion": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. This script reformat", "glimpse2/concordance": "Program to compute the genotyping error rate at the sample or marker level.", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq", "cnaqc": "Quality control of copy number data from bulk WGS assays"}}, "target": "pyclonevi", "target_idx": 3}
{"id": "mod_chromap_chromap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap. (tools: chromap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rtgtools_bndeval": null, "busco_phylogenomics": null, "bwa_mem": null, "hhsuite_hhsearch": null, "chromap_chromap": null}}, "target": "chromap_chromap", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_2_25", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "local_subworkflow_nextclade_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should this step (nextclade/run) be packaged: Viral clade typing and QC?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow NEXTCLADE": null, "Use nf-core subworkflow nextclade": null, "Leave them out": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "local_subworkflow_irma_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for IRMA (irma).", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow IRMA": null, "Use nf-core subworkflow irma": null, "Leave them out": null}}, "target": "Local subworkflow IRMA", "target_idx": 1}
{"id": "schema_std_metaboigniter_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metaboigniter", "description": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/metaboigniter?", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,type,level,msfile": null, "sample,group,path,ref,method": null}}, "target": "sample,type,level,msfile", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_4_1", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Nanopore sequencing run with sample to barcode assignment and flowcell type?", "criteria": {"sample,bam": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "pipe_all101_readsimulator_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data.. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]"}}, "target": "readsimulator", "target_idx": 0}
{"id": "pipe_all101_variantbenchmarking_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for benchmark analysis? Specific context: Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research. Topics: benchmark, small-variants, structural-variants, variant-calling. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a"}}, "target": "variantbenchmarking", "target_idx": 2}
{"id": "mod_nail_search_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: nail search is a fast and scalable tool for searching protein sequences against protein databases (tools: nail)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "nail_search": "nail search is a fast and scalable tool for searching protein sequences against protein databases", "samplesheetparser_validate": "Validate an Illumina SampleSheet.csv (V1 or V2) for index, adapter, and\nstructural issues. Format is auto-dete", "dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins"}}, "target": "nail_search", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_6", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_mmseqs_databases_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download an mmseqs-formatted database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangeratac/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkref", "bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "mmseqs/databases": "Download an mmseqs-formatted database", "plink/indep": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other.", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo"}}, "target": "mmseqs/databases", "target_idx": 2}
{"id": "mod_suppa_psiperevent_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate PSI values for alternative splicing events using SUPPA (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "opt/track": "track aligns query probe sequences to any target transcriptome", "rmats/prep": "MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data.", "suppa/generateevents": "Generates alternative splicing events from a GTF file using SUPPA.", "suppa/psiperevent": "Calculate PSI values for alternative splicing events using SUPPA"}}, "target": "suppa/psiperevent", "target_idx": 4}
{"id": "mod_deeparg_downloaddata_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes (tools: deeparg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_updateblastdb": "Downloads a BLAST database from NCBI", "aria2": "CLI Download utility", "deeparg_downloaddata": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "ectyper": "In silico prediction of E. coli serotype", "lsa_cosine": "Calculates the cosine similarity matrix between samples based on a gene expression matrix."}}, "target": "deeparg_downloaddata", "target_idx": 2}
{"id": "intent_prepare_data_4", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "prepare_data", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_2_0", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "intent_ask_question_2", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "ask_question", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diaproteomics", "assay_type": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "data_format": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,raw_file,condition": null, "sample,mzml": null, "sample,fasta": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "mod_narfmap_hashtable_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create DRAGEN hashtable for reference genome (tools: narfmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"narfmap_hashtable": "Create DRAGEN hashtable for reference genome", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "tmb_pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "bowtie_build": "Create bowtie index for reference genome", "bbmap_bbnorm": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result i"}}, "target": "narfmap_hashtable", "target_idx": 0}
{"id": "field_constraint_expected_cells_1_12", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"pattern: ^\\S+\\.csv$": null, "format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "resource_bcftools_consensus_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONSENSUS", "tool": "bcftools/consensus", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONSENSUS (Compresses VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_createpanelrefs_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Generate Panel of Normals, models or other similar references from lots of samples. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin"}}, "target": "createpanelrefs", "target_idx": 5}
{"id": "samplesheet_arch_spatial_xenium_0_0", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "field_constraint_sex_3_2", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "resource_blobtk_depth_4", "category": "resource_profiling", "state": {"process": "BLOBTK_DEPTH", "tool": "blobtk/depth", "description": "Creates a bed file containing the depth of data at intervals of an aligned bam."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_DEPTH (Creates a bed file containing the depth of data at intervals of an aligned bam.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_34", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_ultraplex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ultraplex is an all-in-one software package for processing and demultiplexing fastq files. (tools: ultraplex)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bases2fastq": "Demultiplex Element Biosciences bases files", "bcftools_isec": "Apply set operations to VCF files", "genmod_score": "Score the variants of a vcf based on their annotation", "ultraplex": "Ultraplex is an all-in-one software package for processing and demultiplexing fastq files.", "bclconvert": "Demultiplex Illumina BCL files"}}, "target": "ultraplex", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Tumor-only somatic variant calling without matched normal. Input files: Paired-end FASTQ reads from tumor biopsy without matched normal.", "question": {"type": "choice", "instructions": "Which columns are standard for Tumor-only somatic variant calling without matched normal input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_marsseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/marsseq", "assay": "marsseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/marsseq (MARS-seq v2 pre-processing pipeline with velocity)?", "criteria": {"fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,fastq_1,fastq_2,strandedness,type": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample_id,img_directory,parameter_file": null}}, "target": "fastq_1,fastq_2,batch,amp_batches,seq_batches", "target_idx": 0}
{"id": "field_constraint_strandedness_1_5", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "mod_bandage_image_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render an assembly graph in GFA 1.0 format to PNG and SVG image formats (tools: bandage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clair3": "Clair3 is a germline small variant caller for long-reads", "odgi_draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "gfatools_stat": "Summary statistics for GFA files", "last_mafconvert": "Converts MAF alignments in another format.", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}}, "target": "bandage_image", "target_idx": 4}
{"id": "mod_windowmasker_ustat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program to take a counts file and creates a file of genomic co-ordinates to be masked. (tools: windowmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"windowmasker_ustat": "A program to take a counts file and creates a file of genomic co-ordinates to be masked.", "fastq_preprocess_seqkit": "Subworkflow that preprocesses FASTQ files", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "genometester4_glistmaker": "Create and count k-mer lists from nucelotide sequences.", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "windowmasker_ustat", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_35", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_scrna_10x_v3_0_4", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "pipe_all101_seqsubmit_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core pipeline for data submission to ENA. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "callingcards": "A pipeline for processing calling cards data", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "seqsubmit": "nf-core pipeline for data submission to ENA", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]"}}, "target": "seqsubmit", "target_idx": 7}
{"id": "mod_lofreq_alnqual_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to for insert base and indel alignment qualities (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_consensus": "Compresses VCF files", "lofreq_alnqual": "Lofreq subcommand to for insert base and indel alignment qualities", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "yara_index": "Builds a YARA index for a reference genome", "megahit": "An ultra-fast metagenomic assembler for large and complex metagenomics"}}, "target": "lofreq_alnqual", "target_idx": 1}
{"id": "resource_bcftools_csq_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CSQ", "tool": "bcftools/csq", "description": "bcftools Haplotype-aware consequence caller"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CSQ (bcftools Haplotype-aware consequence caller) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_dynamic_resource_allocation_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_amulety_translate_4", "category": "resource_profiling", "state": {"process": "AMULETY_TRANSLATE", "tool": "amulety/translate", "description": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_TRANSLATE (A module to translate BCR and TCR nucleotide sequences into amino acid sequences) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_funcprofiler_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/funcprofiler", "description": "Read-based functional profiling of microbiome sequencing data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/funcprofiler?", "criteria": {"sample,type,level,msfile": null, "id,path": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,bam,bai,cram,crai": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_10", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_retry_errorstrategy_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_executor_support_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Genome analysis from reference-compressed CRAM files)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Genome analysis from reference-compressed CRAM files with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "field_constraint_phenotype_1_7", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "type: string free-text": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "mod_seqwish_induce_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Induce a variation graph in GFA format from alignments in PAF format (tools: seqwish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bandage/image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats", "seqwish/induce": "Induce a variation graph in GFA format from alignments in PAF format", "numorph/3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "paftools/sam2paf": "A program to convert bam into paf.", "hamronization/fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification"}}, "target": "seqwish/induce", "target_idx": 1}
{"id": "mod_starfusion_detect_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast and Accurate Fusion Transcript Detection from RNA-Seq (tools: star-fusion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_starfusion": "This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. Thi", "genomad_download": "Download geNomad databases and related files", "sniffles": "structural-variant calling with sniffles", "arriba_arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "starfusion_detect": "Fast and Accurate Fusion Transcript Detection from RNA-Seq"}}, "target": "starfusion_detect", "target_idx": 4}
{"id": "samplesheet_arch_ancient_dna_eager_4_0", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status", "pipeline": "nf-core/eager"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bismark_genomepreparation_3", "category": "resource_profiling", "state": {"process": "BISMARK_GENOMEPREPARATION", "tool": "bismark/genomepreparation", "description": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_GENOMEPREPARATION (Converts a specified reference genome into two different bisulfite\nconverted ver) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_phenotype_0_6", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "format: file-path": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "mod_gridss_preprocess_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and coverage metrics) from an input BAM file prior to assembly and variant calling. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/reheader": "Replace the header in the bam file with the header generated by the command.\nThis command is much faster than ", "amulety/antiberty": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety.", "gridss/preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and ", "gridss/call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment", "gridss/extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for"}}, "target": "gridss/preprocess", "target_idx": 2}
{"id": "mod_yte_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A YAML template engine with Python expressions (tools: yte)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill.", "fcs/fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi", "quartonotebook": "Render a Quarto notebook, including parametrization.", "yte": "A YAML template engine with Python expressions", "pbmm2/align": "Alignment with PacBio's minimap2 frontend"}}, "target": "yte", "target_idx": 3}
{"id": "resource_bcftools_pluginsetgt_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSETGT", "tool": "bcftools/pluginsetgt", "description": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSETGT (Sets genotypes according to the specified criteria and filtering expressions. Fo) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "local_subworkflow_preparereports_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should PREPAREREPORTS (custom/preparereports, multiqc) be built?", "criteria": {"Leave them out": null, "Local subworkflow PREPAREREPORTS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow preparereports": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_1_3", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "pipe_all101_airrflow_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for airr. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "metapep": "From metagenomes to epitopes and beyond", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo"}}, "target": "airrflow", "target_idx": 9}
{"id": "mod_htseq_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: count how many reads map to each feature (tools: htseq/count)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"maltextract": "Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening", "htseq_count": "count how many reads map to each feature", "fusioncatcher_build": "Build references for fusioncatcher", "cellrangerarc_count": "Module to use Cell Ranger's ARC pipelines analyze sequencing data produced from Chromium Single Cell ARC. Uses", "cellrangeratac_count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC."}}, "target": "htseq_count", "target_idx": 1}
{"id": "schema_std_radseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/radseq", "description": "Variant-calling pipeline for Restriction site-associated DNA sequencing (RADseq).", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/radseq?", "criteria": {"sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1,fastq_2,umi_barcodes": null}}, "target": "sample,fastq_1,fastq_2,umi_barcodes", "target_idx": 3}
{"id": "mod_plink2_pca_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform PCA analysis using PLINK (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium", "parabricks/fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "mapdamage2": "Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads ge", "plink2/pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "plink2/pca": "Perform PCA analysis using PLINK"}}, "target": "plink2/pca", "target_idx": 4}
{"id": "mod_assemblyscan_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembly summary statistics in JSON format (tools: assemblyscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_applyvarcal": null, "abra2": null, "abricate_run": null, "purgedups_calcuts": null, "assemblyscan": null}}, "target": "assemblyscan", "target_idx": 4}
{"id": "field_constraint_fastq_2_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Tumor-only somatic variant calling without matched normal)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Tumor-only somatic variant calling without matched normal with entry step FASTQC.", "criteria": {"patient,normal,tumor": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_taxonkit_lineage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert taxonids to taxon lineages (tools: taxonkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plastid_metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "taxonkit_lineage": "Convert taxonids to taxon lineages", "cramino": "Quality assessment of long-read bam files using cramino.", "ganon_table": "Generate a multi-sample report file from the output of ganon report runs"}}, "target": "taxonkit_lineage", "target_idx": 2}
{"id": "intent_debug_error_20", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "debug_error", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_24", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "field_constraint_sample_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "assay_type": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "data_format": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns are standard for Hybrid bacterial assembly combining short Illumina and long Nanopore reads input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_fcsgx_fetchdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fetches the NCBI FCS-GX database using a provided manifest URL (tools: fcsgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tabix/bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde", "hamronization/summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "fcsgx/cleangenome": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome asse", "fcsgx/fetchdb": "Fetches the NCBI FCS-GX database using a provided manifest URL", "antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt"}}, "target": "fcsgx/fetchdb", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "assay_type": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "data_format": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,kraken_db": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_abacas_2", "category": "resource_profiling", "state": {"process": "ABACAS", "tool": "abacas", "description": "Contiguate draft genome assembly"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABACAS (Contiguate draft genome assembly) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wgs_pe_2_5", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "assay_type": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "data_format": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,cpg,methylation": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_seqkit_concat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenating multiple uncompressed sequence files together (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_concat": null, "agrvate": null, "maxquant_lfq": null, "bcftools_concat": null, "vembrane_table": null}}, "target": "seqkit_concat", "target_idx": 0}
{"id": "mod_graphtyper_vcfconcatenate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tools for population-scale genotyping using pangenome graphs. (tools: graphtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk_concat": null, "survivor_merge": null, "cat_cat": null, "graphtyper_vcfconcatenate": null, "tximeta_tximport": null}}, "target": "graphtyper_vcfconcatenate", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_34", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "field_constraint_status_0_10", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_1_3", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_gatk4_splitintervals_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split intervals into sub-interval files. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_convert": null, "gatk4_splitintervals": null, "bedgovcf": null, "minimac4_compressref": null, "catpack_reads": null}}, "target": "gatk4_splitintervals", "target_idx": 1}
{"id": "resource_abyss_abysspe_2", "category": "resource_profiling", "state": {"process": "ABYSS_ABYSSPE", "tool": "abyss/abysspe", "description": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABYSS_ABYSSPE (ABySS is a de novo sequence assembler intended for short paired-end reads and ge) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_1_2", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cram": null, "sample,bam,bai": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "field_constraint_sex_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"pattern: ^\\S+\\.gz$": null, "format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_1_3", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,bam": null, "sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_phenotype_0_0", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"enum: [normal, tumor]": null, "format: file-path": null, "type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_1_3", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,vcf": null, "sample,image": null, "sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking. Input files: Circulating tumor DNA FASTQs across patient clinical draw intervals.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_1_6", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "noul_single_hyphen_cli_params_error_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_custom_getchromsizes_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a FASTA file of chromosome sizes and a fasta index file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngsbits/bedannotategc": "Annotates GC content fraction to regions in a BED file.", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "bcftools/pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "custom/getchromsizes": "Generates a FASTA file of chromosome sizes and a fasta index file"}}, "target": "custom/getchromsizes", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wgs_pe_0_4", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_deeptools_plotcorrelation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualises sample correlations using a compressed matrix generated by mutlibamsummary or multibigwigsummary as input. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_plotcorrelation": "Visualises sample correlations using a compressed matrix generated by mutlibamsummary or multibigwigsummary as", "custom_matrixfilter": "filter a matrix based on a minimum value and numbers of samples that must pass.", "deeptools_computematrix": "calculates scores per genome regions for other deeptools plotting utilities", "windowmasker_convert": "Masks out highly repetitive DNA sequences with low complexity in a genome", "samtools_reheader": "Replace the header in the bam file with the header generated by the command.\nThis command is much faster than "}}, "target": "deeptools_plotcorrelation", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_45", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_bwafastalign_mem_1", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_MEM", "tool": "bwafastalign/mem", "description": "Performs fastq alignment to a fasta reference using BWA-FastAlign."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_MEM (Performs fastq alignment to a fasta reference using BWA-FastAlign.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_chromap_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_CHROMAP", "modules": ["chromap/chromap", "picard/addorreplacereadgroups", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_CHROMAP (chromap/chromap, picard/addorreplacereadgroups, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_chromap": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_CHROMAP": null}}, "target": "Use nf-core subworkflow fastq_align_chromap", "target_idx": 1}
{"id": "mod_sentieon_rsempreparereference_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare a reference genome for RSEM (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cdhit_cdhit": null, "sentieon_rsempreparereference": null, "custom_rsemmergecounts": null, "tximeta_tximport": null, "diamond_blastp": null}}, "target": "sentieon_rsempreparereference", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_43", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_named_process_output_emits_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_ascat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: copy number profiles of tumour cells. (tools: ascat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purecn/coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "bamclipper": "This module is used to clip primer sequences from your alignments.", "fastq_fastqc_umitools_fastp": "Read QC, UMI extraction and trimming", "ascat": "copy number profiles of tumour cells."}}, "target": "ascat", "target_idx": 4}
{"id": "subworkflow_pkg_quant_tximport_summarizedexperiment_1", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT", "modules": ["custom/tx2gene", "tximeta/tximport", "summarizedexperiment/summarizedexperiment"], "description": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT (custom/tx2gene, tximeta/tximport, summarizedexperiment/summarizedexperiment) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow quant_tximport_summarizedexperiment": null, "Local subworkflow QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT": null, "Leave them out": null}}, "target": "Use nf-core subworkflow quant_tximport_summarizedexperiment", "target_idx": 1}
{"id": "resource_atlas_splitmerge_1", "category": "resource_profiling", "state": {"process": "ATLAS_SPLITMERGE", "tool": "atlas/splitmerge", "description": "split single end read groups by length and merge paired end reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_SPLITMERGE (split single end read groups by length and merge paired end reads) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_freyja_boot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bootstrap sample demixing by resampling each site based on a multinomial distribution of read depth across all sites, where the event probabilities were determined by the fraction of the total sample reads found at each site, followed by a secondary resampling at each site according to a multinomial distribution (that is, binomial when there was only one SNV at a site), where event probabilities were determined by the frequencies of each base at the site, and the number of trials is given by the sequencing depth. (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja_variants": null, "bamtools_stats": null, "freyja_boot": null, "fcsgx_cleangenome": null, "bedgovcf": null}}, "target": "freyja_boot", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_40", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "field_constraint_sex_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_36", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_skani_triangle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: All-to-all ANI computation. (tools: skani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani/triangle": "All-to-all ANI computation.", "rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "angsd/contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome.", "skani/search": "Memory-efficient ANI database queries with skani."}}, "target": "skani/triangle", "target_idx": 0}
{"id": "mod_roary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pan-genome from annotated bacterial assemblies in GFF3 format (tools: roary)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "nanolyse": "DNA contaminant removal using NanoLyse", "tabix_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files", "agat_spaddintrons": "Add intron features to gtf/gff file without intron features.", "roary": "Calculate pan-genome from annotated bacterial assemblies in GFF3 format"}}, "target": "roary", "target_idx": 4}
{"id": "mod_cleanifier_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download human reference index (tools: cleanifier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "cleanifier_download": "Download human reference index", "plink2_pca": "Perform PCA analysis using PLINK", "vireo": "Use vireo to perform donor deconvolution for multiplexed scRNA-seq data", "blast_updateblastdb": "Downloads a BLAST database from NCBI"}}, "target": "cleanifier_download", "target_idx": 1}
{"id": "noul_workflow_completion_lifecycle_hook_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_oncoanalyser_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A comprehensive cancer DNA/RNA analysis and reporting pipeline. Topics: cancer, clinical, ctdna, dna, exome, longitudinal. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]"}}, "target": "oncoanalyser", "target_idx": 5}
{"id": "mod_pairtools_select_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select pairs according to given condition by options.args (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools_restrict": "Assign restriction fragments to pairs", "pairtools_select": "Select pairs according to given condition by options.args", "pairtools_merge": "Merge multiple pairs/pairsam files", "truvari_bench": "Given baseline and comparison sets of variants, calculate the recall/precision/f-measure", "samtools_calmd": "calculates MD and NM tags"}}, "target": "pairtools_select", "target_idx": 1}
{"id": "field_constraint_fastq_1_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "field_constraint_sex_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "mod_custom_tabulartogseagct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a TSV or CSV with features by row and observations by column to a GCT format file as consumed by GSEA (tools: tabulartogseagct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"syri": "Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearran", "gsea_gsea": "run the Broad Gene Set Enrichment tool in GSEA mode", "custom_tabulartogseagct": "Convert a TSV or CSV with features by row and observations by column to a GCT format file as consumed by GSEA", "openms_peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)", "seqkit_fx2tab": "Convert FASTA/Q to tabular format, and provide various information, like sequence length, GC content/GC skew."}}, "target": "custom_tabulartogseagct", "target_idx": 2}
{"id": "schema_std_evexplorer_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/evexplorer", "description": "nf-core/evexplorer is a pipeline for analyzing RNA data from extracellular vesicles, compatible with technologies such as nextflex, comboSeq, and ONT with further support forthcoming. evexplorer handles QC, expressed region detection, library size normalization and Differential RNA Expression (DRE)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/evexplorer?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq_1,fastq_2,pool,hash_index": null}}, "target": "sample,fastq_1,fastq_2,batch,condition", "target_idx": 2}
{"id": "samplesheet_arch_vcf_annotation_pipeline_0_3", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,vcf,tbi": null, "sample,bam,bai": null, "sample,bed": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_vembrane_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort VCF/BCF files by custom Python expressions for variant prioritization (tools: vembrane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/gwas": "Generate GWAS association studies", "htseq/count": "count how many reads map to each feature", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "vembrane/sort": "Sort VCF/BCF files by custom Python expressions for variant prioritization"}}, "target": "vembrane/sort", "target_idx": 4}
{"id": "schema_std_tumourevo_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/tumourevo. Description: Analysis pipeline to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/tumourevo.", "criteria": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "patient,sample,vcf,status,cna": null, "patient,vcf,tbi,dataset,tumour_sample": null}}, "target": "patient,vcf,tbi,dataset,tumour_sample", "target_idx": 3}
{"id": "pipe_all101_pacvar_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Longread PacBio sequencing processing for WGS and PureTarget. Topics: alignment, long-read, pacbio, puretarget, variant-calling, wgs. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"slamseq": null, "pathogensurveillance": null, "bactmap": null, "longraredisease": null, "nascent": null, "clipseq": null, "pacvar": null, "mcmicro": null}}, "target": "pacvar", "target_idx": 6}
{"id": "samplesheet_arch_rare_disease_trio_2_0", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_0", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_all101_fetchngs_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for ddbj analysis? Specific context: Pipeline to fetch metadata and raw FastQ files from public databases. Topics: ddbj, download, ena, fastq, geo, sra. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "seqsubmit": "nf-core pipeline for data submission to ENA", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]"}}, "target": "fetchngs", "target_idx": 5}
{"id": "samplesheet_arch_epigenomics_hic_0_4", "category": "samplesheet_schema", "state": {"technology": "3D Chromatin Structure", "workflow_entry": "FASTQC", "library_inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hi-C chromosome conformation capture mapping?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,matrix,contacts": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_igv_js_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: igv.js is an embeddable interactive genome visualization component (tools: igv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem3_gem3indexer": "Create a GEM index from a FASTA file", "igv_js": "igv.js is an embeddable interactive genome visualization component", "annotsv_installannotations": "Install the AnnotSV annotations", "cowpy": "Print any text in a cow or other characters", "merquryfk_hapmaker": "Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables"}}, "target": "igv_js", "target_idx": 1}
{"id": "mod_bedtools_shift_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Shifts each feature by specific number of bases (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa_psiperevent": null, "agat_convertgff2bed": null, "agat_convertbed2gff": null, "samtools_coverage": null, "bedtools_shift": null}}, "target": "bedtools_shift", "target_idx": 4}
{"id": "resource_bcftools_split_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SPLIT", "tool": "bcftools/split", "description": "Split a vcf file into files per chromosome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SPLIT (Split a vcf file into files per chromosome) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq", "data_format": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bbmap_filterbyname_3", "category": "resource_profiling", "state": {"process": "BBMAP_FILTERBYNAME", "tool": "bbmap/filterbyname", "description": "Filter out sequences by sequence header name(s)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_FILTERBYNAME (Filter out sequences by sequence header name(s)) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_cobs_compactconstruct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a compact bloom filter COBS index (tools: cobs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "fgbio/fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI", "cobs/compactconstruct": "Builds a compact bloom filter COBS index", "rbt/vcfsplit": "A tool for splitting VCF/BCF files into N equal chunks, including BND support", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "cobs/compactconstruct", "target_idx": 2}
{"id": "noul_subworkflow_structural_blocks_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_1_2", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,fastq_1": null, "sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "mod_differential_functional_enrichment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run functional analysis on differential abundance analysis output (tools: differential_functional_enrichment)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deseq2_differential": "runs a differential expression analysis with DESeq2", "dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs", "differential_functional_enrichment": "Run functional analysis on differential abundance analysis output", "fgumi_codec": "Call CODEC consensus reads from a UMI-grouped BAM with fgumi"}}, "target": "differential_functional_enrichment", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for FAIRE-seq / DNAse-seq open chromatin profiling. Input files: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for FAIRE-seq / DNAse-seq open chromatin profiling with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_kraken2_add_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds fasta files to a Kraken2 taxonomic database (tools: kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kraken2_add": "Adds fasta files to a Kraken2 taxonomic database", "tabix_bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde", "bam_markduplicates_picard": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "kraken2_add", "target_idx": 0}
{"id": "field_constraint_fastq_2_3_9", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "mod_mash_dist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate Mash distances between reference and query sequences (tools: mash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon_indexunion": "Combine multiple deacon indexes (A ∪ B ...)", "scds": "Module to use scds for doublet scoring", "snpdists": "Pairwise SNP distance matrix from a FASTA sequence alignment", "mash_dist": "Calculate Mash distances between reference and query sequences", "ska_distance": "Calculate pairwise distances and basic clustering from SKA sketches"}}, "target": "mash_dist", "target_idx": 3}
{"id": "mod_mash_sketch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates vastly reduced representations of sequences using MinHash (tools: mash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fairy/sketch": "Sketches FASTQ reads into binary sketch (.bcsp) files for alignment-free coverage estimation.", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "mash/sketch": "Creates vastly reduced representations of sequences using MinHash", "tcoffee/alncompare": "Compares 2 alternative MSAs to evaluate them.", "barrnap": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files"}}, "target": "mash/sketch", "target_idx": 2}
{"id": "mod_rtgtools_cnveval_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The cnveval tool of RTG tools. It is used to evaluate called CNV regions for agreement with a baseline CNV set. (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_extract": "Subset plink pfiles with a text file of variant identifiers", "rgi_cardannotation": "Preprocess the CARD database for RGI to predict antibiotic resistance from protein or nucleotide data", "rtgtools_bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "rtgtools_cnveval": "The cnveval tool of RTG tools. It is used to evaluate called CNV regions for agreement with a baseline CNV set", "holodeck_methylate": "Generate a methylation-annotated VCF from a reference genome with holodeck"}}, "target": "rtgtools_cnveval", "target_idx": 3}
{"id": "field_constraint_strandedness_1_4", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"pattern: ^[0-9]+$": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_clean_fcs_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CLEAN_FCS", "modules": ["fcs/fcsadaptor", "fcsgx/rungx"], "description": "Foreign Contamination Screen (FCS) is a tool suite for identifying and removing contaminant sequences in genome assemblies"}, "question": {"type": "choice", "instructions": "How should FASTA_CLEAN_FCS (fcs/fcsadaptor, fcsgx/rungx) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_CLEAN_FCS": null, "Use nf-core subworkflow fasta_clean_fcs": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_clean_fcs", "target_idx": 1}
{"id": "mod_sourmash_sketch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a signature (a group of FracMinHash sketches) of a sequence using sourmash (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash_compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "bcftools_plugintag2tag": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD.", "sourmash_sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "fmhfunprofiler": "Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references.", "cleanifier_index": "Builds a Cuckoo filter or Cuckoo hash table index from reference sequences (FASTA/FASTQ) for fast contaminatio"}}, "target": "sourmash_sketch", "target_idx": 2}
{"id": "intent_ask_question_3", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "build_pipeline": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 1}
{"id": "mod_gridss_assemble_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble breakend contigs for GRIDSS structural variant calling (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss_assemble": "Assemble breakend contigs for GRIDSS structural variant calling", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "openms_idfilter": "Filters peptide/protein identification results by different criteria.", "bamclipper": "This module is used to clip primer sequences from your alignments.", "fasta_explore_search_plot_tidk": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats\nalong a sliding win"}}, "target": "gridss_assemble", "target_idx": 0}
{"id": "mod_gfatools_gfa2fa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts GFA or rGFA files to FASTA (tools: gfatools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"manta_germline": null, "dshbio_exportsegments": null, "gfatools_gfa2fa": null, "vt_normalize": null, "bandage_image": null}}, "target": "gfatools_gfa2fa", "target_idx": 2}
{"id": "mod_nanomonsv_parse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parse all the supporting reads of putative somatic SVs using nanomonsv.\nAfter successful completion, you will find supporting reads stratified by\ndeletions, insertions, and rearrangements.\nA precursor to \"nanomonsv get\" (tools: nanomonsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": "Annotation and Ranking of Structural Variation", "dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "nanomonsv/parse": "Parse all the supporting reads of putative somatic SVs using nanomonsv.\nAfter successful completion, you will ", "caddsv/get": "Download CADD-SV annotation resources or SegmentNT model files.", "bedtools/intersect": "Allows one to screen for overlaps between two sets of genomic features."}}, "target": "nanomonsv/parse", "target_idx": 2}
{"id": "resource_aardvark_compare_2", "category": "resource_profiling", "state": {"process": "AARDVARK_COMPARE", "tool": "aardvark/compare", "description": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_COMPARE (A tool to evaluate variant calling performance by comparing a query VCF against ) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_41", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_denovotranscript_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq. Topics: denovo-assembly, rna-seq, transcriptome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteogenomicsdb": null, "denovotranscript": null, "rnasplice": null, "reportho": null, "viralrecon": null}}, "target": "denovotranscript", "target_idx": 1}
{"id": "field_constraint_sample_1_3", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"type: integer": null, "format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_csvtk_join_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Join two or more CSV (or TSV) tables by selected fields into a single table (tools: csvtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"assemblyscan": "Assembly summary statistics in JSON format", "ultraplex": "Ultraplex is an all-in-one software package for processing and demultiplexing fastq files.", "csvtk_concat": "Concatenate two or more CSV (or TSV) tables into a single table", "csvtk_join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "csvtk_sort": "Sort  CSV (or TSV) tables"}}, "target": "csvtk_join", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_0_25", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_wipertools_fastqwiper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files (tools: fastqwiper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer_makeucscfile": "Create a UCSC bed graph with the HOMER suite", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "wipertools_fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "snpsites": "Rapidly extracts SNPs from a multi-FASTA alignment."}}, "target": "wipertools_fastqwiper", "target_idx": 2}
{"id": "pipe_all101_reportho_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core pipeline for comparative analysis of ortholog predictions. Topics: ortholog. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ribomsqc": null, "drugresponseeval": null, "reportho": null, "lsmquant": null, "clipseq": null, "bactmap": null, "denovotranscript": null, "pixelator": null}}, "target": "reportho", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "data_format": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,unite_fasta": null, "sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_0_1", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fast5": null, "sample,bam": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_22", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_vrhyme_linkbins_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Linking bins output by vRhyme to create one sequences per bin (tools: vrhyme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vrhyme/linkbins": null, "verifybamid/verifybamid": null, "pridepy/fetchsdrf": null, "clame": null, "vrhyme/vrhyme": null}}, "target": "vrhyme/linkbins", "target_idx": 0}
{"id": "samplesheet_arch_singlecell_parse_splitseq_0_3", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,bam": null, "sample,well,plate": null, "sample,fastq_1,fastq_2": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_ont_demux_barcodes_2_5", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "intent_build_pipeline_10", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_4_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "NANOPLOT", "library_inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: High molecular weight environmental metagenomic long reads per sampling site?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "mod_shovill_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble bacterial isolate genomes from Illumina paired-end reads (tools: shovill)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sawfish/discover": "SV candidate discovery from PacBio HiFi data", "viennarna/rnalfold": "calculate locally stable secondary structures of RNAs", "shovill": "Assemble bacterial isolate genomes from Illumina paired-end reads", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "shovill", "target_idx": 2}
{"id": "mod_mmseqs_taxonomy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the lowest common ancestor by identifying the query sequence homologs against the target database. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trimal": "trimAl is a tool for the automated removal of spurious sequences or poorly aligned regions from a multiple seq", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "fastplong": "Perform adapter/quality trimming and QC on long sequencing reads (ONT, PacBio, etc.)", "mmseqs_taxonomy": "Computes the lowest common ancestor by identifying the query sequence homologs against the target database.", "mmseqs_easycluster": "Cluster sequences using MMSeqs2 easy cluster."}}, "target": "mmseqs_taxonomy", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_3", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_bigslice_bigslice_3", "category": "resource_profiling", "state": {"process": "BIGSLICE_BIGSLICE", "tool": "bigslice/bigslice", "description": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenBank format along with an HMM database and produces a SQLite database and FASTA outputs of predicted features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_BIGSLICE (A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nI) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_sentieon_tnfilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters the raw output of sentieon/tnhaplotyper2. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/tnfilter": "Filters the raw output of sentieon/tnhaplotyper2.", "rseqc/junctionannotation": "compare detected splice junctions to reference gene model", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "bedtools/sort": "Sorts a feature file by chromosome and other criteria."}}, "target": "sentieon/tnfilter", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_2_43", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_gcta_fastgwa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariatereml": "Run bivariate REML analysis with a single dense GRM", "folddisco_query": "Search a prebuilt folddisco index for a discontinuous residue motif in a query protein structure", "gcta_fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "vireo": "Use vireo to perform donor deconvolution for multiplexed scRNA-seq data", "gcta_calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups"}}, "target": "gcta_fastgwa", "target_idx": 2}
{"id": "resource_bedtools_map_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAP", "tool": "bedtools/map", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAP (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_4", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "field_constraint_status_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "mod_krona_ktimporttext_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a Krona chart from text files listing quantities and lineages. (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_plotprofile": null, "deeptools_plotheatmap": null, "krona_ktimporttext": null, "cellrangerarc_mkfastq": null, "gridss_generateponbedpe": null}}, "target": "krona_ktimporttext", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_5_2", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Visium spatial transcriptomics with histology image.", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,image": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "noul_channel_mix_operator_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_plink2_vcf2bgen_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert from VCF file to BGEN file version 1.2 format preserving dosages. (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "merquryfk_katcomp": "A reimplemenation of Kat Comp to work with FastK databases", "plink2_vcf2bgen": "Convert from VCF file to BGEN file version 1.2 format preserving dosages.", "plink2_filter": "Filters plink bfiles or pfiles with filters such as maf or var", "plink2_pca": "Perform PCA analysis using PLINK"}}, "target": "plink2_vcf2bgen", "target_idx": 2}
{"id": "mod_samtools_samples_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Write sample names and path to reference genome of an alignment to a text file. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "kleborate": "Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species", "sylph/sketchsamples": "Sketching/indexing sequencing reads", "samtools/samples": "Write sample names and path to reference genome of an alignment to a text file.", "plink2/filter": "Filters plink bfiles or pfiles with filters such as maf or var"}}, "target": "samtools/samples", "target_idx": 3}
{"id": "resource_bamaligncleaner_0", "category": "resource_profiling", "state": {"process": "BAMALIGNCLEANER", "tool": "bamaligncleaner", "description": "removes unused references from header of sorted BAM/CRAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMALIGNCLEANER (removes unused references from header of sorted BAM/CRAM files.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_6_5", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns are standard for CUT&RUN / CUT&TAG chromatin profiling with IgG control input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,spikein,fastq": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_36", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_gatk4_splitcram_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits CRAM files efficiently by taking advantage of their container based structure (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bamsormadup": "Parallel sorting and duplicate marking", "autocycler_trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "bwameme_mem": "Performs fastq alignment to a fasta reference using BWA-MEME", "gatk4_splitcram": "Splits CRAM files efficiently by taking advantage of their container based structure", "gatk_indelrealigner": "Performs local realignment around indels to correct for mapping errors"}}, "target": "gatk4_splitcram", "target_idx": 3}
{"id": "schema_std_reportho_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/reportho", "assay": "reportho pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/reportho (nf-core pipeline for comparative analysis of ortholog predic)?", "criteria": {"sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,condition,reference": null, "id,fasta,query": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "id,fasta,query", "target_idx": 2}
{"id": "resource_biobambam_bammarkduplicates2_1", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMARKDUPLICATES2", "tool": "biobambam/bammarkduplicates2", "description": "Locate and tag duplicate reads in a BAM file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMARKDUPLICATES2 (Locate and tag duplicate reads in a BAM file) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_sarek_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay": "sarek pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/sarek (Analysis pipeline to detect germline or somatic variants (pr)?", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 3}
{"id": "mod_numorph_3dunet_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: 3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit. (tools: numorph_3dunet)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coreograph": null, "bio2zarr_vcf2zarrexplode": null, "kleborate": null, "baysor_run": null, "numorph_3dunet": null}}, "target": "numorph_3dunet", "target_idx": 4}
{"id": "resource_bcftools_mpileup_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MPILEUP", "tool": "bcftools/mpileup", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MPILEUP (Compresses VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_include_modular_process_syntax_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_methylsieve_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter/tag unconverted reads in methylation sequencing with methylsieve; for maximum throughput it can also run inline in the alignment pipe (aligner | methylsieve | sort) rather than as a standalone step (tools: methylsieve)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "cellrangeratac_count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "genomescope2": "Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical ", "methylsieve": "Filter/tag unconverted reads in methylation sequencing with methylsieve; for maximum throughput it can also ru", "bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts."}}, "target": "methylsieve", "target_idx": 3}
{"id": "resource_affy_justrma_1", "category": "resource_profiling", "state": {"process": "AFFY_JUSTRMA", "tool": "affy/justrma", "description": "Read CEL files into an ExpressionSet and generate a matrix"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AFFY_JUSTRMA (Read CEL files into an ExpressionSet and generate a matrix) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_apbs_5", "category": "resource_profiling", "state": {"process": "APBS", "tool": "apbs", "description": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Boltzmann Solver). Produces electrostatic potential\nmaps and solvation energy values for large biomolecular assemblages."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to APBS (Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nus) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_mm2plus_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides fasta index required by mm2plus alignment. (tools: mm2plus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsift/split": null, "simpleaf/index": null, "bismark/genomepreparation": null, "mm2plus/index": null, "bowtie/build": null}}, "target": "mm2plus/index", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_39", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_plink_epistasis_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk_depth": "Creates a bed file containing the depth of data at intervals of an aligned bam.", "plink_epistasis": "Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others.", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "plink_fastepistasis": "Fast Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others.", "verifybamid_verifybamid2": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig"}}, "target": "plink_epistasis", "target_idx": 1}
{"id": "pipe_all101_nanostring_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for nanostring analysis? Specific context: An analysis pipeline for Nanostring nCounter expression data.. Topics: nanostring, nanostringnorm. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "callingcards": "A pipeline for processing calling cards data", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri"}}, "target": "nanostring", "target_idx": 7}
{"id": "mod_hifitrimmer_trim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/FASTQ input and emits gzip-compressed FASTA (default) or FASTQ, or SAM, BAM, or CRAM according to the selected output format. (tools: hifi-trimmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender_removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "bam2fastx_bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "hifiadapterfilt_hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "hifitrimmer_trim": "Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/F", "gatk4_createreadcountpanelofnormals": "Creates a panel of normals (PoN) for read-count denoising given the read counts for samples in the panel."}}, "target": "hifitrimmer_trim", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_13", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_bam_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "field_constraint_fastq_1_0_4", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "schema_std_mag_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay": "mag pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/mag (Assembly and binning of metagenomes)?", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "sample_id,img_directory,parameter_file": null, "sample,tools,file,index": null}}, "target": "sample,run,group,short_reads_1,short_reads_2", "target_idx": 0}
{"id": "resource_bio2zarr_vcf2zarrconvert_2", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARRCONVERT", "tool": "bio2zarr/vcf2zarrconvert", "description": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARRCONVERT (Convert VCF data to the VCF Zarr specification reliably, in parallel or distribu) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bbmap_bbsplit_4", "category": "resource_profiling", "state": {"process": "BBMAP_BBSPLIT", "tool": "bbmap/bbsplit", "description": "Split sequencing reads by mapping them to multiple references simultaneously"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBSPLIT (Split sequencing reads by mapping them to multiple references simultaneously) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Multi-lane Illumina sequencing run of clinical samples. Input files: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_tif_registration_stainwarpy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy (tools: tif_registration_stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy_extractchannel": null, "leafcutter_differentialsplicing": null, "hmmer_hmmlogo": null, "stainwarpy_register": null, "tif_registration_stainwarpy": null}}, "target": "tif_registration_stainwarpy", "target_idx": 4}
{"id": "schema_std_scrnaseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/scrnaseq. Description: Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/scrnaseq.", "criteria": {"sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,fastq_1,fastq_2,fastq_barcode,expected_cells", "target_idx": 0}
{"id": "resource_bbmap_bbmerge_0", "category": "resource_profiling", "state": {"process": "BBMAP_BBMERGE", "tool": "bbmap/bbmerge", "description": "Merging overlapping paired reads into a single read."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBMERGE (Merging overlapping paired reads into a single read.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bbmap_bbduk_2", "category": "resource_profiling", "state": {"process": "BBMAP_BBDUK", "tool": "bbmap/bbduk", "description": "Adapter and quality trimming of sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBDUK (Adapter and quality trimming of sequencing reads) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_3_0", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "resource_atlas_pmd_0", "category": "resource_profiling", "state": {"process": "ATLAS_PMD", "tool": "atlas/pmd", "description": "Estimate the post-mortem damage patterns of DNA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_PMD (Estimate the post-mortem damage patterns of DNA) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bismark_align_5", "category": "resource_profiling", "state": {"process": "BISMARK_ALIGN", "tool": "bismark/align", "description": "Performs alignment of BS-Seq reads using bismark"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_ALIGN (Performs alignment of BS-Seq reads using bismark) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_krakentools_combinekreports_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes multiple kraken-style reports and combines them into a single report file (tools: krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krakentools/combinekreports": "Takes multiple kraken-style reports and combines them into a single report file", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "fastq_extract_kraken_krakentools": "Extract classified Kraken2 reads by taxonomic id", "vcfexpress": "Filter a VCF/BCF and optionally print by template expression. If no template is given the output will be VCF/B", "scramble/clusteranalysis": "The Cluster Analysis tool of Scramble analyses and interprets the soft-clipped clusters found by `cluster_iden"}}, "target": "krakentools/combinekreports", "target_idx": 0}
{"id": "mod_csvtk_mutate2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a new column from selected fields by awk-like arithmetic/string expressions (tools: csvtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wipertools/reportgather": "A tool of the wipertools suite that merges wiping reports generated by wipertools_fastqwiper", "csvtk/sort": "Sort  CSV (or TSV) tables", "csvtk/mutate2": "Create a new column from selected fields by awk-like arithmetic/string expressions", "csvtk/split": "Splits CSV/TSV into multiple files according to column values", "clustalo/guidetree": "Renders a guidetree in clustalo"}}, "target": "csvtk/mutate2", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic cancer variant calling with tumor-normal pairs)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "patient,sample,status,bam,bai": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "core_tool_macs2_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Model-based analysis of ChIP-Seq data to identify statistically significant transcription factor binding sites and histone mark enrichment peaks.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"macs2": "Model-based Analysis of ChIP-Seq (MACS) for identifying transcript factor binding sites", "seacr": "Peak caller", "genrich": "Peak caller", "epic2": "Diffuse domain caller", "homer": "Motif discovery tool"}}, "target": "macs2", "target_idx": 0}
{"id": "schema_std_detaxizer_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/detaxizer. Description: A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/detaxizer.", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,seq_data,pbi,start_from": null, "condition,type,microbiome_path,alleles,weights_path": null}}, "target": "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1", "target_idx": 1}
{"id": "mod_midas_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to estimate bacterial species abundance (tools: midas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate/run": null, "bam_dedup_stats_samtools_umitools": null, "gatk4/shiftfasta": null, "midas/run": null, "amrfinderplus/update": null}}, "target": "midas/run", "target_idx": 3}
{"id": "intent_prepare_data_16", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "prepare_data", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_4_0", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end Tn5 transposed FASTQs across conditions and replicates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "noul_multiple_script_sections_invalid_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_fungtion_downloadmodels_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads the pretrained ESM-1b weights (esm1b_t33_650M_UR50S.pt) that fungtion\nuses for fungal effector prediction into a local models/ directory via\n`fungtion setup-models`. The downloaded directory is used as input to the\nFUNGTION_FUNGTION prediction module. (tools: fungtion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_csq": null, "fungtion_fungtion": null, "ngscheckmate_ncm": null, "sentieon_coveragemetrics": null, "fungtion_downloadmodels": null}}, "target": "fungtion_downloadmodels", "target_idx": 4}
{"id": "mod_verifybamid_verifybamid2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure high quality sequence reads and reliable downstream analysis. (tools: verifybamid2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"authentict/deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries", "checkm2/databasedownload": "CheckM2 database download", "verifybamid/verifybamid": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "catpack/contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).", "verifybamid/verifybamid2": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig"}}, "target": "verifybamid/verifybamid2", "target_idx": 4}
{"id": "samplesheet_arch_proteomics_dia_3_0", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Data-Independent Acquisition (DIA) quantitative mass spectrometry with entry step INPUT_CHECK.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null, "sample,peptides_tsv": null, "sample,mzml": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "resource_blobtk_plot_2", "category": "resource_profiling", "state": {"process": "BLOBTK_PLOT", "tool": "blobtk/plot", "description": "Creates differing styles of blobplots depending on provided arguments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_PLOT (Creates differing styles of blobplots depending on provided arguments.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_48", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "schema_std_radseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/radseq. Description: Variant-calling pipeline for Restriction site-associated DNA sequencing (RADseq)..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/radseq.", "criteria": {"sample,fastq_1,fastq_2,genome": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1,fastq_2,group": null, "seeds,network,perturbed_networks": null}}, "target": "sample,fastq_1,fastq_2,umi_barcodes", "target_idx": 1}
{"id": "field_constraint_expected_cells_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_6_5", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns are standard for Viral genome sequencing on Oxford Nanopore MinION / GridION input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "resource_bcftools_pluginfixploidy_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFIXPLOIDY", "tool": "bcftools/pluginfixploidy", "description": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFIXPLOIDY (The fixploidy plugin fixes ploidy in genotype fields according to specified ploi) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bcftools_plugintag2tag_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINTAG2TAG", "tool": "bcftools/plugintag2tag", "description": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINTAG2TAG (Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_sex_0_3", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "schema_std_bamtofastq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/bamtofastq. Description: Converts bam or cram files to fastq format and does quality control..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/bamtofastq.", "criteria": {"sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample_id,img_directory,parameter_file": null, "sample_id,mapped,index,file_type": null}}, "target": "sample_id,mapped,index,file_type", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_5_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_rtgtools_bndeval_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND baseline variant set (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tmb_pytmb": null, "fastq_align_dedup_bwameth": null, "holodeck_simulate": null, "rtgtools_cnveval": null, "rtgtools_bndeval": null}}, "target": "rtgtools_bndeval", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wgs_pe_0_0", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "local_subworkflow_nextclade_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should this step (nextclade/run) be packaged: Viral clade typing and QC?", "criteria": {"Local subworkflow NEXTCLADE": null, "Leave them out": null, "Use nf-core subworkflow nextclade": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 0}
{"id": "mod_umitools_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "umitools_extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "fgbio_groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "gatk4_createsequencedictionary": "Creates a sequence dictionary for a reference sequence", "hmmer_eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie"}}, "target": "umitools_extract", "target_idx": 1}
{"id": "mod_porechop_abi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extension of Porechop whose purpose is to process adapter sequences in ONT reads. (tools: porechop_abi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mudskipper_index": null, "porechop_abi": null, "hifiadapterfilt_hifiadapterfilt": null, "artic_aligntrim": null, "deeptools_bamcoverage": null}}, "target": "porechop_abi", "target_idx": 1}
{"id": "mod_coverm_contig_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Map reads to contigs and estimate coverage (tools: coverm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr/merge": "Merge reads that were mapped to multiple indices", "gatk4/variantfiltration": "Filter variants", "checkm/qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "coverm/contig": "Map reads to contigs and estimate coverage", "coptr/estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data"}}, "target": "coverm/contig", "target_idx": 3}
{"id": "resource_busco_busco_4", "category": "resource_profiling", "state": {"process": "BUSCO_BUSCO", "tool": "busco/busco", "description": "Benchmarking Universal Single Copy Orthologs"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_BUSCO (Benchmarking Universal Single Copy Orthologs) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_0_25", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_4_0", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities", "pipeline": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "noul_include_modular_process_syntax_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/dualrnaseq) for Dual RNA-seq simultaneous host and pathogen transcriptomics. Input files: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/dualrnaseq, determine the input samplesheet column structure for: Dual RNA-seq simultaneous host and pathogen transcriptomics.", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_6_4", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter", "pipeline": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Small RNA / miRNA sequencing input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,mirna_id": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_plink2_remove_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove samples from a plink2 dataset (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium", "huggingface/download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "plink2/remove": "Remove samples from a plink2 dataset", "ultra/index": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment", "plink2/pca": "Perform PCA analysis using PLINK"}}, "target": "plink2/remove", "target_idx": 2}
{"id": "resource_bismark_report_5", "category": "resource_profiling", "state": {"process": "BISMARK_REPORT", "tool": "bismark/report", "description": "Collects bismark alignment reports"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_REPORT (Collects bismark alignment reports) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_undeclared_process_file_inputs_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bcftools_merge_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MERGE", "tool": "bcftools/merge", "description": "Merge VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MERGE (Merge VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_37", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_survivor_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Report multiple stats over a VCF file (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/concat": null, "survivor/merge": null, "agat/sqstatbasic": null, "survivor/stats": null, "snpsift/annmem": null}}, "target": "survivor/stats", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_42", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Single-end Oxford Nanopore direct RNA)", "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Oxford Nanopore direct RNA input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "schema_std_mag_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/mag. Description: Assembly and binning of metagenomes.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/mag.", "criteria": {"sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,bundle,image": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,run,group,short_reads_1,short_reads_2", "target_idx": 2}
{"id": "mod_gatk4_variantstotable_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract fields from a VCF file to a tab-delimited table (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ciri2": "Circular RNA identification based on multiple seed matching", "gatk4_variantstotable": "Extract fields from a VCF file to a tab-delimited table", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files.", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "gatk4_variantstotable", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_13", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_2_0", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,otu_table": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_agrvate_0", "category": "resource_profiling", "state": {"process": "AGRVATE", "tool": "agrvate", "description": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGRVATE (Rapid identification of Staphylococcus aureus agr locus type and agr operon vari) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bbmap_bbnorm_0", "category": "resource_profiling", "state": {"process": "BBMAP_BBNORM", "tool": "bbmap/bbnorm", "description": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result in a flat coverage distribution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBNORM (BBNorm is designed to normalize coverage by down-sampling reads over high-depth ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_rpbp_estimateorfbayesfactors_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian models to its per-codon\nP-site count vector: a \"translated\" model that expects P-site density\nto concentrate at codon-start positions (the in-frame signal a\ntranslating ribosome produces), and an \"untranslated\" / noise model\nfor the same data. The Bayes factor (ratio of marginal likelihoods)\nquantifies how much the data favour the translated hypothesis.\n\nEmits a BED-style table with one row per ORF carrying genomic\ncoordinates plus the mean and variance of the log Bayes factor across\nMCMC samples. Downstream, `rpbp/selectfinalpredictionset` applies\nBayes-factor, length and overlap rules to this table to produce the\nfinal filtered prediction set.\n\nUses the Stan models bundled inside the rpbp Python package. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/selectfinalpredictionset": null, "rpbp/getperiodiclengthsoffsets": null, "limma/differential": null, "rpbp/estimateorfbayesfactors": null, "fastq_remove_rrna": null}}, "target": "rpbp/estimateorfbayesfactors", "target_idx": 3}
{"id": "mod_seqkit_pair_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: match up paired-end reads from two fastq files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_sliding": "Use seqkit to generate sliding windows of input fasta", "seqkit_replace": "Use seqkit to find/replace strings within sequences and sequence headers", "seqkit_pair": "match up paired-end reads from two fastq files", "samtools_index": "Index SAM/BAM/CRAM file", "pigz_compress": "Compresses files with pigz."}}, "target": "seqkit_pair", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic cancer variant calling with tumor-normal pairs. Input files: Paired-end FASTQs for patient tumor and germline normal tissue.", "question": {"type": "choice", "instructions": "Which columns are standard for Somatic cancer variant calling with tumor-normal pairs input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_agat_convertspgff2gtf_0", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2GTF", "tool": "agat/convertspgff2gtf", "description": "Converts a GFF/GTF file into a proper GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2GTF (Converts a GFF/GTF file into a proper GTF file) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_scramble_clusteranalysis_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Cluster Analysis tool of Scramble analyses and interprets the soft-clipped clusters found by `cluster_identifier` (tools: scramble)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scramble/clusteridentifier": "The cluster_identifier tool of Scramble identifies soft clipped clusters", "scramble/clusteranalysis": "The Cluster Analysis tool of Scramble analyses and interprets the soft-clipped clusters found by `cluster_iden", "salsa2": "SALSA, A tool to scaffold long read assemblies with HiC", "blat": "Queries a sequence subject", "controlfreec/freec2circos": "Format Freec output to circos input format"}}, "target": "scramble/clusteranalysis", "target_idx": 1}
{"id": "pipe_all101_riboseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"airrflow": null, "pacvar": null, "smrnaseq": null, "raredisease": null, "riboseq": null, "viralmetagenome": null, "phaseimpute": null, "pairgenomealign": null}}, "target": "riboseq", "target_idx": 4}
{"id": "schema_std_raredisease_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay": "raredisease pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/raredisease (Call and score variants from WGS/WES of rare disease patient)?", "criteria": {"sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,fastq_1,fastq_2,replicate,control": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 1}
{"id": "mod_utils_nfcore_pipeline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow with utility functions specific to the nf-core pipeline template (tools: utils_nfcore_pipeline)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nfcore_pipeline": "Subworkflow with utility functions specific to the nf-core pipeline template", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline", "kaiju/mkfmi": "Make Kaiju FMI-index file from a protein FASTA file", "utils_references": "Functionality for dealing with references that may be useful for any Nextflow pipeline"}}, "target": "utils_nfcore_pipeline", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_24", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_igv_js_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: igv.js is an embeddable interactive genome visualization component (tools: igv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genomad/download": "Download geNomad databases and related files", "gatk4spark/markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "igv/js": "igv.js is an embeddable interactive genome visualization component"}}, "target": "igv/js", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay_type": "PacBio HiFi unaligned BAM variant calling", "data_format": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi unaligned BAM variant calling input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_26", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "noul_default_empty_channel_behavior_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hic", "assay_type": "Hi-C chromosome conformation capture mapping", "data_format": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hi-C chromosome conformation capture mapping with entry step FASTQC.", "criteria": {"sample,bed": null, "sample,matrix,contacts": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_0_3", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral amplicon sequencing with primers?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_biscuit_pileup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "gapseq_draft": "Create draft metabolic model from pathway and transporter predictions", "regenie_splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "bismark_report": "Collects bismark alignment reports", "biscuit_pileup": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call so"}}, "target": "biscuit_pileup", "target_idx": 4}
{"id": "mod_bcftools_pluginsetgt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that. (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "rundbcan_easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "bcftools_concat": "Concatenate VCF files", "bcftools_index": "Index VCF tools", "deacon_filter": "Filter DNA sequences using index of reference genome"}}, "target": "bcftools_pluginsetgt", "target_idx": 0}
{"id": "mod_catpack_bins_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gtdbtk_classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "catpack_bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "maltextract": "Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening", "pindel_pindel": "Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and", "catpack_addnames": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins)."}}, "target": "catpack_bins", "target_idx": 1}
{"id": "mod_sexdeterrmine_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate the relative coverage on the Gonosomes vs Autosomes from the output of samtools depth, with error bars. (tools: sexdeterrmine)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmbuild": null, "sexdeterrmine": null, "atlas/pmd": null, "bamaligncleaner": null, "damageprofiler": null}}, "target": "sexdeterrmine", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_3_0", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for RNA gene fusion detection (Arriba, STAR-Fusion) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fusion_bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_3_2", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking with entry step FASTQC.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_rtgtools_cnveval_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The cnveval tool of RTG tools. It is used to evaluate called CNV regions for agreement with a baseline CNV set. (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rtgtools/cnveval": null, "regenie/splitl0": null, "holodeck/methylate": null, "holodeck/simulate": null, "trgt/merge": null}}, "target": "rtgtools/cnveval", "target_idx": 0}
{"id": "pipe_all101_mnaseseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze MNase-seq analysis pipeline using BWA and DANPOS2.. Topics: mnase-seq, nucleosome, nucleosome-maps, nucleosome-positioning. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnadnavar": null, "pacvar": null, "ribomsqc": null, "mnaseseq": null, "bactmap": null}}, "target": "mnaseseq", "target_idx": 3}
{"id": "mod_getorganelle_fromreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembles organelle genomes from genomic data (tools: getorganelle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani/dist": null, "abra2": null, "getorganelle/fromreads": null, "ale": null, "mm2plus/align": null}}, "target": "getorganelle/fromreads", "target_idx": 2}
{"id": "mod_tcoffee_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using T_COFFEE (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco/phylogenomics": null, "tcoffee/align": null, "merquryfk/hapmaker": null, "bwa/mem": null, "pyclonevi": null}}, "target": "tcoffee/align", "target_idx": 1}
{"id": "field_constraint_bam_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "pipe_all101_longraredisease_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders. Topics: nanopore, pacbio. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metaboigniter": null, "longraredisease": null, "phyloplace": null, "sarek": null, "rangeland": null}}, "target": "longraredisease", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/genomeassembler) for Long-read Pacific Biosciences HiFi sequencing. Input files: Single HiFi BAM or FastQ.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Pacific Biosciences HiFi sequencing with entry step HIFIADAPTERFILT.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_13", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_scnanoseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for 10xgenomics. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo"}}, "target": "scnanoseq", "target_idx": 3}
{"id": "pipe_all101_callingcards_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for processing calling cards data. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnafusion": null, "pacvar": null, "rnavar": null, "clipseq": null, "diaproteomics": null, "callingcards": null, "hadge": null, "mag": null}}, "target": "callingcards", "target_idx": 5}
{"id": "field_constraint_expected_cells_0_9", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Multiplexed Oxford Nanopore run with barcode demultiplexing. Input files: Nanopore sequencing run with sample to barcode assignment and flowcell type.", "question": {"type": "choice", "instructions": "Which columns are standard for Multiplexed Oxford Nanopore run with barcode demultiplexing input samplesheet?", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "subworkflow_pkg_mafft_align_3", "category": "subworkflow_packaging", "state": {"subworkflow": "MAFFT_ALIGN", "modules": ["mafft/align"], "description": "Prepare channels for running MAFFT/align"}, "question": {"type": "choice", "instructions": "How should MAFFT_ALIGN (mafft/align) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow MAFFT_ALIGN": null, "Use nf-core subworkflow mafft_align": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow mafft_align", "target_idx": 2}
{"id": "mod_last_mafconvert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts MAF alignments in another format. (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_postmask": "Post-alignment masking", "biscuit_mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "mobsuite_typer": "Bacterial plasmid typing and mobility prediction", "last_lastdb": "Prepare sequences for subsequent alignment with lastal.", "last_mafconvert": "Converts MAF alignments in another format."}}, "target": "last_mafconvert", "target_idx": 4}
{"id": "mod_bclconvert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Illumina BCL files (tools: bclconvert)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bclconvert": "Demultiplex Illumina BCL files", "mirtop/counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns ", "bcl2fastq": "Demultiplex Illumina BCL files", "bases2fastq": "Demultiplex Element Biosciences bases files", "cellranger/mkgtf": "Module to build a filtered GTF needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkgtf command."}}, "target": "bclconvert", "target_idx": 0}
{"id": "mod_pydamage_analyze_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Damage parameter estimation for ancient DNA (tools: pydamage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"endorspy": null, "dedup": null, "fcsgx_rungx": null, "fastp": null, "pydamage_analyze": null}}, "target": "pydamage_analyze", "target_idx": 4}
{"id": "mod_bismark_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of BS-Seq reads using bismark (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "bismark/align": "Performs alignment of BS-Seq reads using bismark", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "krakentools/combinekreports": "Takes multiple kraken-style reports and combines them into a single report file", "delly/call": "Call structural variants"}}, "target": "bismark/align", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_1", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_agat_convertspgff2tsv_4", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2TSV", "tool": "agat/convertspgff2tsv", "description": "Converts a GFF/GTF file into a TSV file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2TSV (Converts a GFF/GTF file into a TSV file) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_20", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_fastq_trim_fastp_fastqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read QC, fastp trimming and read qc (tools: fastq_trim_fastp_fastqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_trim_fastp_fastqc": "Read QC, fastp trimming and read qc", "bam_qc_rnaseq": "Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC ", "gatk4/printsvevidence": "WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end an", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data"}}, "target": "fastq_trim_fastp_fastqc", "target_idx": 0}
{"id": "mod_fasta_build_add_kraken2_bracken_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KRAKEN2 and BRACKEN build custom database subworkflow (tools: fasta_build_add_kraken2_bracken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "fasta_build_add_kraken2_bracken": "KRAKEN2 and BRACKEN build custom database subworkflow", "manta_somatic": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "vrhyme_vrhyme": "Binning virus genomes from metagenomes"}}, "target": "fasta_build_add_kraken2_bracken", "target_idx": 1}
{"id": "resource_autocycler_combine_3", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMBINE", "tool": "autocycler/combine", "description": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMBINE (Merge resolved cluster assemblies into final consensus outputs with Autocycler.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_bai_0_5", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "mod_deepvariant_postprocessvariants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/duplex": null, "fgbio/sortbam": null, "bcftools/consensus": null, "deepvariant/postprocessvariants": null, "bcftools/concat": null}}, "target": "deepvariant/postprocessvariants", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_17", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_0_1", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,cram,crai": null, "sample,cram": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 0}
{"id": "mod_bcftools_mpileup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses VCF files (tools: mpileup)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldseek_easysearch": "Search for protein structural hits against a foldseek database of protein structures", "atlas_call": "generate VCF file from a BAM file using various calling methods", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools_mpileup": "Compresses VCF files", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope"}}, "target": "bcftools_mpileup", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_12", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_crisprseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/crisprseq. Description: A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`)..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/crisprseq.", "criteria": {"sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,fastq_2": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "id,fasta": null}}, "target": "sample,fastq_1,fastq_2,condition,reference", "target_idx": 0}
{"id": "resource_bowtie2_align_2", "category": "resource_profiling", "state": {"process": "BOWTIE2_ALIGN", "tool": "bowtie2/align", "description": "Align reads to a reference genome using bowtie2"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_ALIGN (Align reads to a reference genome using bowtie2) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_rtgtools_svdecompose_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngscheckmate/vafncm": null, "fgbio/callmolecularconsensusreads": null, "severus": null, "svtools/vcftobedpe": null, "rtgtools/svdecompose": null}}, "target": "rtgtools/svdecompose", "target_idx": 4}
{"id": "mod_sambamba_depth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Outputs a coverage file from bam files (tools: sambamba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sambamba_depth": "Outputs a coverage file from bam files", "metabat2_jgisummarizebamcontigdepths": "Depth computation per contig step of metabat2", "macsyfinder_download": "Download MacSyFinder models using msf_data", "jvarkit_wgscoverageplotter": "Plot whole genome coverage from BAM/CRAM file as SVG", "seqkit_seq": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)"}}, "target": "sambamba_depth", "target_idx": 0}
{"id": "pipe_all101_proteinfamilies_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for metagenomics. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr"}}, "target": "proteinfamilies", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_7", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_any2fasta_5", "category": "resource_profiling", "state": {"process": "ANY2FASTA", "tool": "any2fasta", "description": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input files may be gzip, bzip2, zip, or zstd compressed."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANY2FASTA (Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_ariba_run_3", "category": "resource_profiling", "state": {"process": "ARIBA_RUN", "tool": "ariba/run", "description": "Query input FASTQs against Ariba formatted databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_RUN (Query input FASTQs against Ariba formatted databases) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcftools_isec_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ISEC", "tool": "bcftools/isec", "description": "Apply set operations to VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ISEC (Apply set operations to VCF files) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_variantprioritization_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/variantprioritization", "assay": "variantprioritization pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/variantprioritization (Bioinformatics analysis pipeline for the functional annotati)?", "criteria": {"sample,sample_id,fastq_1,fastq_2,method": null, "patient,sample,vcf,status,cna": null, "sample,bam,bai,cram,crai": null, "sample_id,bam,vcf,library_id,lane": null}}, "target": "patient,sample,vcf,status,cna", "target_idx": 1}
{"id": "mod_pairtools_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple pairs/pairsam files (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/merge": "Merge VCF files", "jvarkit/dict2bed": "Extract BED file from hts files containing a dictionary (VCF,BAM, CRAM, DICT, etc...)", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "pairtools/merge": "Merge multiple pairs/pairsam files", "custom/tabulartogseacls": "Make a GSEA class file (.cls) from tabular inputs"}}, "target": "pairtools/merge", "target_idx": 3}
{"id": "core_tool_picard_markduplicates_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Identify and flag PCR and optical duplicate reads in coordinate-sorted BAM files based on 5-prime mapping coordinates.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"picard_markduplicates": "Identifies duplicate reads in BAM files", "samtools": "SAM/BAM utilities", "gatk_markduplicates": "GATK duplicate marking", "sambamba": "Fast BAM tools", "fastp": "FASTQ trimmer"}}, "target": "picard_markduplicates", "target_idx": 0}
{"id": "schema_std_nanostring_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/nanostring. Description: An analysis pipeline for Nanostring nCounter expression data..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/nanostring.", "criteria": {"sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,fastq_1,fastq_2,bam,bai": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample_id,name,description,path,path_2": null}}, "target": "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT", "target_idx": 2}
{"id": "resource_baysor_segfree_5", "category": "resource_profiling", "state": {"process": "BAYSOR_SEGFREE", "tool": "baysor/segfree", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_SEGFREE (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_methyldackel_mbias_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates methylation bias plots from alignments (tools: methyldackel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/report": null, "gatk/indelrealigner": null, "bismark/methylationextractor": null, "methyldackel/mbias": null, "utils_annotation_cache": null}}, "target": "methyldackel/mbias", "target_idx": 3}
{"id": "resource_basicpy_4", "category": "resource_profiling", "state": {"process": "BASICPY", "tool": "basicpy", "description": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is developed based on the Matlab version of BaSiC tool with major improvements in the algorithm."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASICPY (BaSiCPy is a python package for background and shading correction of optical mic) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_2_43", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_amulety_esm2_1", "category": "resource_profiling", "state": {"process": "AMULETY_ESM2", "tool": "amulety/esm2", "description": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ESM2 (A module to create esm2 embeddings of antibody (BCR) amino acid sequences using ) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_pacvar_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Longread PacBio sequencing processing for WGS and PureTarget. Topics: alignment, long-read, pacbio, puretarget, variant-calling, wgs. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "seqsubmit": "nf-core pipeline for data submission to ENA", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]"}}, "target": "pacvar", "target_idx": 5}
{"id": "mod_merquryfk_ploidyplot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An improved version of Smudgeplot using FastK (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscreen_buildfromindex": null, "merquryfk_ploidyplot": null, "perbase": null, "cobiontid_kmercounter": null, "concoct_concoct": null}}, "target": "merquryfk_ploidyplot", "target_idx": 1}
{"id": "mod_somalier_ancestry_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/GVCF or from jointly-called VCFs (tools: somalier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome", "survivor/simsv": "Simulate an SV VCF file based on a reference genome", "ascat": "copy number profiles of tumour cells.", "somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/"}}, "target": "somalier/ancestry", "target_idx": 4}
{"id": "mod_transrate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reference-free and reference-based quality assessment of de novo transcriptome\nassemblies. Only sequence-based (--assembly) and reference-based (--reference) metrics\nare supported. Read-based metrics (--left/--right) are not: they hard-require the\n`bam-read` binary, which isn't published on any conda channel, and their aligner\n(snap-aligner, pinned to an old dev build) segfaults building an index for at least\nsmall test genomes. (tools: transrate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_plot": null, "gstama_collapse": null, "msisensor_scan": null, "transrate": null, "dastool_dastool": null}}, "target": "transrate", "target_idx": 3}
{"id": "mod_snpsift_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate a VCF file with another VCF file (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellranger/mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command.", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "octopusv/svcf2bed": "Converts octopusv SVCF files to the standard BED format", "atlas/call": "generate VCF file from a BAM file using various calling methods", "snpsift/annotate": "Annotate a VCF file with another VCF file"}}, "target": "snpsift/annotate", "target_idx": 4}
{"id": "samplesheet_arch_faire_seq_chromatin_0_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bcl2fastq_0", "category": "resource_profiling", "state": {"process": "BCL2FASTQ", "tool": "bcl2fastq", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCL2FASTQ (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_createpanelrefs_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for createpanelrefs analysis? Specific context: Generate Panel of Normals, models or other similar references from lots of samples. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin"}}, "target": "createpanelrefs", "target_idx": 4}
{"id": "resource_bcftools_pluginfixploidy_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFIXPLOIDY", "tool": "bcftools/pluginfixploidy", "description": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFIXPLOIDY (The fixploidy plugin fixes ploidy in genotype fields according to specified ploi) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_expected_cells_0_12", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "noul_undeclared_process_file_inputs_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_anndata_barcodes_5", "category": "resource_profiling", "state": {"process": "ANNDATA_BARCODES", "tool": "anndata/barcodes", "description": "Module to subset AnnData object to cells with matching barcodes from the csv file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_BARCODES (Module to subset AnnData object to cells with matching barcodes from the csv fil) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_atlas_splitmerge_0", "category": "resource_profiling", "state": {"process": "ATLAS_SPLITMERGE", "tool": "atlas/splitmerge", "description": "split single end read groups by length and merge paired end reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_SPLITMERGE (split single end read groups by length and merge paired end reads) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_hmmer_hmmbuild_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: create an hmm profile from a multiple sequence alignment (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macsyfinder/search": "Search for macromolecular systems in protein datasets using MacSyFinder", "entrezdirect/xtract": "Queries an NCBI database using an UID", "motus/preplong": "Taxonomic meta-omics profiling using universal marker genes", "hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "hmmer/hmmbuild", "target_idx": 3}
{"id": "noul_default_empty_channel_behavior_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_unzipfiles_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unzip ZIP archive files (tools: unzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunzip": null, "rustqc": null, "zip": null, "bbmap/sendsketch": null, "unzipfiles": null}}, "target": "unzipfiles", "target_idx": 4}
{"id": "mod_gatk4_mergebamalignment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge unmapped with mapped BAM files (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_phylogenomics": null, "picard_positionbaseddownsamplesam": null, "fusionreport_detect": null, "gatk4_mergebamalignment": null, "amps": null}}, "target": "gatk4_mergebamalignment", "target_idx": 3}
{"id": "mod_macs3_callpeak_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments (tools: macs3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macs3_callpeak": null, "chromap_index": null, "salsa2": null, "bwa_mem": null, "alignoth": null}}, "target": "macs3_callpeak", "target_idx": 0}
{"id": "schema_std_nanostring_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanostring", "assay": "nanostring pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/nanostring (An analysis pipeline for Nanostring nCounter expression data)?", "criteria": {"SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_39", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_dedup_bwamem_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BWAMEM", "modules": ["parabricks/fq2bam", "samtools/index", "picard/addorreplacereadgroups", "picard/markduplicates", "bam_sort_stats_samtools", "fastq_align_bwa"], "description": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BWAMEM (parabricks/fq2bam, samtools/index, picard/addorreplacereadgroups, picard/markduplicates, bam_sort_stats_samtools, fastq_align_bwa) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_DEDUP_BWAMEM": null, "Use nf-core subworkflow fastq_align_dedup_bwamem": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwamem", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/bacass) for Hybrid bacterial assembly combining short Illumina and long Nanopore reads. Input files: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate.", "question": {"type": "choice", "instructions": "Which columns are standard for Hybrid bacterial assembly combining short Illumina and long Nanopore reads input samplesheet?", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_1_2", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status", "pipeline": "nf-core/eager"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_delly_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call structural variants (tools: delly)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"delly_call": null, "metator_pipeline": null, "abyss_abysspe": null, "agat_convertspgff2tsv": null, "pharokka_installdatabases": null}}, "target": "delly_call", "target_idx": 0}
{"id": "mod_mmseqs_fasta_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file. (tools: mmseqs_fasta_cluster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "windowmasker/convert": "Masks out highly repetitive DNA sequences with low complexity in a genome", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "mmseqs_fasta_cluster": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file.", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}}, "target": "mmseqs_fasta_cluster", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_19", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_vclust_prefilter_align_cluster_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER", "modules": ["vclust/prefilter", "vclust/align", "vclust/cluster"], "description": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter"}, "question": {"type": "choice", "instructions": "How should FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER (vclust/prefilter, vclust/align, vclust/cluster) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster": null, "Local subworkflow FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster", "target_idx": 1}
{"id": "mod_fgumi_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts a SAM or BAM file. Several sort orders are available, including coordinate,\nqueryname, and template-coordinate. This is a high-performance replacement for fgbio SortBam. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plotsr": "Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes.", "csvtk_sort": "Sort  CSV (or TSV) tables", "trgt_plot": "Visualize tandem repeats genotyped by TRGT", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "fgumi_sort": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate,\nqueryname, and template-coor"}}, "target": "fgumi_sort", "target_idx": 4}
{"id": "field_constraint_status_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "mod_bwamem2_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA-mem2 index for reference genome (tools: bwamem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_step2": "Run REGENIE step 2 association testing from precomputed step 1 predictions", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "biscuit_index": "Indexes a reference genome for use with Biscuit", "bwamem2_index": "Create BWA-mem2 index for reference genome", "ltrretriever_ltrretriever": "Identifies LTR retrotransposons using LTR_retriever"}}, "target": "bwamem2_index", "target_idx": 3}
{"id": "mod_mmseqs_easysearch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Searches for the sequences of a fasta file in a database using MMseqs2 (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/easysearch": null, "mmseqs/createindex": null, "mmseqs/createdb": null, "pairtools/select": null, "samtools/flagstat": null}}, "target": "mmseqs/easysearch", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Xenium in situ subcellular spatial RNA transcriptomics. Input files: Xenium output bundle with transcripts CSV, cell polygons, and morphology images.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Xenium in situ subcellular spatial RNA transcriptomics with entry step INPUT_CHECK.", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "noul_module_metadata_propagation_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Tumor-only somatic variant calling without matched normal)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,normal,tumor": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_42", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_all101_variantprioritization_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR).. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": null, "circdna": null, "phaseimpute": null, "createpanelrefs": null, "variantprioritization": null, "nascent": null, "bamtofastq": null, "mnaseseq": null, "createtaxdb": null, "rnavar": null}}, "target": "variantprioritization", "target_idx": 4}
{"id": "field_constraint_fastq_1_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: integer": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "mod_slamdunk_map_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings. (tools: slamdunk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"slamdunk/map": "Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings.", "disambiguate": "Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ fi", "arriba/visualisation": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "pear": "PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger.", "saltshaker/plot": "mtDNA deletion and duplication plotting downstream of mitosalt"}}, "target": "slamdunk/map", "target_idx": 0}
{"id": "mod_kallisto_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create kallisto index (tools: kallisto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_isec": "Apply set operations to VCF files", "pirate": "Pangenome toolbox for bacterial genomes", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "kallistobustools_ref": "index creation for kb count quantification of single-cell data.", "kallisto_index": "Create kallisto index"}}, "target": "kallisto_index", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_0_37", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_biscuit_align_2", "category": "resource_profiling", "state": {"process": "BISCUIT_ALIGN", "tool": "biscuit/align", "description": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_ALIGN (Aligns single- or paired-end reads from bisulfite-converted libraries to a refer) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_modkit_callmods_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call mods from a modbam, creates a new modbam with probabilities set to 100% if a base modification is called or 0% if called canonical (tools: modkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_report": "Collects bismark alignment reports", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "hmmer_eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie", "riker_multi": "Run multiple riker collectors in a single BAM pass using riker multi. Specify\ntools via ext.args (e.g. '--tool", "modkit_callmods": "Call mods from a modbam, creates a new modbam with probabilities set to 100% if a base modification is called "}}, "target": "modkit_callmods", "target_idx": 4}
{"id": "field_constraint_bai_1_10", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "resource_ampcombi_1", "category": "resource_profiling", "state": {"process": "AMPCOMBI", "tool": "ampcombi", "description": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI (A tool to parse and summarise results from antimicrobial peptides tools and pres) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_pathogensurveillance_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Surveillance of pathogens using population genomics and sequencing. Topics: biosurveillance, pathogen-identification. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": null, "pathogensurveillance": null, "detaxizer": null, "nanostring": null, "bactmap": null}}, "target": "pathogensurveillance", "target_idx": 1}
{"id": "mod_topas_gencons_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage present in ancient DNA (tools: topas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_consensus": "Compresses VCF files", "gecco_run": "GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomi", "sexdeterrmine": "Calculate the relative coverage on the Gonosomes vs Autosomes from the output of samtools depth, with error ba", "topas_gencons": "Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage presen", "bismark_methylationextractor": "Extracts methylation information for individual cytosines from alignments."}}, "target": "topas_gencons", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_4_1", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired FASTQs for both GEX and ATAC modalities per nucleus?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,bam": null, "sample,rna_fastq,atac_fastq": null, "sample,matrix": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "mod_foldcomp_compress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Efficient compression tool for protein structures (tools: foldcomp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldcomp/compress": "Efficient compression tool for protein structures", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "blast/blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "deeptmhmm": "A Deep Learning Model for Transmembrane Topology Prediction and Classification"}}, "target": "foldcomp/compress", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_qc_stats_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_STATS", "modules": ["fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp"], "description": "Generate statistics for short read sequencing data using multiple tools"}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_STATS (fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_QC_STATS": null, "Use nf-core subworkflow fastq_qc_stats": null}}, "target": "Use nf-core subworkflow fastq_qc_stats", "target_idx": 3}
{"id": "mod_gawk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: If you are like many computer users, you would frequently like to make changes in various text files\nwherever certain patterns appear, or extract data from parts of certain lines while discarding the rest.\nThe job is easy with awk, especially the GNU implementation gawk. (tools: gawk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"oarfish/alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "seqkit/tab2fx": "Convert tabular format (first two/three columns) to FASTA/Q format.", "gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever ", "jvarkit/vcf2table": "Convert VCF to a user friendly table", "savana/to": "Tumour-only somatic SV calling with optional copy-number analysis in SAVANA"}}, "target": "gawk", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_0_1", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bcftools_pluginscatter_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSCATTER", "tool": "bcftools/pluginscatter", "description": "Split VCF by chunks or regions, creating multiple VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSCATTER (Split VCF by chunks or regions, creating multiple VCFs.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_7_0", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_gapseq_find_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict metabolic pathways from genomic data using gapseq (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spmergeannotations": null, "agat_spextractsequences": null, "gapseq_find": null, "bam_variant_calling_mpileup_bcftools": null, "lofreq_filter": null}}, "target": "gapseq_find", "target_idx": 2}
{"id": "resource_bwamem2_index_0", "category": "resource_profiling", "state": {"process": "BWAMEM2_INDEX", "tool": "bwamem2/index", "description": "Create BWA-mem2 index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAMEM2_INDEX (Create BWA-mem2 index for reference genome) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_high", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_2", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "pipe_all101_stableexpression_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). The ideal use case is for determining the most suitable RT-qPCR reference genes for a given species.. Topics: expression, housekeeping-genes, qpcr-analysis. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]"}}, "target": "stableexpression", "target_idx": 0}
{"id": "mod_salmon_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create index for salmon (tools: salmon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_mpileup": "Generate text pileup output for one or multiple BAM files. Each input file produces a separate group of pileup", "diamond_deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "bowtie_build": "Create bowtie index for reference genome", "salmon_index": "Create index for salmon"}}, "target": "salmon_index", "target_idx": 4}
{"id": "mod_suppa_generateevents_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates alternative splicing events from a GTF file using SUPPA. (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa/generateevents": "Generates alternative splicing events from a GTF file using SUPPA.", "suppa/psiperisoform": "Calculate PSI values for transcript isoforms using SUPPA", "diamond/blastp": "Queries a DIAMOND database using blastp mode", "longstitch": "\"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - ", "misopy/index": "Build an indexed representation of a GFF for efficient retrieval of genes"}}, "target": "suppa/generateevents", "target_idx": 0}
{"id": "schema_std_raredisease_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/raredisease. Description: Call and score variants from WGS/WES of rare disease patients..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/raredisease.", "criteria": {"sample,fastq_1,fastq_2,bam,bai": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,strandedness,type": null, "id,fasta,query": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 0}
{"id": "noul_workflow_completion_lifecycle_hook_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_taxonkit_list_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate taxonomic subtrees based on taxonids (tools: taxonkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"taxonkit/list": "Generate taxonomic subtrees based on taxonids", "ganon/table": "Generate a multi-sample report file from the output of ganon report runs", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "liftoff": "Uses Liftoff to accurately map annotations in GFF or GTF between assemblies of the same,\nor closely-related sp", "gatk4/splitcram": "Splits CRAM files efficiently by taking advantage of their container based structure"}}, "target": "taxonkit/list", "target_idx": 0}
{"id": "field_constraint_sample_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"enum: [0, 1]": null, "format: file-path": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "mod_fastq_ngscheckmate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs. (tools: fastq_ngscheckmate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_ngscheckmate": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set", "fargene": "tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full", "medaka": "A tool to create consensus sequences and variant calls from nanopore sequencing data", "ngscheckmate/vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "bam_ngscheckmate": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set o"}}, "target": "fastq_ngscheckmate", "target_idx": 0}
{"id": "field_constraint_sex_1_1", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "local_subworkflow_prepilluminareads_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should this step (trimmomatic) be packaged: Single-step adapter trimming for Illumina reads?", "criteria": {"Local subworkflow PREPILLUMINAREADS": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 0}
{"id": "field_constraint_strandedness_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"pattern: ^[0-9]+$": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_pretextsnapshot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to generate images from Pretext contact maps. (tools: pretextsnapshot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "pretextsnapshot": "A module to generate images from Pretext contact maps.", "paftools_sam2paf": "A program to convert bam into paf.", "cooler_merge": "Merge multiple coolers with identical axes", "fusionreport_download": "Build DB for fusionreport"}}, "target": "pretextsnapshot", "target_idx": 1}
{"id": "resource_bcftools_concat_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONCAT", "tool": "bcftools/concat", "description": "Concatenate VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONCAT (Concatenate VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_core10_sarek_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Whole-genome sequencing for germline variant calling with GATK HaplotypeCaller, DeepVariant, and Strelka2.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"viralrecon": null, "rnaseq": null, "eager": null, "sarek": null, "chipseq": null, "mag": null, "ampliseq": null, "taxprofiler": null, "scrnaseq": null, "atacseq": null}}, "target": "sarek", "target_idx": 3}
{"id": "mod_abra2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembly Based ReAligner for next-generation sequencing data (tools: abra2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging/macsima2mc": "Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO.", "gatk4/reblockgvcf": "Condenses homRef blocks in a single-sample GVCF", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "abra2", "target_idx": 2}
{"id": "mod_sentieon_rsemcalculateexpression_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate expression with RSEM (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "custom/rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "sentieon/rsemcalculateexpression": "Calculate expression with RSEM", "tabix/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files", "rsem/preparereference": "Prepare a reference genome for RSEM"}}, "target": "sentieon/rsemcalculateexpression", "target_idx": 2}
{"id": "noul_file_pairing_in_channel_tuples_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_1_4", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bam": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_32", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_ivar_consensus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a consensus sequence from a BAM file using iVar (tools: ivar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ivar_consensus": "Generate a consensus sequence from a BAM file using iVar", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "pyrodigal": "Pyrodigal is a Python module that provides bindings to Prodigal, a fast, reliable protein-coding gene predicti", "ivar_variants": "Call variants from a BAM file using iVar", "glimpse_ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information."}}, "target": "ivar_consensus", "target_idx": 0}
{"id": "mod_plink_missing_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute sample-based and variant-based missing genotype rates and write a new PLINK binary fileset (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "plink/bmerge": "Merge a second PLINK binary fileset into the first and write a new combined PLINK binary fileset", "plink/bcf": "Analyses binary variant call format (BCF) files using plink", "motus/downloaddb": "Download the mOTUs database", "plink/missing": "Compute sample-based and variant-based missing genotype rates and write a new PLINK binary fileset"}}, "target": "plink/missing", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_0_37", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "field_constraint_expected_cells_1_4", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_5_3", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: Fungal ITS1/ITS2 marker gene amplicon surveillance.", "criteria": {"sample,unite_fasta": null, "sample,primer_its1,primer_its2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_phenotype_0_5", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_46", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_17", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_ska_distance_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairwise distances and basic clustering from SKA sketches (tools: ska)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "alignoth": "Creating alignment plots from bam files", "ska_distance": "Calculate pairwise distances and basic clustering from SKA sketches", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "seqkit_stats": "simple statistics of FASTA/Q files"}}, "target": "ska_distance", "target_idx": 2}
{"id": "mod_fasta_bgzip_index_dict_samtools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA file. (tools: fasta_bgzip_index_dict_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trust4": "Run TRUST4 on RNA-seq data", "htslib/bgziptabix": "Multi-purpose module to compress, decompress and index files using bgzip and tabix.", "imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op", "samtools/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "fasta_bgzip_index_dict_samtools": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA f"}}, "target": "fasta_bgzip_index_dict_samtools", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_2_4", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_channel_collect_operator_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay_type": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "data_format": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end low-input fragment FASTQs with target antibody and IgG negative control?", "criteria": {"sample,spikein,fastq": null, "sample,bam": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "mod_blast_blastdbcmd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Retrieve entries from a BLAST database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package", "pairtools/sort": "Sort a .pairs/.pairsam file", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "blast/blastdbcmd": "Retrieve entries from a BLAST database"}}, "target": "blast/blastdbcmd", "target_idx": 4}
{"id": "pipe_all101_genomeassembler_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads. Topics: genome-assembly. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants"}}, "target": "genomeassembler", "target_idx": 1}
{"id": "resource_bftools_showinf_4", "category": "resource_profiling", "state": {"process": "BFTOOLS_SHOWINF", "tool": "bftools/showinf", "description": "Extract OME xml data from OME-tif"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFTOOLS_SHOWINF (Extract OME xml data from OME-tif) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_3_2", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ATAC-seq chromatin accessibility with biological replicates with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "resource_blast_blastdbcmd_2", "category": "resource_profiling", "state": {"process": "BLAST_BLASTDBCMD", "tool": "blast/blastdbcmd", "description": "Retrieve entries from a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTDBCMD (Retrieve entries from a BLAST database) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_6_5", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns are standard for Hi-C chromosome conformation capture mapping input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bed": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_deeptools_bamcoverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig or bedGraph) as output. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_index": null, "lofreq_call": null, "allelecounter": null, "cmseq_polymut": null, "deeptools_bamcoverage": null}}, "target": "deeptools_bamcoverage", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_2_37", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_vclust_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Vclust cluster performs threshold-based clustering by assigning a genome sequence to a cluster if its similarity (e.g., ANI) to the cluster meets or exceeds a user-defined threshold. (tools: vclust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"knotannotsv": "Simple tool to create a customizable html file (to be displayed on a web browser) from an AnnotSV output", "vclust_cluster": "Vclust cluster performs threshold-based clustering by assigning a genome sequence to a cluster if its similari", "ribotish_quality": "Quality control of riboseq bam data", "cdhit_cdhitest": "Cluster nucleotide sequences using sequence similarity", "cdhit_cdhit": "Cluster protein sequences using sequence similarity"}}, "target": "vclust_cluster", "target_idx": 1}
{"id": "subworkflow_pkg_opt_flip_track_stat_3", "category": "subworkflow_packaging", "state": {"subworkflow": "OPT_FLIP_TRACK_STAT", "modules": ["opt/flip", "opt/track", "opt/stat"], "description": "Off-target probe detection"}, "question": {"type": "choice", "instructions": "How should OPT_FLIP_TRACK_STAT (opt/flip, opt/track, opt/stat) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow OPT_FLIP_TRACK_STAT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow opt_flip_track_stat": null}}, "target": "Use nf-core subworkflow opt_flip_track_stat", "target_idx": 3}
{"id": "resource_bcl2fastq_1", "category": "resource_profiling", "state": {"process": "BCL2FASTQ", "tool": "bcl2fastq", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCL2FASTQ (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_2_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "samplesheet_arch_pediatric_trio_somatic_0_2", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bedtools_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts a feature file by chromosome and other criteria. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "ucsc_bigwigaverageoverbed": "compute average score of bigwig over bed file", "bedtools_sort": "Sorts a feature file by chromosome and other criteria.", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "fcsgx_cleangenome": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome asse"}}, "target": "bedtools_sort", "target_idx": 2}
{"id": "mod_pbtk_pbmerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simple tool which merges several PacBio BAM files together (tools: pbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"graphmap2_index": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt", "pbtk_pbmerge": "Simple tool which merges several PacBio BAM files together", "pbbam_pbmerge": "The pbbam software package provides components to create, query, & edit PacBio BAM files and associated indice"}}, "target": "pbtk_pbmerge", "target_idx": 3}
{"id": "mod_pygenprop_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a Micromeda file containing pathway annotations for one or more genomes.\nSupporting InterProScan and protein sequence information can also be optionally incorporated. (tools: pygenprop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_clean_fcs": "Foreign Contamination Screen (FCS) is a tool suite for identifying and removing contaminant sequences in genom", "pygenprop/build": "Generate a Micromeda file containing pathway annotations for one or more genomes.\nSupporting InterProScan and ", "slamdunk/all": "Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification", "pygenprop/info": "Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assign", "eggnogmapper": "Fast genome-wide functional annotation through orthology assignment."}}, "target": "pygenprop/build", "target_idx": 1}
{"id": "noul_process_conditional_execution_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "schema_std_callingcards_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/callingcards", "description": "A pipeline for processing calling cards data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/callingcards?", "criteria": {"sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,barcode_details": null, "sample,fastq_1,fastq_2,strandedness,type": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null}}, "target": "sample,fastq_1,fastq_2,barcode_details", "target_idx": 1}
{"id": "subworkflow_pkg_deepvariant_0", "category": "subworkflow_packaging", "state": {"subworkflow": "DEEPVARIANT", "modules": ["deepvariant/makeexamples", "deepvariant/callvariants", "deepvariant/postprocessvariants"], "description": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data"}, "question": {"type": "choice", "instructions": "How should DEEPVARIANT (deepvariant/makeexamples, deepvariant/callvariants, deepvariant/postprocessvariants) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow DEEPVARIANT": null, "Use nf-core subworkflow deepvariant": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow deepvariant", "target_idx": 2}
{"id": "mod_agrvate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rapid identification of Staphylococcus aureus agr locus type and agr operon variants (tools: agrvate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "biohansel": "Use k-mers to rapidly subtype S. enterica genomes", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "agrvate", "target_idx": 2}
{"id": "mod_picard_createsequencedictionary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a sequence dictionary for a reference sequence. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra/align": null, "blat": null, "agat/spextractsequences": null, "viennarna/rnalfold": null, "picard/createsequencedictionary": null}}, "target": "picard/createsequencedictionary", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_index_methylseq_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_METHYLSEQ", "modules": ["untar", "gunzip", "bismark/genomepreparation", "bwameth/index", "bwa/index", "samtools/faidx"], "description": "Generate index files from reference fasta for bismark, bwameth and bwamem aligners"}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_METHYLSEQ (untar, gunzip, bismark/genomepreparation, bwameth/index, bwa/index, samtools/faidx) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTA_INDEX_METHYLSEQ": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_index_methylseq": null}}, "target": "Use nf-core subworkflow fasta_index_methylseq", "target_idx": 3}
{"id": "resource_bedtools_merge_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MERGE", "tool": "bedtools/merge", "description": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MERGE (combines overlapping or “book-ended” features in an interval file into a single ) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_amulety_antiberty_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi", "saltshaker_plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "amulety_antiberty": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety.", "amulety_embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "busco_busco": "Benchmarking Universal Single Copy Orthologs"}}, "target": "amulety_antiberty", "target_idx": 2}
{"id": "schema_std_bacmodel_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacmodel", "description": "Systems-based bacterial functional modeling pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/bacmodel?", "criteria": {"id,fasta": null, "sample,fastq_1,fastq_2,batch,condition": null, "id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "core_tool_multiqc_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Aggregate and summarize quality control metrics and analysis logs across FastQC, Cutadapt, and STAR into a single interactive HTML report.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"fastp": null, "trimmomatic": null, "picard": null, "multiqc": null, "fastqc": null}}, "target": "multiqc", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_3_1", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Standard Paired-end Whole Genome Sequencing (WGS) with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "intent_prepare_data_1", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "build_pipeline": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_2_5", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_deeptools_multibamsummary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes read coverage for genomic regions (bins) across the entire genome. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "methurator_gtestimator": "Run estimator for DNA methylation sequencing saturation.", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "fastq_decontaminate_deacon_hostile": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile", "deeptools_multibamsummary": "Computes read coverage for genomic regions (bins) across the entire genome."}}, "target": "deeptools_multibamsummary", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_1_4", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_star_indexversion_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Get the minimal allowed index version from STAR (tools: star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star_indexversion": "Get the minimal allowed index version from STAR", "leafcutter_clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "lsa_cosine": "Calculates the cosine similarity matrix between samples based on a gene expression matrix.", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}}, "target": "star_indexversion", "target_idx": 0}
{"id": "local_subworkflow_irma_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for IRMA (irma).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow IRMA": null, "Use nf-core subworkflow irma": null}}, "target": "Local subworkflow IRMA", "target_idx": 2}
{"id": "pipe_all101_phyloplace_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for evolution analysis? Specific context: nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.. Topics: evolution, evolutionary-tree, phylogenetic-placement, phylogenetics, sequence-classification, taxonomy-assignment. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "metapep": "From metagenomes to epitopes and beyond", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]"}}, "target": "phyloplace", "target_idx": 4}
{"id": "mod_emu_abundance_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A taxonomic profiler for metagenomic 16S data optimized for error prone long reads. (tools: emu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"emu_abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads.", "irescue": "Quantification of transposable elements expression in scRNA-seq", "sratools_fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA).", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken."}}, "target": "emu_abundance", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_39", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_4_4", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Raw paired-end Illumina WGS FASTQs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_impute_beagle5_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_BEAGLE5", "modules": ["beagle5/beagle", "bcftools/index", "bcftools/view", "glimpse2/ligate"], "description": "Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_BEAGLE5 (beagle5/beagle, bcftools/index, bcftools/view, glimpse2/ligate) be structured in DSL2?", "criteria": {"Local subworkflow VCF_IMPUTE_BEAGLE5": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow vcf_impute_beagle5": null}}, "target": "Use nf-core subworkflow vcf_impute_beagle5", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_47", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_bbmap_bbduk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adapter and quality trimming of sequencing reads (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_taps_conversion": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis", "bbmap_bbduk": "Adapter and quality trimming of sequencing reads", "cutadapt": "Removes adapter sequences from sequencing reads", "chopper": "Filter and trim long read data.", "fastq_removeadapters_merge": "Remove adapters and merge reads based on various module choices"}}, "target": "bbmap_bbduk", "target_idx": 1}
{"id": "mod_amulety_balmpaired_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq_requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "amulety_antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety.", "custom_pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi", "angsd_soapsnpcalibration": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments.", "amulety_balmpaired": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}}, "target": "amulety_balmpaired", "target_idx": 4}
{"id": "resource_bcftools_pluginfixploidy_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFIXPLOIDY", "tool": "bcftools/pluginfixploidy", "description": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFIXPLOIDY (The fixploidy plugin fixes ploidy in genotype fields according to specified ploi) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_chromap_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_CHROMAP", "modules": ["chromap/chromap", "picard/addorreplacereadgroups", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_CHROMAP (chromap/chromap, picard/addorreplacereadgroups, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_chromap": null, "Local subworkflow FASTQ_ALIGN_CHROMAP": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_chromap", "target_idx": 0}
{"id": "subworkflow_pkg_bam_vcf_impute_glimpse2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VCF_IMPUTE_GLIMPSE2", "modules": ["glimpse2/chunk", "glimpse2/phase", "glimpse2/ligate", "glimpse2/splitreference", "bcftools/index"], "description": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should BAM_VCF_IMPUTE_GLIMPSE2 (glimpse2/chunk, glimpse2/phase, glimpse2/ligate, glimpse2/splitreference, bcftools/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_vcf_impute_glimpse2": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_VCF_IMPUTE_GLIMPSE2": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_vcf_impute_glimpse2", "target_idx": 0}
{"id": "mod_fastq_align_star_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bowtie2 then sort with samtools (tools: fastq_align_star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "fastq_align_star": "Align reads to a reference genome using bowtie2 then sort with samtools", "shapeit5/phasecommon": "Tool to phase common sites, typically SNP array data, or the first step of WES/WGS data.", "repeatmodeler/builddatabase": "Create a database for RepeatModeler", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "fastq_align_star", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_diamond_blastp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a DIAMOND database using blastp mode (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "diamond_blastp": "Queries a DIAMOND database using blastp mode", "hmmcopy_readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows", "savana_classify": "Classify structural variants using SAVANA"}}, "target": "diamond_blastp", "target_idx": 2}
{"id": "schema_std_pacvar_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/pacvar. Description: Longread PacBio sequencing processing for WGS and PureTarget.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/pacvar.", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "family_id,sample,file_path,hpo_terms,sex": null, "sample,bam,pbi,fail,repeat_id": null, "id,fasta,query": null}}, "target": "sample,bam,pbi,fail,repeat_id", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_3_1", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral genome sequencing on Oxford Nanopore MinION / GridION with entry step NANOPLOT.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_3_1", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "template": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for PacBio HiFi unaligned BAM variant calling with entry step PBMM2_ALIGN.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "mod_macs3_callpeak_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments (tools: macs3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"viralconsensus": "Fast and memory-efficient viral consensus genome sequence generation from read alignments", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins", "macs3/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "busco/busco": "Benchmarking Universal Single Copy Orthologs", "alignoth": "Creating alignment plots from bam files"}}, "target": "macs3/callpeak", "target_idx": 2}
{"id": "mod_vg_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: vg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vg/index": null, "rsem/calculateexpression": null, "biscuit/qc": null, "opt/track": null, "bismark/genomepreparation": null}}, "target": "vg/index", "target_idx": 0}
{"id": "mod_utils_nextflow_pipeline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow with functionality that may be useful for any Nextflow pipeline (tools: utils_nextflow_pipeline)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nextflow_pipeline": "Subworkflow with functionality that may be useful for any Nextflow pipeline", "quantmsutils/dianncfg": "Generate DIA-NN configuration arguments from enzyme and Unimod modification parameters.\nThis module uses quant", "regenie/splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "star/indexversion": "Get the minimal allowed index version from STAR", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline"}}, "target": "utils_nextflow_pipeline", "target_idx": 0}
{"id": "schema_std_methylarray_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/methylarray. Description: Process methylation data from Illumina arrays. Pre-processing, quality checks, confounder check and DMPs (differentially methylated positions) and DMRs (differentially methylated regions). Optionally estimates cell type composition and adjusts data for it..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/methylarray.", "criteria": {"id,fasta,reference,optional_data,template": null, "sample,bam,pbi,fail,repeat_id": null, "sample_id,idat_red,idat_green,group": null, "vcf,fasta,genome,site,source": null}}, "target": "sample_id,idat_red,idat_green,group", "target_idx": 2}
{"id": "mod_gatk4spark_baserecalibrator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate recalibration table for Base Quality Score Recalibration (BQSR) (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4spark/baserecalibrator": null, "gatk4/gatherbqsrreports": null, "sentieon/qualcal": null, "metaphlan3/mergemetaphlantables": null, "upd": null}}, "target": "gatk4spark/baserecalibrator", "target_idx": 0}
{"id": "mod_fusionreport_detect_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fusionreport_detect (tools: fusionreport)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr/normalize": null, "fusionreport/detect": null, "krona/ktimporttaxonomy": null, "duphold": null, "purgedups/splitfa": null}}, "target": "fusionreport/detect", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bcftools_csq_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CSQ", "tool": "bcftools/csq", "description": "bcftools Haplotype-aware consequence caller"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CSQ (bcftools Haplotype-aware consequence caller) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_39", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_gatk4_mergemutectstats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges mutect2 stats generated on different intervals/regions (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_depth": "Computes the depth at each position or region.", "gem2_gemindexer": "Create a GEM index from a FASTA file", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "gatk4_mergemutectstats": "Merges mutect2 stats generated on different intervals/regions", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content"}}, "target": "gatk4_mergemutectstats", "target_idx": 3}
{"id": "mod_eggnogmapper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast genome-wide functional annotation through orthology assignment. (tools: eggnogmapper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa/samse": null, "agat/spfilterbyorfsize": null, "eggnogmapper": null, "atlasgeneannotationmanipulation/gtf2featureannotation": null, "bwameme/index": null}}, "target": "eggnogmapper", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_43", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "subworkflow_pkg_bam_variant_demix_boot_freyja_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_DEMIX_BOOT_FREYJA", "modules": ["freyja/variants", "freyja/demix", "freyja/update", "freyja/boot"], "description": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to the Hu-1 reference)"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_DEMIX_BOOT_FREYJA (freyja/variants, freyja/demix, freyja/update, freyja/boot) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VARIANT_DEMIX_BOOT_FREYJA": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_variant_demix_boot_freyja": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_variant_demix_boot_freyja", "target_idx": 2}
{"id": "resource_angsd_soapsnpcalibration_2", "category": "resource_profiling", "state": {"process": "ANGSD_SOAPSNPCALIBRATION", "tool": "angsd/soapsnpcalibration", "description": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_SOAPSNPCALIBRATION (Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality mat) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_spring_decompress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, efficient, lossless decompression of FASTQ files. (tools: spring)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"repeatmodeler/repeatmodeler": null, "art/illumina": null, "spring/decompress": null, "adapterremovalfixprefix": null, "last/split": null}}, "target": "spring/decompress", "target_idx": 2}
{"id": "noul_channel_collect_operator_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_1_3", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Small RNA / miRNA sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "samplesheet_arch_cancer_longitudinal_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Longitudinal cancer monitoring across multiple timepoints. Input files: Serial plasma cfDNA and biopsy FASTQs across treatment intervals.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Longitudinal cancer monitoring across multiple timepoints with entry step FASTQC.", "criteria": {"patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_agat_convertspgff2gtf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a GFF/GTF file into a proper GTF file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "bbmap/repair": "Re-pairs reads that became disordered or had some mates eliminated.", "rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome", "agat/convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}}, "target": "agat/convertspgff2gtf", "target_idx": 1}
{"id": "mod_yahs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs assembly scaffolding using YaHS (tools: yahs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "bcftools_merge": "Merge VCF files", "fastcov": "Generate a coverage plot from one or more bam files", "yahs": "Performs assembly scaffolding using YaHS", "ragtag_scaffold": "Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. G"}}, "target": "yahs", "target_idx": 3}
{"id": "mod_vcf2maf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: vcf2maf (tools: vcf2maf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf2maf": "vcf2maf", "bam_variant_calling_sort_freebayes_bcftools": "Call variants using freebayes, then sort and index", "cooler/dump": "Dump a cooler’s data to a text stream.", "bcftools/annotate": "Add or remove annotations.", "atlas/call": "generate VCF file from a BAM file using various calling methods"}}, "target": "vcf2maf", "target_idx": 0}
{"id": "mod_krona_ktimportkrona_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect multiple krona reports into a single html file (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldseek/easysearch": "Search for protein structural hits against a foldseek database of protein structures", "vembrane/sort": "Sort VCF/BCF files by custom Python expressions for variant prioritization", "krona/ktimporttaxonomy": "KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot.", "krona/ktimportkrona": "Collect multiple krona reports into a single html file", "deeptools/plotfingerprint": "plots cumulative reads coverages by BAM file"}}, "target": "krona/ktimportkrona", "target_idx": 3}
{"id": "field_constraint_bai_0_12", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_30", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_macse_refinealignment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: improves the input nucleotide alignment in a codon-aware manner (tools: macse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mafft_align": "Multiple sequence alignment using MAFFT", "emboss_cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "macse_refinealignment": "improves the input nucleotide alignment in a codon-aware manner", "suppa_psiperevent": "Calculate PSI values for alternative splicing events using SUPPA", "metaeuk_easypredict": "Annotation of eukaryotic metagenomes using MetaEuk"}}, "target": "macse_refinealignment", "target_idx": 2}
{"id": "mod_mash_screen_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Screens query sequences against large sequence databases (tools: mash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctree": "Clone trees for Cancer Evolution studies from bulk sequencing data.", "mash/screen": "Screens query sequences against large sequence databases", "kleborate": "Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "staphscan": "staphscan is a tool to screen genome assemblies of Staphylococcus aureus"}}, "target": "mash/screen", "target_idx": 1}
{"id": "mod_metabat2_jgisummarizebamcontigdepths_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Depth computation per contig step of metabat2 (tools: metabat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metabat2_jgisummarizebamcontigdepths": null, "diamond_blastx": null, "clame": null, "hmmer_eslalipid": null, "csvtk_sort": null}}, "target": "metabat2_jgisummarizebamcontigdepths", "target_idx": 0}
{"id": "mod_seqfu_derep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in the sequence header. Can dereplicate already dereplicated FASTA files, summing the numbers found in the headers. (tools: seqfu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqfu/derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th", "diamond/makedb": "Builds a DIAMOND database", "happy/happy": "Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}}, "target": "seqfu/derep", "target_idx": 0}
{"id": "mod_fast2q_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program that counts sequence occurrences in FASTQ files. (tools: 2FAST2Q)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "plink2/het": "Calculate Inbreeding data with plink2", "vcflib/vcfbreakmulti": "If multiple alleles are specified in a single record, break the record into several lines preserving allele-sp", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "fast2q": "A program that counts sequence occurrences in FASTQ files."}}, "target": "fast2q", "target_idx": 4}
{"id": "field_constraint_expected_cells_1_14", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "mod_instrain_profile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly accurate genome comparisons, analysis of coverage, microdiversity, and linkage, and sensitive SNP detection with gene localization and synonymous non-synonymous identification (tools: instrain)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "instrain/profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "bcftools/pluginfixploidy": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignmen", "idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}}, "target": "instrain/profile", "target_idx": 1}
{"id": "pipe_all101_marsseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for facs-sorting analysis? Specific context: MARS-seq v2 pre-processing pipeline with velocity. Topics: facs-sorting, mars-seq, single-cell, single-cell-rna-seq, star-solo, transcriptional-dynamics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "seqsubmit": "nf-core pipeline for data submission to ENA", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "marsseq", "target_idx": 3}
{"id": "mod_nanomonsv_get_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call somatic structural variants with nanomonsv get using tumor/control\nparse outputs and a reference genome. (tools: nanomonsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"geoquery_getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "nanomonsv_get": "Call somatic structural variants with nanomonsv get using tumor/control\nparse outputs and a reference genome.", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "seqfu_check": "Evaluates the integrity of DNA FASTQ files"}}, "target": "nanomonsv_get", "target_idx": 2}
{"id": "resource_bcftools_view_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_VIEW", "tool": "bcftools/view", "description": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_VIEW (View, subset and filter VCF or BCF files by position and filtering expression. C) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_4_2", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted CRAM alignments with companion CRAI indexes?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,cram,crai": null, "sample,cram": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "noul_executor_support_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_ask_question_15", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "ask_question": null, "debug_error": null}}, "target": "ask_question", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_21", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_megan_rma2info_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analyses an RMA file and exports information in text format (tools: megan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"megan_rma2info": null, "bbmap_sendsketch": null, "star_genomegenerate": null, "megan_daa2info": null, "skani_triangle": null}}, "target": "megan_rma2info", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_35", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_barrnap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: barrnap uses a hmmer profile to find rrnas in reads or contig fasta files (tools: barrnap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"barrnap": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files", "umitools/dedup": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "infernal/cmsearch": "Search covariance models against a sequence database", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "ferrohgvs/normalize": "Normalize HGVS variant descriptions to canonical form with ferro"}}, "target": "barrnap", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_28", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "field_constraint_sample_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"type: integer": null, "format: file-path": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_19", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_23", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_taxonkit_lineage_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert taxonids to taxon lineages (tools: taxonkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"taxonkit/lineage": "Convert taxonids to taxon lineages", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "fastq_qc_trim_filter_setstrandedness": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files,", "vrhyme/extractunbinned": "Extracting sequences that were unbinnned by vRhyme into a FASTA file", "ganon/classify": "Classify FASTQ files against ganon database"}}, "target": "taxonkit/lineage", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_18", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_modkit_bedmethyltobigwig_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a bedMethyl file to bigWig format using modkit (tools: modkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"famsa_align": "Aligns sequences using FAMSA", "sratools_prefetch": "Download sequencing data from the NCBI Sequence Read Archive (SRA).", "autocycler_cluster": "Cluster replicons in compressed assemblies with Autocycler.", "autocycler_combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "modkit_bedmethyltobigwig": "Convert a bedMethyl file to bigWig format using modkit"}}, "target": "modkit_bedmethyltobigwig", "target_idx": 4}
{"id": "pipe_all101_ribomsqc_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo"}}, "target": "ribomsqc", "target_idx": 2}
{"id": "mod_popscle_freemuxlet_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing and external genotyping data for each sample is not available. (tools: popscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "picard_mergesamfiles": "Merges multiple BAM files into a single file", "popscle_dscpileup": "Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode.", "rtgtools_vcfeval": "The VCFeval tool of RTG tools. It is used to evaluate called variants for agreement with a baseline variant se"}}, "target": "popscle_freemuxlet", "target_idx": 0}
{"id": "subworkflow_pkg_bam_vcf_impute_glimpse2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VCF_IMPUTE_GLIMPSE2", "modules": ["glimpse2/chunk", "glimpse2/phase", "glimpse2/ligate", "glimpse2/splitreference", "bcftools/index"], "description": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should BAM_VCF_IMPUTE_GLIMPSE2 (glimpse2/chunk, glimpse2/phase, glimpse2/ligate, glimpse2/splitreference, bcftools/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_vcf_impute_glimpse2": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_VCF_IMPUTE_GLIMPSE2": null}}, "target": "Use nf-core subworkflow bam_vcf_impute_glimpse2", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_29", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_5_1", "category": "samplesheet_schema", "state": "nextflow run custom/mira-nf --input samplesheet.csv (Assay: Custom MIRA-NF Influenza / SC2 pipeline)", "question": {"type": "choice", "instructions": "In Nextflow pipeline custom/mira-nf, determine the input samplesheet column structure for: Custom MIRA-NF Influenza / SC2 pipeline.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bcftools_pluginvcf2table_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINVCF2TABLE", "tool": "bcftools/pluginvcf2table", "description": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output as one row, with INFO and FORMAT fields as columns."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINVCF2TABLE (Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table ) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_cnvpytor_callcnvs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Command line tool for calling CNVs in whole genome sequencing data (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvnator_convert2vcf": null, "sentieon_varcal": null, "cnvpytor_callcnvs": null, "cnvkit_antitarget": null, "fgumi_downsample": null}}, "target": "cnvpytor_callcnvs", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_align_hisat2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_HISAT2", "modules": ["hisat2/align", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using hisat2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_HISAT2 (hisat2/align, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_hisat2": null, "Leave them out": null, "Local subworkflow FASTQ_ALIGN_HISAT2": null}}, "target": "Use nf-core subworkflow fastq_align_hisat2", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_18", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_4_4", "category": "samplesheet_schema", "state": {"technology": "Spatial In Situ", "workflow_entry": "INPUT_CHECK", "library_inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Xenium output bundle with transcripts CSV, cell polygons, and morphology images?", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "mod_rtgtools_bndeval_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND baseline variant set (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rtgtools/cnveval": "The cnveval tool of RTG tools. It is used to evaluate called CNV regions for agreement with a baseline CNV set", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "sentieon/dnascope": "DNAscope algorithm performs an improved version of Haplotype variant calling.", "rtgtools/bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "peddy": "Manipulation, validation and exploration of pedigrees"}}, "target": "rtgtools/bndeval", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_18", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_blast_updateblastdb_0", "category": "resource_profiling", "state": {"process": "BLAST_UPDATEBLASTDB", "tool": "blast/updateblastdb", "description": "Downloads a BLAST database from NCBI"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_UPDATEBLASTDB (Downloads a BLAST database from NCBI) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_custom_sratoolsncbisettings_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Test for the presence of suitable NCBI settings or create them on the fly. (tools: sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"zip": null, "entrezdirect/esearch": null, "fgumi/extract": null, "fcsgx/fetchdb": null, "custom/sratoolsncbisettings": null}}, "target": "custom/sratoolsncbisettings", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_1_33", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_28", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_42", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_cooler_zoomify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a multi-resolution cooler file by coarsening (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler/digest": null, "cooltools/insulation": null, "bcftools/pluginscatter": null, "crumble": null, "cooler/zoomify": null}}, "target": "cooler/zoomify", "target_idx": 4}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_fastq_2_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "mod_idr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate) (tools: idr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode/ribocode": "Call ORFs with RiboCode from Ribo-Seq data", "fusionreport/download": "Build DB for fusionreport", "homer/findpeaks": "Find peaks with HOMER suite", "homer/maketagdirectory": "Create a tag directory with the HOMER suite", "idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)"}}, "target": "idr", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_0_36", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_module_metadata_propagation_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_genescopefk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A derivative of GenomeScope2.0 modified to work with FastK (tools: genescopefk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"echtvar_encode": "Make (encode) a new echtvar file from decomposed vcf", "ganon_buildcustom": "Build ganon database using custom reference sequences.", "fgumi_duplex": "Calls duplex consensus sequences from reads generated from the same double-stranded\nsource molecule. This is a", "fastk_merge": "A tool to merge FastK histograms", "genescopefk": "A derivative of GenomeScope2.0 modified to work with FastK"}}, "target": "genescopefk", "target_idx": 4}
{"id": "resource_admixture_3", "category": "resource_profiling", "state": {"process": "ADMIXTURE", "tool": "admixture", "description": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datasets, where the individuals are unrelated (for example, the individuals in a case-control association study)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADMIXTURE (ADMIXTURE is a program for estimating ancestry in a model-based manner from larg) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_2", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_sambamba_markdup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: find and mark duplicate reads in BAM file (tools: sambamba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sambamba_markdup": null, "picard_markduplicates": null, "bcftools_rohviz": null, "dshbio_splitgff3": null, "biobambam_bammarkduplicates2": null}}, "target": "sambamba_markdup", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_23", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_18", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_viennarna_rnafold_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary structures and partition function of RNAs. (tools: viennarna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stranger": null, "sam2lca_analyze": null, "fusioncatcher_fusioncatcher": null, "viennarna_rnafold": null, "abra2": null}}, "target": "viennarna_rnafold", "target_idx": 3}
{"id": "resource_agat_spmergeannotations_0", "category": "resource_profiling", "state": {"process": "AGAT_SPMERGEANNOTATIONS", "tool": "agat/spmergeannotations", "description": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated names and fixes other oddities met in those files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPMERGEANNOTATIONS (This script merge different gff annotation files in one. It uses the AGAT parser) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_crisprseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/crisprseq. Description: A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`)..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/crisprseq.", "criteria": {"sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,strandedness": null, "sample_id,mapped,index,file_type": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,condition,reference", "target_idx": 0}
{"id": "schema_std_funcprofiler_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/funcprofiler", "description": "Read-based functional profiling of microbiome sequencing data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/funcprofiler?", "criteria": {"sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "id,raw_file": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "fastq_1,fastq_2,group,replicate,md5_1": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 2}
{"id": "mod_megan_daa2info_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Analyses a DAA file and exports information in text format (tools: megan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tidk/plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "diamond/blastp": "Queries a DIAMOND database using blastp mode", "megan/rma2info": "Analyses an RMA file and exports information in text format", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "megan/daa2info": "Analyses a DAA file and exports information in text format"}}, "target": "megan/daa2info", "target_idx": 4}
{"id": "samplesheet_arch_chipseq_with_control_4_0", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin", "pipeline": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads for immunoprecipitation and input chromatin?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_49", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_antismash_antismashdownloaddatabases_0", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHDOWNLOADDATABASES", "tool": "antismash/antismashdownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_decontaminate_deacon_hostile_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DECONTAMINATE_DEACON_HOSTILE", "modules": ["hostile/fetch", "hostile/clean", "deacon/index", "deacon/filter", "fastq_fetch_clean_hostile", "fastq_index_filter_deacon"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile"}, "question": {"type": "choice", "instructions": "How should FASTQ_DECONTAMINATE_DEACON_HOSTILE (hostile/fetch, hostile/clean, deacon/index, deacon/filter, fastq_fetch_clean_hostile, fastq_index_filter_deacon) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_decontaminate_deacon_hostile": null, "Leave them out": null, "Local subworkflow FASTQ_DECONTAMINATE_DEACON_HOSTILE": null}}, "target": "Use nf-core subworkflow fastq_decontaminate_deacon_hostile", "target_idx": 1}
{"id": "schema_std_pixelator_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pixelator", "description": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pixelator?", "criteria": {"sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "sample,fastq_1,fastq_2,pool,hash_index", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for 16S rRNA / ITS microbiome amplicon profiling. Input files: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs.", "question": {"type": "choice", "instructions": "Which columns are standard for 16S rRNA / ITS microbiome amplicon profiling input samplesheet?", "criteria": {"sample,otu_table": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_1_5", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "template": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_4_3", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates?", "criteria": {"sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bamstats_generalstats_1", "category": "resource_profiling", "state": {"process": "BAMSTATS_GENERALSTATS", "tool": "bamstats/generalstats", "description": "write your description here"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMSTATS_GENERALSTATS (write your description here) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/chipseq) for ChIP-seq with IP and input control design. Input files: Paired-end FASTQ reads for immunoprecipitation and input chromatin.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_13", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_controlfreec_makegraph_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot Freec output (tools: controlfreec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcl2fastq": "Demultiplex Illumina BCL files", "rgi_bwt": "Predict antibiotic resistance from protein or nucleotide data", "cnvnator_convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "controlfreec_makegraph": "Plot Freec output", "controlfreec_freec2bed": "Plot Freec output"}}, "target": "controlfreec_makegraph", "target_idx": 3}
{"id": "mod_wfmash_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a pangenome-scale aligner (tools: wfmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"differential_functional_enrichment": null, "seqkit/translate": null, "phyloflash": null, "wfmash": null, "somalier/ancestry": null}}, "target": "wfmash", "target_idx": 3}
{"id": "mod_hamronization_abricate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize ABRicate outputs using the hAMRonization specification (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/align": "Performs alignment of BS-Seq reads using bismark", "hamronization/fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever ", "hamronization/abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "hamronization/abricate", "target_idx": 3}
{"id": "mod_pbcpgtools_alignedbamtocpgscores_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts aligned BAM files into CpG methylation scores (tools: pbcpgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbcpgtools_alignedbamtocpgscores": "Converts aligned BAM files into CpG methylation scores", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bismark_report": "Collects bismark alignment reports", "mafft_align": "Multiple sequence alignment using MAFFT", "fastq_align_bwaaln": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed "}}, "target": "pbcpgtools_alignedbamtocpgscores", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq", "data_format": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_confusing_combine_with_mix_semantics_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_autocycler_compress_4", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMPRESS", "tool": "autocycler/compress", "description": "Package candidate assemblies for clustering by Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMPRESS (Package candidate assemblies for clustering by Autocycler.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bakta_bakta_5", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTA", "tool": "bakta/bakta", "description": "Annotation of bacterial genomes (isolates, MAGs) and plasmids"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTA (Annotation of bacterial genomes (isolates, MAGs) and plasmids) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_cutandrun_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/cutandrun. Description: Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/cutandrun.", "criteria": {"fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample_id,img_directory,parameter_file": null}}, "target": "fastq_1,fastq_2,group,replicate,control", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_5_2", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Trio exome/genome sequencing (Proband, Mother, Father).", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_44", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "noul_named_process_output_emits_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_freyja_boot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bootstrap sample demixing by resampling each site based on a multinomial distribution of read depth across all sites, where the event probabilities were determined by the fraction of the total sample reads found at each site, followed by a secondary resampling at each site according to a multinomial distribution (that is, binomial when there was only one SNV at a site), where event probabilities were determined by the frequencies of each base at the site, and the number of trials is given by the sequencing depth. (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "delly/call": "Call structural variants", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "svdb/query": "Query a structural variant database, using a vcf file as query", "freyja/boot": "Bootstrap sample demixing by resampling each site based on a multinomial distribution of read depth across all"}}, "target": "freyja/boot", "target_idx": 4}
{"id": "schema_std_longraredisease_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/longraredisease. Description: Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/longraredisease.", "criteria": {"family_id,sample,file_path,hpo_terms,sex": null, "id,path": null, "sample,bam,pbi,fail,repeat_id": null, "sample,bam,bai,cram,crai": null}}, "target": "family_id,sample,file_path,hpo_terms,sex", "target_idx": 0}
{"id": "samplesheet_arch_riboseq_profiling_0_0", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness", "pipeline": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,fastq_1,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "mod_humann3_regroup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Regrouping genes to other functional categories (tools: humann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribodetector": "Accurate and rapid RiboRNA sequences Detector based on deep learning", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "pharokka/pharokka": "Functional annotation of phages", "humann3/regroup": "Regrouping genes to other functional categories", "bam_impute_quilt": "Subworkflow to impute BAM files using QUILT software.\nVariants location to impute are obtain through the tsv f"}}, "target": "humann3/regroup", "target_idx": 3}
{"id": "pipe_all101_readsimulator_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data.. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": null, "eager": null, "proteinannotator": null, "rnadnavar": null, "nanoseq": null, "hicar": null, "raredisease": null, "metapep": null}}, "target": "readsimulator", "target_idx": 0}
{"id": "field_constraint_fastq_2_0_4", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "resource_abacas_5", "category": "resource_profiling", "state": {"process": "ABACAS", "tool": "abacas", "description": "Contiguate draft genome assembly"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABACAS (Contiguate draft genome assembly) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_6_0", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns are standard for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) input samplesheet?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_gatk4_baserecalibrator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate recalibration table for Base Quality Score Recalibration (BQSR) (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "sentieon_qualcal": "Generate recalibration table and optionally perform base quality recalibration", "kalign_align": "Aligns sequences using kalign", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "kma_index": "This module wraps the index module of the KMA alignment tool."}}, "target": "gatk4_baserecalibrator", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_32", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_44", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_cutandrun_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "description": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/cutandrun?", "criteria": {"sample,group,path,ref,method": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample_id,mapped,index,file_type": null}}, "target": "fastq_1,fastq_2,group,replicate,control", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_extract_relate_somalier_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_EXTRACT_RELATE_SOMALIER", "modules": ["htslib/bgziptabix", "somalier/extract", "somalier/relate"], "description": "Perform somalier extraction and relate stats on input VCFs"}, "question": {"type": "choice", "instructions": "How should VCF_EXTRACT_RELATE_SOMALIER (htslib/bgziptabix, somalier/extract, somalier/relate) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_extract_relate_somalier": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow VCF_EXTRACT_RELATE_SOMALIER": null}}, "target": "Use nf-core subworkflow vcf_extract_relate_somalier", "target_idx": 0}
{"id": "noul_channel_filter_operator_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_gatk4_gatherbqsrreports_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gathers scattered BQSR recalibration reports into a single file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/datametrics": "Collects multiple quality metrics from a bam file", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "htsnimtools/vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "gatk4/gatherbqsrreports": "Gathers scattered BQSR recalibration reports into a single file", "sentieon/qualcal": "Generate recalibration table and optionally perform base quality recalibration"}}, "target": "gatk4/gatherbqsrreports", "target_idx": 3}
{"id": "samplesheet_arch_cutandrun_pe_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cutandrun) for CUT&RUN / CUT&TAG chromatin profiling with IgG control. Input files: Paired-end low-input fragment FASTQs with target antibody and IgG negative control.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "field_constraint_strandedness_0_7", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null, "format: file-path": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "core_tool_featurecounts_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Assign and quantify mapped reads to genomic features such as exons, genes, and promoter annotations from sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"salmon": "Transcript quantifier", "kallisto": "RNA quantification", "stringtie": "Transcript assembly", "featurecounts": "Assign sequence reads to genomic features (genes, exons, promoters)", "htseq": "High-throughput sequencing analysis"}}, "target": "featurecounts", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_6", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/cutandrun --input samplesheet.csv (Assay: CUT&RUN / CUT&TAG chromatin profiling with IgG control)", "question": {"type": "choice", "instructions": "Which columns are standard for CUT&RUN / CUT&TAG chromatin profiling with IgG control input samplesheet?", "criteria": {"sample,spikein,fastq": null, "sample,fastq_1,fastq_2": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "resource_bcftools_consensus_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONSENSUS", "tool": "bcftools/consensus", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONSENSUS (Compresses VCF files) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_vcf_annotation_pipeline_2_0", "category": "samplesheet_schema", "state": {"technology": "Variant Annotation", "workflow_entry": "ENSEMBLVEP", "library_inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_22", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_rnasplice_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis. Topics: alternative-splicing, rna, rna-seq, splicing. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"smrnaseq": null, "rnastructurome": null, "scrnaseq": null, "rnasplice": null, "metaboigniter": null}}, "target": "rnasplice", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_1_26", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_purecn_intervalfile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate on and off-target intervals for PureCN from a list of targets (tools: purecn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purecn/run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "gtdbtk/gtdbtoncbimajorityvote": "Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy", "purecn/coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI", "gridss/annotate": "Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmaske", "purecn/intervalfile": "Generate on and off-target intervals for PureCN from a list of targets"}}, "target": "purecn/intervalfile", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_1_20", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_biobambam_bammerge_2", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMERGE", "tool": "biobambam/bammerge", "description": "Merge a list of sorted bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMERGE (Merge a list of sorted bam files) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_pharmcat_vcfpreprocessor_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The PharmCAT VCF Preprocessor is a script that can pre-process VCF files for PharmCAT to make sure the VCF file complies with PharmCAT's VCF Requirements (tools: pharmcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"numorph/3dunet": null, "leehom": null, "wget": null, "pharmcat/vcfpreprocessor": null, "scanpy/filter": null}}, "target": "pharmcat/vcfpreprocessor", "target_idx": 3}
{"id": "intent_debug_error_11", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "build_pipeline": null, "debug_error": null}}, "target": "debug_error", "target_idx": 3}
{"id": "mod_epang_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: splits an alignment into reference and query parts (tools: epang)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm", "epang/split": "splits an alignment into reference and query parts", "concoct/cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "epang/place": "phylogenetic placement of query sequences in a reference tree", "quartonotebook": "Render a Quarto notebook, including parametrization."}}, "target": "epang/split", "target_idx": 1}
{"id": "mod_whatshap_phase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Phase variants in a VCF file using long-read sequencing data (tools: whatshap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"differential_functional_enrichment": "Run functional analysis on differential abundance analysis output", "eagle2": "Perform phasing of genotyped data with or without a reference panel", "whatshap_phase": "Phase variants in a VCF file using long-read sequencing data", "beagle5_beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers.", "kled": "An ultra-fast and sensitive structural variant detection tool for long-read sequencing data."}}, "target": "whatshap_phase", "target_idx": 2}
{"id": "mod_transdecoder_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. You can use this module after transdecoder_longorf (tools: transdecoder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_extract": "Subset plink pfiles with a text file of variant identifiers", "transdecoder_predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "purecn_normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as", "antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt"}}, "target": "transdecoder_predict", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_30", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_4_3", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_fetchngs_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to fetch metadata and raw FastQ files from public databases. Topics: ddbj, download, ena, fastq, geo, sra. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"differentialabundance": null, "methylseq": null, "rnastructurome": null, "raredisease": null, "marsseq": null, "scrnaseq": null, "fetchngs": null, "scnanoseq": null, "bamtofastq": null, "rnadnavar": null}}, "target": "fetchngs", "target_idx": 6}
{"id": "subworkflow_pkg_bam_sort_stats_samtools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SORT_STATS_SAMTOOLS", "modules": ["samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Sort SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_SORT_STATS_SAMTOOLS (samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_sort_stats_samtools": null, "Local subworkflow BAM_SORT_STATS_SAMTOOLS": null}}, "target": "Use nf-core subworkflow bam_sort_stats_samtools", "target_idx": 2}
{"id": "local_subworkflow_checkirma_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should CHECKIRMA (custom/checkirma) be built?", "criteria": {"Local subworkflow CHECKIRMA": null, "Use nf-core subworkflow checkirma": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 0}
{"id": "resource_bcftools_call_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CALL", "tool": "bcftools/call", "description": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily lost in the process of transition under htslib, but will be added back on popular demand.\nThe original calling model can be invoked with the -c option."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CALL (This command replaces the former bcftools view caller.\nSome of the original func) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Longitudinal cancer monitoring across multiple timepoints. Input files: Serial plasma cfDNA and biopsy FASTQs across treatment intervals.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_1_5", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_callingcards_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for processing calling cards data. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"callingcards": "A pipeline for processing calling cards data", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]"}}, "target": "callingcards", "target_idx": 0}
{"id": "noul_undeclared_process_file_inputs_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_gatk4_printsvevidence_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file containing the location of and orientation of read pairs marked as discordant, and a file containing the clipping location of all soft clipped reads and the orientation of the clipping. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_printsvevidence": null, "gatk4_baserecalibrator": null, "gatk4_applybqsr": null, "clusty": null, "paftools_sam2paf": null}}, "target": "gatk4_printsvevidence", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_4_1", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted BAMs with index for tumor and normal samples?", "criteria": {"sample,bam,bai": null, "patient,sample,bam": null, "sample,vcf": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "pipe_all101_proteinfamilies_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Generation and updating of protein families. Topics: metagenomics, protein-families. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]"}}, "target": "proteinfamilies", "target_idx": 0}
{"id": "local_subworkflow_checkirma_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for CHECKIRMA (custom/checkirma).", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow checkirma": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "samplesheet_arch_ont_direct_rna_se_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Single-end Oxford Nanopore direct RNA)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fast5": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_platypus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Platypus is a tool that efficiently and accurately calling genetic variants from next-generation DNA sequencing data (tools: platypus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"platypus": "Platypus is a tool that efficiently and accurately calling genetic variants from next-generation DNA sequencin", "graphtyper_genotype": "Tools for population-scale genotyping using pangenome graphs.", "ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro", "bedtools_getfasta": "extract sequences in a FASTA file based on intervals defined in a feature file.", "gatk4spark_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)"}}, "target": "platypus", "target_idx": 0}
{"id": "field_constraint_sample_0_11", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "mod_bbmap_filterbyname_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter out sequences by sequence header name(s) (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "freyja/demix": "specify the relative abundance of each known haplotype", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "bbmap/filterbyname": "Filter out sequences by sequence header name(s)"}}, "target": "bbmap/filterbyname", "target_idx": 4}
{"id": "samplesheet_arch_spatial_visium_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Visium spatial transcriptomics with histology image. Input files: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Visium spatial transcriptomics with histology image.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "mod_vcf2zarr_explode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF(s) to intermediate columnar format (tools: vcf2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": null, "merqury_merqury": null, "atlas_call": null, "vcf2zarr_explode": null, "chromograph": null}}, "target": "vcf2zarr_explode", "target_idx": 3}
{"id": "field_constraint_strandedness_1_14", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "mod_cellrangerarc_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's ARC pipelines analyze sequencing data produced from Chromium Single Cell ARC. Uses the cellranger-arc count command. (tools: cellrangerarc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc_count": "Module to use Cell Ranger's ARC pipelines analyze sequencing data produced from Chromium Single Cell ARC. Uses", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "last_mafconvert": "Converts MAF alignments in another format.", "mash_screen": "Screens query sequences against large sequence databases", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin"}}, "target": "cellrangerarc_count", "target_idx": 0}
{"id": "subworkflow_pkg_bam_variant_calling_sort_freebayes_bcftools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS", "modules": ["freebayes", "bcftools/sort"], "description": "Call variants using freebayes, then sort and index"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS (freebayes, bcftools/sort) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VARIANT_CALLING_SORT_FREEBAYES_BCFTOOLS": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools": null}}, "target": "Use nf-core subworkflow bam_variant_calling_sort_freebayes_bcftools", "target_idx": 3}
{"id": "samplesheet_arch_ont_direct_rna_se_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Single-end Oxford Nanopore direct RNA. Input files: Single fastq per sample.", "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Oxford Nanopore direct RNA input samplesheet?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "schema_std_evexplorer_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/evexplorer", "assay": "evexplorer pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/evexplorer (nf-core/evexplorer is a pipeline for analyzing RNA data from)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,batch,condition": null, "id,test_vcf,test_regions,caller,subsample": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "sample,fastq_1,fastq_2,batch,condition", "target_idx": 1}
{"id": "mod_crumble_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Controllable lossy compression of BAM/CRAM files (tools: crumble)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crumble": null, "htslib/bgziptabix": null, "openms/idfilter": null, "ganon/report": null, "abra2": null}}, "target": "crumble", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_6_4", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate", "pipeline": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Which columns are standard for Hybrid bacterial assembly combining short Illumina and long Nanopore reads input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_gffread_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validate, filter, convert and perform various other operations on GFF files (tools: gffread)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "megan/rma2info": "Analyses an RMA file and exports information in text format", "agat/spaddintrons": "Add intron features to gtf/gff file without intron features.", "gedi/price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "gffread": "Validate, filter, convert and perform various other operations on GFF files"}}, "target": "gffread", "target_idx": 4}
{"id": "schema_std_pathogensurveillance_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pathogensurveillance", "description": "Surveillance of pathogens using population genomics and sequencing", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pathogensurveillance?", "criteria": {"sample_id,name,description,path,path_2": null, "id,path": null, "id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample_id,name,description,path,path_2", "target_idx": 0}
{"id": "noul_channel_collect_operator_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_allelecounter_0", "category": "resource_profiling", "state": {"process": "ALLELECOUNTER", "tool": "allelecounter", "description": "Generates a count of coverage of alleles"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALLELECOUNTER (Generates a count of coverage of alleles) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/dualrnaseq", "assay_type": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "data_format": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns are standard for Dual RNA-seq simultaneous host and pathogen transcriptomics input samplesheet?", "criteria": {"sample,host_fasta": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_0_2", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,tss_bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "resource_bcl2fastq_5", "category": "resource_profiling", "state": {"process": "BCL2FASTQ", "tool": "bcl2fastq", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCL2FASTQ (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_samtools_fasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a SAM/BAM/CRAM file to FASTA (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamclipper": "This module is used to clip primer sequences from your alignments.", "samtools/fasta": "Converts a SAM/BAM/CRAM file to FASTA", "ascat": "copy number profiles of tumour cells.", "wisecondorx/predict": "Find copy number aberrations", "octopusv/svcf2bed": "Converts octopusv SVCF files to the standard BED format"}}, "target": "samtools/fasta", "target_idx": 1}
{"id": "noul_deprecated_file_output_syntax_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bbmap_sendsketch_5", "category": "resource_profiling", "state": {"process": "BBMAP_SENDSKETCH", "tool": "bbmap/sendsketch", "description": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_SENDSKETCH (Compares query sketches to reference sketches hosted on a remote server via the ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_1_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_fastq_contam_seqtk_kraken_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a contamination report from FastQ input after subsampling (tools: fastq_contam_seqtk_kraken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbmm2/align": "Alignment with PacBio's minimap2 frontend", "bamstats/generalstats": "write your description here", "fastq_contam_seqtk_kraken": "Produces a contamination report from FastQ input after subsampling", "gfatools/stat": "Summary statistics for GFA files", "bedtools/jaccard": "Calculate Jaccard statistic b/w two feature files."}}, "target": "fastq_contam_seqtk_kraken", "target_idx": 2}
{"id": "mod_cellranger_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expression. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "cellranger/count": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expressi", "cutesv": "structural-variant calling with cutesv", "parabricks/haplotypecaller": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating GATK haplotypecaller."}}, "target": "cellranger/count", "target_idx": 2}
{"id": "mod_mudskipper_bulk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert genomic BAM/SAM files to transcriptomic BAM/RAD files. (tools: mudskipper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": null, "mudskipper/bulk": null, "cellranger/mkref": null, "abra2": null, "bedtools/slop": null}}, "target": "mudskipper/bulk", "target_idx": 1}
{"id": "mod_skani_search_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Memory-efficient ANI database queries with skani. (tools: skani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svdb_build": "Build a structural variant database", "skani_search": "Memory-efficient ANI database queries with skani.", "skani_dist": "Simple ANI calculation between reference and query genomes.", "concoct_concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "skani_search", "target_idx": 1}
{"id": "resource_amps_3", "category": "resource_profiling", "state": {"process": "AMPS", "tool": "amps", "description": "Post-processing script of the MaltExtract component of the HOPS package"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPS (Post-processing script of the MaltExtract component of the HOPS package) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_isoseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/isoseq", "description": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences and produce a bed annotation. ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/isoseq?", "criteria": {"sample,fastq_1,fastq_2,bam,bai": null, "sample,seq_data,pbi,start_from": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2,strandedness,condition": null}}, "target": "sample,seq_data,pbi,start_from", "target_idx": 1}
{"id": "samplesheet_arch_spatial_visium_3_0", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Visium spatial transcriptomics with histology image with entry step FASTQC.", "criteria": {"sample,fastq_1,image": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,image,slide,area": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 3}
{"id": "noul_named_output_channel_access_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_viralintegration_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for chimeric-alignment. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG."}}, "target": "viralintegration", "target_idx": 7}
{"id": "mod_gcta_bivariatereml_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run bivariate REML analysis with a single dense GRM (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariatereml": "Run bivariate REML analysis with a single dense GRM", "quilt_quilt2": "QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased re", "hicap": "Identify cap locus serotype and structure in your Haemophilus influenzae assemblies", "gcta_grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`", "gcta_adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`"}}, "target": "gcta_bivariatereml", "target_idx": 0}
{"id": "field_constraint_phenotype_0_7", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "mod_roary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pan-genome from annotated bacterial assemblies in GFF3 format (tools: roary)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"roary": "Calculate pan-genome from annotated bacterial assemblies in GFF3 format", "traitar/pfamget": "Download PFAM database for traitar phenotype prediction", "agat/spaddintrons": "Add intron features to gtf/gff file without intron features.", "umitools/prepareforrsem": "Make the output from umi_tools dedup or group compatible with RSEM", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file"}}, "target": "roary", "target_idx": 0}
{"id": "pipe_all101_bactmap_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences. Topics: bacteria, bacterial, bacterial-genome-analysis, genomics, mapping, phylogeny. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": null, "nanoseq": null, "callingcards": null, "dualrnaseq": null, "bactmap": null, "genomeqc": null, "mag": null, "pairgenomealign": null}}, "target": "bactmap", "target_idx": 4}
{"id": "resource_bcftools_convert_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONVERT", "tool": "bcftools/convert", "description": "Converts certain output formats to VCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONVERT (Converts certain output formats to VCF) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_concoct_concoct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage data for multiple samples (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker_call": "mtDNA deletion and duplication calling downstream of mitosalt", "concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "gens_preparecovandbaf": "Tools for preparing inputs for visualization in Gens", "concoct_concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "concoct_concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile"}}, "target": "concoct_concoct", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_14", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_43", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_sentieon_gvcftyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform joint genotyping on one or more samples pre-called with Sentieon's Haplotyper. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon/indexdiff": "Subtract minimizers in deacon index (or fasta file) from another index (A - B)", "gcta/bivariatereml": "Run bivariate REML analysis with a single dense GRM", "bcftools/pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "sentieon/gvcftyper": "Perform joint genotyping on one or more samples pre-called with Sentieon's Haplotyper.", "genin2": "Genin2 is a lightining-fast bioinformatic tool to predict genotypes for H5 viruses belonging to the European c"}}, "target": "sentieon/gvcftyper", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_3_2", "category": "samplesheet_schema", "state": {"technology": "Spatial In Situ", "workflow_entry": "INPUT_CHECK", "library_inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Xenium in situ subcellular spatial RNA transcriptomics with entry step INPUT_CHECK.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,image": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_5_3", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Longitudinal cancer monitoring across multiple timepoints.", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bedtools_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts a feature file by chromosome and other criteria. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio/exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "samtools/collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "bedtools/sort": "Sorts a feature file by chromosome and other criteria."}}, "target": "bedtools/sort", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_1_25", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "ATAC-seq chromatin accessibility with biological replicates", "data_format": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ATAC-seq chromatin accessibility with biological replicates with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_8_1", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "mod_bwafastalign_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA-FASTALIGN index for reference genome (tools: bwafastalign)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwafastalign_index": null, "miranda": null, "bbmap_index": null, "gatk4_composestrtablefile": null, "bcftools_index": null}}, "target": "bwafastalign_index", "target_idx": 0}
{"id": "mod_comet_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool (tools: comet)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "odgi_sort": "Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm.", "bam_docounts_contamination_angsd": "Calculate contamination of the X-chromosome with ANGSD", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "diamond_linclust": "Fast protein sequence clustering using a greedy incremental approach"}}, "target": "comet", "target_idx": 3}
{"id": "mod_fungtion_fungtion_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts fungal effector proteins from protein FASTA sequences using ESM-1b\nprotein language model embeddings and R-based SVM models. Optionally produces\nsimilarity-network and relationship-tree visualizations and an HTML report for\npredicted effectors. Requires the pretrained ESM-1b weights from\nFUNGTION_DOWNLOADMODELS as input. (tools: fungtion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcfanno": "quickly annotate your VCF with any number of INFO fields from any number of VCFs or BED files", "cdhit_cdhit": "Cluster protein sequences using sequence similarity", "biscuit_bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "fungtion_fungtion": "Predicts fungal effector proteins from protein FASTA sequences using ESM-1b\nprotein language model embeddings ", "clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million"}}, "target": "fungtion_fungtion", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_22", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "field_constraint_sample_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"type: integer": null, "format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_legsta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Typing of clinical and environmental isolates of Legionella pneumophila (tools: legsta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "kmcp/index": "Construct KMCP database from k-mer files", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "legsta": "Typing of clinical and environmental isolates of Legionella pneumophila", "samtools/view": "filter/convert SAM/BAM/CRAM file"}}, "target": "legsta", "target_idx": 3}
{"id": "mod_ampcombi2_complete_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A submodule that merges all output summary tables from ampcombi/parsetables in one summary file. (tools: ampcombi2/complete)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cleanifier/index": null, "ampcombi2/cluster": null, "krona/ktupdatetaxonomy": null, "amplify/predict": null, "ampcombi2/complete": null}}, "target": "ampcombi2/complete", "target_idx": 4}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_4_1", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Circulating tumor DNA FASTQs across patient clinical draw intervals?", "criteria": {"sample,bam": null, "sample,timepoint,fastq": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_confusing_combine_with_mix_semantics_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_rtgtools_vcfeval_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The VCFeval tool of RTG tools. It is used to evaluate called variants for agreement with a baseline variant set (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"staphopiasccmec": "Predicts Staphylococcus aureus SCCmec type based on primers.", "rtgtools/vcfeval": "The VCFeval tool of RTG tools. It is used to evaluate called variants for agreement with a baseline variant se", "gt/gff3": "GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "holodeck/eval": "Evaluate alignment accuracy of holodeck-simulated reads"}}, "target": "rtgtools/vcfeval", "target_idx": 1}
{"id": "resource_baysor_run_5", "category": "resource_profiling", "state": {"process": "BAYSOR_RUN", "tool": "baysor/run", "description": "Bayesian segmentation of spatial transcriptomics data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_RUN (Bayesian segmentation of spatial transcriptomics data.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_fastquorum_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/fastquorum. Description: Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/fastquorum.", "criteria": {"sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,strandedness,type": null, "sample,fastq_1,fastq_2,library_id,lane": null, "sample,fastq_1,fastq_2,rundir,tags": null}}, "target": "sample,fastq_1,fastq_2,library_id,lane", "target_idx": 2}
{"id": "pipe_all101_proteinfamilies_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Generation and updating of protein families. Topics: metagenomics, protein-families. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanoseq": null, "drugresponseeval": null, "rnaseq": null, "cutandrun": null, "hic": null, "proteinfamilies": null, "stableexpression": null, "viralmetagenome": null}}, "target": "proteinfamilies", "target_idx": 5}
{"id": "mod_gcta_grmcutoff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff` (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariatereml": "Run bivariate REML analysis with a single dense GRM", "hmmer_hmmstat": "display summary statistics for each profile HMM in an HMM database file", "gcta_adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`", "gcta_grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient "}}, "target": "gcta_grmcutoff", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_3_1", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Parse Biosciences Split-seq combinatorial barcoding with entry step FASTQC.", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_kallistobustools_ref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: index creation for kb count quantification of single-cell data. (tools: kb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender_removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "kallistobustools_ref": "index creation for kb count quantification of single-cell data.", "cellbender_merge": "Module to use CellBender to remove ambient RNA from single-cell RNA-seq data", "gatk4_filtermutectcalls": "Filters the raw output of mutect2, can optionally use outputs of calculatecontamination and learnreadorientati", "fastq_find_mirna_mirdeep2": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, proc"}}, "target": "kallistobustools_ref", "target_idx": 1}
{"id": "mod_hmmer_hmmlogo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: extract logo data from a profile HMM file to produce an HMM logo (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment", "rundbcan_easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "hmmer_hmmfetch": "extract hmm from hmm database file or create index for hmm database", "bamstats_generalstats": "write your description here", "hmmer_hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo"}}, "target": "hmmer_hmmlogo", "target_idx": 4}
{"id": "pipe_all101_viralmetagenome_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for epidemiology analysis? Specific context: A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.. Topics: epidemiology, fastq, ngs, viral-metagenomics, virology, virus-genomes. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]"}}, "target": "viralmetagenome", "target_idx": 3}
{"id": "mod_svdb_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a structural variant database (tools: svdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caddsv/run": null, "caddsv/get": null, "autocycler/resolve": null, "svdb/build": null, "mmseqs/easycluster": null}}, "target": "svdb/build", "target_idx": 3}
{"id": "field_constraint_fastq_1_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "intent_prepare_data_13", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "debug_error": null, "build_pipeline": null}}, "target": "prepare_data", "target_idx": 0}
{"id": "mod_bcftools_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split a vcf file into files per chromosome (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/split": "Split a vcf file into files per chromosome", "rseqc/splitbam": "Split BAM file based on gene list in BED format", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "metaphlan/makedb": "Build MetaPhlAn database for taxonomic profiling.", "bcftools/annotate": "Add or remove annotations."}}, "target": "bcftools/split", "target_idx": 0}
{"id": "mod_gatk4_genomicsdbimport_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: merge GVCFs from multiple samples. For use in joint genotyping or somatic panel of normal creation. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "gatk4_genomicsdbimport": "merge GVCFs from multiple samples. For use in joint genotyping or somatic panel of normal creation.", "sushie": "Software to perform multi-ancestry SNP fine-mapping on molecular data", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "bismark_summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report."}}, "target": "gatk4_genomicsdbimport", "target_idx": 1}
{"id": "schema_std_molkart_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/molkart", "description": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/molkart?", "criteria": {"sample,fastq_1,strandedness": null, "sample,seq_data,pbi,start_from": null, "sample,nuclear_image,spot_table,membrane_image": null, "fastq_1,fastq_2,group,replicate,md5_1": null}}, "target": "sample,nuclear_image,spot_table,membrane_image", "target_idx": 2}
{"id": "core_tool_bwa_mem_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Fast short-read DNA sequence alignment against reference genome creating sorted SAM/BAM alignments for variant calling.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"star": null, "bwa_mem": null, "bowtie2": null, "salmon": null, "minimap2": null}}, "target": "bwa_mem", "target_idx": 1}
{"id": "mod_vcf_filter_bcftools_ensemblvep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter VCF file with bcftools and filter_vep (tools: vcf_filter_bcftools_ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_filter_bcftools_ensemblvep": null, "samtools_bam2fq": null, "stacks_refmap": null, "biscuit_bsconv": null, "agat_spkeeplongestisoform": null}}, "target": "vcf_filter_bcftools_ensemblvep", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_mapad_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_MAPAD", "modules": ["mapad/map", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_MAPAD (mapad/map, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_align_mapad": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_MAPAD": null}}, "target": "Use nf-core subworkflow fastq_align_mapad", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_3_2", "category": "samplesheet_schema", "state": {"technology": "Metagenomics Profiling", "workflow_entry": "FASTQC", "library_inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-taxonomic profiling of complex metagenomic shotgun reads with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bwa_mem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldseek/easysearch": null, "custom/orfmerge": null, "bwa/mem": null, "bwafastalign/mem": null, "bwamem2/mem": null}}, "target": "bwa/mem", "target_idx": 2}
{"id": "resource_bowtie_build_3", "category": "resource_profiling", "state": {"process": "BOWTIE_BUILD", "tool": "bowtie/build", "description": "Create bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_BUILD (Create bowtie index for reference genome) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_35", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "pipe_all101_funcprofiler_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Read-based functional profiling of microbiome sequencing data. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drugresponseeval": null, "funcprofiler": null, "pangenome": null, "proteinfamilies": null, "rnasplice": null, "metatdenovo": null, "drop": null, "seqsubmit": null, "molkart": null, "rnastructurome": null}}, "target": "funcprofiler", "target_idx": 1}
{"id": "resource_blast_updateblastdb_4", "category": "resource_profiling", "state": {"process": "BLAST_UPDATEBLASTDB", "tool": "blast/updateblastdb", "description": "Downloads a BLAST database from NCBI"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_UPDATEBLASTDB (Downloads a BLAST database from NCBI) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_rnavar_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for gatk4. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]"}}, "target": "rnavar", "target_idx": 1}
{"id": "resource_amrfinderplus_run_1", "category": "resource_profiling", "state": {"process": "AMRFINDERPLUS_RUN", "tool": "amrfinderplus/run", "description": "Identify antimicrobial resistance in gene or protein sequences"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMRFINDERPLUS_RUN (Identify antimicrobial resistance in gene or protein sequences) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_align_mapad_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_MAPAD", "modules": ["mapad/map", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_MAPAD (mapad/map, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_MAPAD": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_mapad": null}}, "target": "Use nf-core subworkflow fastq_align_mapad", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/taxprofiler) for Multi-taxonomic profiling of complex metagenomic shotgun reads. Input files: Short or long reads with run accession and library instrument platform.", "question": {"type": "choice", "instructions": "Which columns are standard for Multi-taxonomic profiling of complex metagenomic shotgun reads input samplesheet?", "criteria": {"sample,kraken_db": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_deeptools_plotfingerprint_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: plots cumulative reads coverages by BAM file (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy_happy": "Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row", "deeptools_plotfingerprint": "plots cumulative reads coverages by BAM file", "deeptools_multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "krona_ktimportkrona": "Collect multiple krona reports into a single html file", "centrifuger_build": "Build centrifuger database for taxonomic profiling"}}, "target": "deeptools_plotfingerprint", "target_idx": 1}
{"id": "field_constraint_expected_cells_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"pattern: ^\\S+\\.csv$": null, "format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "mod_metator_pipeline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing and binning of metagenomic metaHiC datasets. (tools: metator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spring_decompress": null, "pretextsnapshot": null, "metator_pipeline": null, "yahs": null, "cellrangerarc_mkgtf": null}}, "target": "metator_pipeline", "target_idx": 2}
{"id": "mod_bedtools_intersect_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Allows one to screen for overlaps between two sets of genomic features. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_epiread": null, "bedtools_intersect": null, "lofreq_indelqual": null, "agat_convertbed2gff": null, "bedops_convert2bed": null}}, "target": "bedtools_intersect", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_3_2", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "NANOPLOT", "library_inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Oxford Nanopore environmental metagenomic sequencing with entry step NANOPLOT.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "mod_ganon_classify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classify FASTQ files against ganon database (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_classify": "Classify FASTQ files against ganon database", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "ganon_table": "Generate a multi-sample report file from the output of ganon report runs", "ska_fasta": "Create genome sketch using split k-mers", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O"}}, "target": "ganon_classify", "target_idx": 0}
{"id": "resource_angsd_gl_5", "category": "resource_profiling", "state": {"process": "ANGSD_GL", "tool": "angsd/gl", "description": "Calculated genotype likelihoods from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_GL (Calculated genotype likelihoods from BAM files.) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_fastq_align_mapad_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and indexed BAM files (tools: fastq_align_mapad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"duphold": null, "csvtk/sort": null, "megahit": null, "fastq_align_mapad": null, "parsesdrf/convert": null}}, "target": "fastq_align_mapad", "target_idx": 3}
{"id": "pipe_all101_isoseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences and produce a bed annotation.. Topics: isoseq, isoseq-3, rna, tama, ultra. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot"}}, "target": "isoseq", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_40", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_41", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_rgi_bwt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict antibiotic resistance from protein or nucleotide data (tools: rgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline", "rgi_bwt": "Predict antibiotic resistance from protein or nucleotide data", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "bwamem3_index": "Create bwa-mem3 index for reference genome"}}, "target": "rgi_bwt", "target_idx": 1}
{"id": "mod_fq_subsample_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fq subsample outputs a subset of records from single or paired FASTQ files. This requires a seed (--seed) to be set in ext.args. (tools: fq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "fq_subsample": "fq subsample outputs a subset of records from single or paired FASTQ files. This requires a seed (--seed) to b", "ariba_getref": "Download and prepare database for Ariba analysis", "bam_dedup_stats_samtools_umicollapse": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats", "samtools_samples": "Write sample names and path to reference genome of an alignment to a text file."}}, "target": "fq_subsample", "target_idx": 1}
{"id": "mod_hmmer_hmmstat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: display summary statistics for each profile HMM in an HMM database file (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file", "viennarna_rnalfold": "calculate locally stable secondary structures of RNAs", "hmmer_hmmstat": "display summary statistics for each profile HMM in an HMM database file", "hmmer_hmmsearch": "search profile(s) against a sequence database", "hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment"}}, "target": "hmmer_hmmstat", "target_idx": 2}
{"id": "mod_happy_ftxpy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Somatic VCF Feature Extraction tool from hap.y. (tools: happy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy_ftxpy": null, "happy_prepy": null, "happy_sompy": null, "baysor_run": null, "gangstr": null}}, "target": "happy_ftxpy", "target_idx": 0}
{"id": "mod_purecn_normaldb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as reported in https://www.bioconductor.org/packages/devel/bioc/vignettes/PureCN/inst/doc/Quick.html, it is advised to provide a normal panel (VCF format) to precompute mapping bias for faster runtimes. (tools: purecn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/genotypegvcfs": null, "purecn/normaldb": null, "purecn/intervalfile": null, "cooler/zoomify": null, "purecn/run": null}}, "target": "purecn/normaldb", "target_idx": 1}
{"id": "subworkflow_pkg_bam_vcf_impute_glimpse2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VCF_IMPUTE_GLIMPSE2", "modules": ["glimpse2/chunk", "glimpse2/phase", "glimpse2/ligate", "glimpse2/splitreference", "bcftools/index"], "description": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should BAM_VCF_IMPUTE_GLIMPSE2 (glimpse2/chunk, glimpse2/phase, glimpse2/ligate, glimpse2/splitreference, bcftools/index) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VCF_IMPUTE_GLIMPSE2": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_vcf_impute_glimpse2": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_vcf_impute_glimpse2", "target_idx": 2}
{"id": "mod_mmseqs_search_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search and calculate a score for similar sequences in a query and a target database. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_createtaxdb": null, "nucmer": null, "mmseqs_search": null, "mmseqs_easycluster": null, "deepbgc_pipeline": null}}, "target": "mmseqs_search", "target_idx": 2}
{"id": "field_constraint_fastq_2_0_0", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_0_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"sample,timepoint,fastq": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "data_format": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,primer_its1,primer_its2": null, "sample,unite_fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "subworkflow_pkg_vcf_filter_bcftools_ensemblvep_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_FILTER_BCFTOOLS_ENSEMBLVEP", "modules": ["bcftools/view", "ensemblvep/filtervep", "htslib/bgziptabix"], "description": "Filter VCF file with bcftools and filter_vep"}, "question": {"type": "choice", "instructions": "How should VCF_FILTER_BCFTOOLS_ENSEMBLVEP (bcftools/view, ensemblvep/filtervep, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Local subworkflow VCF_FILTER_BCFTOOLS_ENSEMBLVEP": null, "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep", "target_idx": 1}
{"id": "noul_named_output_channel_access_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_bactmap_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences. Topics: bacteria, bacterial, bacterial-genome-analysis, genomics, mapping, phylogeny. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis"}}, "target": "bactmap", "target_idx": 1}
{"id": "mod_epang_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: splits an alignment into reference and query parts (tools: epang)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm", "epang_split": "splits an alignment into reference and query parts", "kallistobustools_count": "quantifies scRNA-seq data from fastq files using kb-python.", "cafe": "Analysis of gene family evolution", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient "}}, "target": "epang_split", "target_idx": 1}
{"id": "mod_bigscape_bigscape_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results. (tools: bigscape)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/hwe": null, "antismash/antismash": null, "bigscape/bigscape": null, "centrifuge/build": null, "bigslice/downloaddb": null}}, "target": "bigscape/bigscape", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq.", "criteria": {"sample,well,fastq": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_4_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end Tn5 transposed FASTQs across conditions and replicates?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_48", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_44", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_ctree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clone trees for Cancer Evolution studies from bulk sequencing data. (tools: ctree)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbtk_bam2fastq": "converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq", "fastq_align_dedup_bwameth": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "mmseqs_easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "ctree": "Clone trees for Cancer Evolution studies from bulk sequencing data."}}, "target": "ctree", "target_idx": 4}
{"id": "samplesheet_arch_methylseq_bisulfite_5_3", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/methylseq, determine the input samplesheet column structure for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq).", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,cpg,methylation": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_index_methylseq_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_METHYLSEQ", "modules": ["untar", "gunzip", "bismark/genomepreparation", "bwameth/index", "bwa/index", "samtools/faidx"], "description": "Generate index files from reference fasta for bismark, bwameth and bwamem aligners"}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_METHYLSEQ (untar, gunzip, bismark/genomepreparation, bwameth/index, bwa/index, samtools/faidx) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_index_methylseq": null, "Leave them out": null, "Local subworkflow FASTA_INDEX_METHYLSEQ": null}}, "target": "Use nf-core subworkflow fasta_index_methylseq", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Genome analysis from reference-compressed CRAM files)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_5_5", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry).", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_7_0", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_0_0", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_suppa_generateevents_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates alternative splicing events from a GTF file using SUPPA. (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa_diffsplice": "Perform differential splicing analysis using SUPPA.", "tcoffee_regressive": "Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package", "humann3_renorm": "Normalizing RPKs to relative abundance", "suppa_generateevents": "Generates alternative splicing events from a GTF file using SUPPA.", "suppa_clusterevents": "Cluster events based on PSI values and significantly differentially spliced events using SUPPA2."}}, "target": "suppa_generateevents", "target_idx": 3}
{"id": "resource_bclconvert_4", "category": "resource_profiling", "state": {"process": "BCLCONVERT", "tool": "bclconvert", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCLCONVERT (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_tn_0_1", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,bam,bai": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_42", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_ampir_4", "category": "resource_profiling", "state": {"process": "AMPIR", "tool": "ampir", "description": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ampir uses a supervised statistical machine learning approach to predict AMPs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPIR (A fast and user-friendly method to predict antimicrobial peptides (AMPs) from an) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_28", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "pipe_all101_drugresponseeval_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline for testing drug response prediction models in a statistically and biologically sound way.. Topics: cell-lines, cross-validation, deep-learning, drug-response, drug-response-prediction, drugs. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "metapep": "From metagenomes to epitopes and beyond", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "drugresponseeval", "target_idx": 6}
{"id": "core_tool_mutect2_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Somatic short variant detection (SNVs and small indels) comparing matched tumor and normal sequencing data with Bayesian somatic likelihood filtering.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"mutect2": null, "vardict": null, "strelka2": null, "varscan2": null, "somaticsniper": null}}, "target": "mutect2", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_42", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_antismash_antismashlitedownloaddatabases_5", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES", "tool": "antismash/antismashlitedownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_metacache_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic profiling database building with MetaCache (tools: metacache)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metacache_build": "Taxonomic profiling database building with MetaCache", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "gatk4_unmarkduplicates": "This tool locates and unmark the marked duplicate reads in a BAM or SAM file, where duplicate reads are define", "picard_renamesampleinvcf": "changes name of sample in the vcf file"}}, "target": "metacache_build", "target_idx": 0}
{"id": "mod_minibwa_map_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align fastq reads to a fasta reference using minibwa (tools: minibwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "metabat2/jgisummarizebamcontigdepths": "Depth computation per contig step of metabat2", "minibwa/map": "Align fastq reads to a fasta reference using minibwa", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}}, "target": "minibwa/map", "target_idx": 3}
{"id": "resource_agat_spfilterbyorfsize_5", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERBYORFSIZE", "tool": "agat/spfilterbyorfsize", "description": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF passing the test, the other contains the rest. By default the test is \"> 100\" that means all gene models that have ORF longer than 100 Amino acids, will pass the test."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERBYORFSIZE (The script reads a gff annotation file, and create two output files, one contain) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_utils_nextflow_pipeline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow with functionality that may be useful for any Nextflow pipeline (tools: utils_nextflow_pipeline)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"staphscan": "staphscan is a tool to screen genome assemblies of Staphylococcus aureus", "aria2": "CLI Download utility", "goatools_findenrichment": "Find enriched GO terms in a list of genes", "star_indexversion": "Get the minimal allowed index version from STAR", "utils_nextflow_pipeline": "Subworkflow with functionality that may be useful for any Nextflow pipeline"}}, "target": "utils_nextflow_pipeline", "target_idx": 4}
{"id": "samplesheet_arch_cancer_tumor_only_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Tumor-only somatic variant calling without matched normal)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Tumor-only somatic variant calling without matched normal.", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_coverm_genome_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate read coverage per-genome (tools: coverm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "coptr_merge": "Merge reads that were mapped to multiple indices", "coverm_genome": "Calculate read coverage per-genome", "coptr_estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "cooler_cload": "Create a cooler from genomic pairs and bins"}}, "target": "coverm_genome", "target_idx": 2}
{"id": "mod_rnaquast_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assess the quality of an RNAseq assembly with or without a reference genome (tools: rnaquast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem2/gem2bedmappability": "Convert a mappability file to bedgraph format", "bam_ngscheckmate": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set o", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome", "custom/multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "rnaquast", "target_idx": 3}
{"id": "pipe_all101_magmap_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Best-practice analysis pipeline for mapping reads to a (large) collections of genomes. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": null, "drugresponseeval": null, "nascent": null, "magmap": null, "lsmquant": null, "crisprseq": null, "hadge": null, "metatdenovo": null}}, "target": "magmap", "target_idx": 3}
{"id": "mod_scramble_clusteridentifier_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The cluster_identifier tool of Scramble identifies soft clipped clusters (tools: scramble)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromap_index": "Indexes a fasta reference genome ready for chromatin profiling.", "ascat": "copy number profiles of tumour cells.", "bamclipper": "This module is used to clip primer sequences from your alignments.", "viralconsensus": "Fast and memory-efficient viral consensus genome sequence generation from read alignments", "scramble_clusteridentifier": "The cluster_identifier tool of Scramble identifies soft clipped clusters"}}, "target": "scramble_clusteridentifier", "target_idx": 4}
{"id": "mod_wittyer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A large variant benchmarking tool analogous to hap.py for small variants. (tools: wittyer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jasminesv": "Jointly Accurate Sv Merging with Intersample Network Edges", "wittyer": "A large variant benchmarking tool analogous to hap.py for small variants.", "rtgtools_bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "strdust": "Tandem repeat genotyper for long reads", "octopusv_clean": "Clean broken VCF/SVCF files using OctopuSV clean"}}, "target": "wittyer", "target_idx": 1}
{"id": "resource_bigslice_bigslice_5", "category": "resource_profiling", "state": {"process": "BIGSLICE_BIGSLICE", "tool": "bigslice/bigslice", "description": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenBank format along with an HMM database and produces a SQLite database and FASTA outputs of predicted features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_BIGSLICE (A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nI) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_ampliseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "description": "Amplicon sequencing analysis workflow using DADA2 and QIIME2", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/ampliseq?", "criteria": {"sample,fastq_1,fastq_2,bam,seq_type": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null}}, "target": "sample,fastq_1,fastq_2,sampleID,forwardReads", "target_idx": 2}
{"id": "mod_pcangsd_inbreeding_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate per-sample inbreeding coefficients from genotype likelihoods (tools: pcangsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mashtree": null, "agat_spmergeannotations": null, "pcangsd_inbreeding": null, "peka": null, "agat_spextractsequences": null}}, "target": "pcangsd_inbreeding", "target_idx": 2}
{"id": "mod_fgbio_groupreadsbyumi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template, and then templates are sorted by the 5’ mapping positions\nof the reads from the template, used from earliest mapping position to latest.\nReads that have the same end positions are then sub-grouped by UMI sequence.\n(!) Note: the MQ tag is required on reads with mapped mates (!)\nThis can be added using samblaster with the optional argument --addMateTags. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "picard_createsequencedictionary": "Creates a sequence dictionary for a reference sequence.", "fgbio_groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "tcoffee_tcs": "Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just"}}, "target": "fgbio_groupreadsbyumi", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_22", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_fasta_binning_concoct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs the CONCOCT workflow of contig binning (tools: fasta_binning_concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metaspace_download": null, "concoct_cutupfasta": null, "binette": null, "bwa_index": null, "fasta_binning_concoct": null}}, "target": "fasta_binning_concoct", "target_idx": 4}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_2_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_plastid_metagenegenerate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of interest, optionally applying a mapping rule (tools: plastid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segul/aligntrim": "Trim multiple sequence alignments by filtering columns based on missing data proportion or parsimony informati", "plastid/metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "peka": "Runs PEKA CLIP peak k-mer analysis"}}, "target": "plastid/metagenegenerate", "target_idx": 1}
{"id": "field_constraint_strandedness_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"type: boolean": null, "pattern: ^[0-9]+$": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "field_constraint_sample_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null, "type: integer": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "field_constraint_status_1_12", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_1_22", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_4_3", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted BAMs with index for tumor and normal samples?", "criteria": {"sample,bam,bai": null, "patient,sample,status,bam,bai": null, "patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_4_1", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_undeclared_process_file_inputs_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_consensus_autocycler_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CONSENSUS_AUTOCYCLER", "modules": ["autocycler/compress", "autocycler/cluster", "autocycler/trim", "autocycler/resolve", "autocycler/combine"], "description": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler"}, "question": {"type": "choice", "instructions": "How should FASTA_CONSENSUS_AUTOCYCLER (autocycler/compress, autocycler/cluster, autocycler/trim, autocycler/resolve, autocycler/combine) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_CONSENSUS_AUTOCYCLER": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_consensus_autocycler": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_consensus_autocycler", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry). Input files: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,matrix,barcodes,features": null, "sample,bam": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 2}
{"id": "mod_bcftools_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts VCF files (tools: sort)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepmased_predict": "DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED", "biobambam_bammerge": "Merge a list of sorted bam files", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "bcftools_sort": "Sorts VCF files", "atlas_call": "generate VCF file from a BAM file using various calling methods"}}, "target": "bcftools_sort", "target_idx": 3}
{"id": "mod_learnmsa_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align sequences using learnMSA (tools: learnmsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "learnmsa_align": "Align sequences using learnMSA", "jellyfish_dump": "Dumps the results from a jellyfish binary file into a human readable format", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "learnmsa_align", "target_idx": 2}
{"id": "mod_amrfinderplus_update_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify antimicrobial resistance in gene or protein sequences (tools: amrfinderplus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastplong": "Perform adapter/quality trimming and QC on long sequencing reads (ONT, PacBio, etc.)", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "ultra_index": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "amrfinderplus_update", "target_idx": 2}
{"id": "resource_busco_phylogenomics_3", "category": "resource_profiling", "state": {"process": "BUSCO_PHYLOGENOMICS", "tool": "busco/phylogenomics", "description": "Construct species phylogenies using BUSCO proteins"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PHYLOGENOMICS (Construct species phylogenies using BUSCO proteins) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_45", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_mira_influenza_sc2_2_3", "category": "samplesheet_schema", "state": "nextflow run custom/mira-nf --input samplesheet.csv (Assay: Custom MIRA-NF Influenza / SC2 pipeline)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_grabix_check_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Checks if the input file is bgzip compressed or not (tools: grabix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunzip": null, "grabix_check": null, "foldcomp_compress": null, "happy_prepy": null, "bam_subsampledepth_samtools": null}}, "target": "grabix_check", "target_idx": 1}
{"id": "subworkflow_pkg_tiff_segmentation_vpt_2", "category": "subworkflow_packaging", "state": {"subworkflow": "TIFF_SEGMENTATION_VPT", "modules": ["vizgenpostprocessing/preparesegmentation", "vizgenpostprocessing/runsegmentationontile", "vizgenpostprocessing/compiletilesegmentation"], "description": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool"}, "question": {"type": "choice", "instructions": "How should TIFF_SEGMENTATION_VPT (vizgenpostprocessing/preparesegmentation, vizgenpostprocessing/runsegmentationontile, vizgenpostprocessing/compiletilesegmentation) be structured in DSL2?", "criteria": {"Use nf-core subworkflow tiff_segmentation_vpt": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow TIFF_SEGMENTATION_VPT": null}}, "target": "Use nf-core subworkflow tiff_segmentation_vpt", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_11", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_single_hyphen_cli_params_error_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_art_illumina_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simulation tool to generate synthetic Illumina next-generation sequencing reads (tools: art)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"emu/abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads.", "mapdamage2": "Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads ge", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "art/illumina", "target_idx": 4}
{"id": "resource_blast_updateblastdb_5", "category": "resource_profiling", "state": {"process": "BLAST_UPDATEBLASTDB", "tool": "blast/updateblastdb", "description": "Downloads a BLAST database from NCBI"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_UPDATEBLASTDB (Downloads a BLAST database from NCBI) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_6_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,cpg,methylation": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_picard_mergesamfiles_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges multiple BAM files into a single file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "concoct/extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "picard/mergesamfiles": "Merges multiple BAM files into a single file", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "fmhfunprofiler": "Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references."}}, "target": "picard/mergesamfiles", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_17", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_6_4", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Visium spatial transcriptomics with histology image input samplesheet?", "criteria": {"sample,fastq_1,image": null, "sample,fastq_1,fastq_2": null, "sample,image": null, "sample,fastq_1,fastq_2,image,slide,area": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 3}
{"id": "mod_magus_guidetree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multiple Sequence Alignment using Graph Clustering (tools: magus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngscheckmate_fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "fasta_newick_epang_gappa": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in ", "foldmason_createdb": "Creates a database for Foldmason.", "famsa_align": "Aligns sequences using FAMSA", "magus_guidetree": "Multiple Sequence Alignment using Graph Clustering"}}, "target": "magus_guidetree", "target_idx": 4}
{"id": "samplesheet_arch_spatial_visium_0_0", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,fastq_1,image": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "mod_bakta_bakta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotation of bacterial genomes (isolates, MAGs) and plasmids (tools: bakta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/installannotations": null, "nanoplot": null, "agat/spfilterbyorfsize": null, "pcgr/getref": null, "bakta/bakta": null}}, "target": "bakta/bakta", "target_idx": 4}
{"id": "mod_rseqc_innerdistance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate inner distance between read pairs. (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer/pos2bed": null, "rseqc/innerdistance": null, "elprep/filter": null, "transdecoder/predict": null, "eigenstratdatabasetools/eigenstratsnpcoverage": null}}, "target": "rseqc/innerdistance", "target_idx": 1}
{"id": "mod_rseqc_junctionsaturation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: compare detected splice junctions to reference gene model (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc/junctionsaturation": "compare detected splice junctions to reference gene model", "leafcutter/clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter", "tmb/pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "scramble/clusteridentifier": "The cluster_identifier tool of Scramble identifies soft clipped clusters", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes"}}, "target": "rseqc/junctionsaturation", "target_idx": 0}
{"id": "schema_std_rnafusion_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "description": "RNA-seq analysis pipeline for detection of gene-fusions", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnafusion?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 1}
{"id": "samplesheet_arch_cageseq_transcription_4_2", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,tss_bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "resource_agat_spkeeplongestisoform_1", "category": "resource_profiling", "state": {"process": "AGAT_SPKEEPLONGESTISOFORM", "tool": "agat/spkeeplongestisoform", "description": "Filters GFF records to keep only the longest isoform per gene"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPKEEPLONGESTISOFORM (Filters GFF records to keep only the longest isoform per gene) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_fastq_1_0_12", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "mod_gem2_gem2bedmappability_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a mappability file to bedgraph format (tools: gem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge_build": "Build centrifuge database for taxonomic profiling", "gem2_gemindexer": "Create a GEM index from a FASTA file", "gatk4_preprocessintervals": "Prepares bins for coverage collection.", "gem2_gemmappability": "Define the mappability of a reference", "gem2_gem2bedmappability": "Convert a mappability file to bedgraph format"}}, "target": "gem2_gem2bedmappability", "target_idx": 4}
{"id": "mod_bwafastalign_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA-FASTALIGN index for reference genome (tools: bwafastalign)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie/build": "Create bowtie index for reference genome", "bwafastalign/index": "Create BWA-FASTALIGN index for reference genome", "purgedups/pbcstat": "Create read depth histogram and base-level read depth for an assembly based on pacbio data", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "orfm": "A simple and not slow open reading frame (ORF) caller. The goal is to return a FASTA file of open reading fram"}}, "target": "bwafastalign/index", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_27", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_bismark_summary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"salmon_index": "Create index for salmon", "bismark_methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "bismark_summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "parabricks_indexgvcf": "NVIDIA Clara Parabricks GPU-accelerated gvcf indexing tool.", "bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts."}}, "target": "bismark_summary", "target_idx": 2}
{"id": "noul_channel_mix_operator_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_36", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_amulety_antiberta2_2", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTA2", "tool": "amulety/antiberta2", "description": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTA2 (A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_reportho_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core pipeline for comparative analysis of ortholog predictions. Topics: ortholog. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]"}}, "target": "reportho", "target_idx": 7}
{"id": "pipe_all101_longraredisease_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders. Topics: nanopore, pacbio. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": null, "drop": null, "proteogenomicsdb": null, "genomeqc": null, "variantbenchmarking": null, "diaproteomics": null, "pacvar": null, "longraredisease": null, "reportho": null, "nanostring": null}}, "target": "longraredisease", "target_idx": 7}
{"id": "resource_bedtools_shuffle_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHUFFLE", "tool": "bedtools/shuffle", "description": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a genome file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHUFFLE (bedtools shuffle will randomly permute the genomic locations of a feature file a) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_1_3", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,fasta": null, "sample,mzml": null, "sample,raw_file,condition": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "mod_folddisco_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a geometric-hashing index of discontinuous structural motifs from a directory of protein structure files (tools: folddisco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect_xtract": "Queries an NCBI database using an UID", "elprep_filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "mmseqs_createindex": "Creates sequence index for mmseqs database", "folddisco_index": "Build a geometric-hashing index of discontinuous structural motifs from a directory of protein structure files", "custom_getchromsizes": "Generates a FASTA file of chromosome sizes and a fasta index file"}}, "target": "folddisco_index", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wes_pe_5_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Paired-end Whole Exome Sequencing (WES) target capture.", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_genomeassembler_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/genomeassembler. Description: Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/genomeassembler.", "criteria": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,fastq_1,fastq_2,barcode_details": null, "sample,fasta": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "sample,group,ref_fasta,ref_gff,use_ref", "target_idx": 3}
{"id": "mod_opt_track_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: track aligns query probe sequences to any target transcriptome (tools: opt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"opt_track": "track aligns query probe sequences to any target transcriptome", "fasta_index_bismark_bwameth": "Generate index files from reference fasta for bismark and bwameth", "tcoffee_consensus": "Computes a consensus alignment using T_COFFEE", "xeniumranger_relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts.", "opt_flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple"}}, "target": "opt_track", "target_idx": 0}
{"id": "mod_krona_ktupdatetaxonomy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KronaTools Update Taxonomy downloads a taxonomy database (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigslice_downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "krona_ktupdatetaxonomy": "KronaTools Update Taxonomy downloads a taxonomy database", "metaphlan_metaphlan": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "krona_ktupdatetaxonomy", "target_idx": 2}
{"id": "mod_bigslice_downloaddb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module. (tools: bigslice)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "orfm": "A simple and not slow open reading frame (ORF) caller. The goal is to return a FASTA file of open reading fram", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "bigslice_downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "bam_qc_rnaseq": "Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC "}}, "target": "bigslice_downloaddb", "target_idx": 3}
{"id": "mod_quantmsutils_dianncfg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate DIA-NN configuration arguments from enzyme and Unimod modification parameters.\nThis module uses quantms-utils to convert enzyme and modification specifications into DIA-NN-compatible command-line arguments.\nOnly supports Unimod modifications. For custom modifications, pass arguments directly to the DIANN module. (tools: quantms-utils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbccs": null, "parsesdrf/convert": null, "quantmsutils/dianncfg": null, "bcftools/view": null, "dia_proteomics_analysis": null}}, "target": "quantmsutils/dianncfg", "target_idx": 2}
{"id": "mod_clusty_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with millions of objects. (tools: clusty)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond_deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust", "isoseq_cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences", "quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje", "clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "mobsuite_recon": "A tool to reconstruct plasmids in bacterial assemblies"}}, "target": "clusty", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_1_2", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"plate,sample,bam": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,well,fastq": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_cancer_longitudinal_5_2", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Longitudinal cancer monitoring across multiple timepoints.", "criteria": {"sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_tn_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic cancer variant calling with tumor-normal pairs)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_mudskipper_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM files. (tools: mudskipper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mudskipper_index": "Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM fi", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "msisensorpro_pro": "MSIsensor-pro/pro is a tool used to evaluate MSI using single (tumor) sample sequencing data", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "fasta_gtf_bam_rpbp": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). R"}}, "target": "mudskipper_index", "target_idx": 0}
{"id": "mod_bigscape_bigscape_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results. (tools: bigscape)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr_propd": "Perform differential proportionality analysis", "bam_split_by_region": "Split the reads in the input bam by specified genomic region.", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "antismash_antismashlite": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "bigscape_bigscape", "target_idx": 2}
{"id": "mod_seroba_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine Streptococcus pneumoniae serotype from Illumina paired-end reads (tools: seroba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mummer": "MUMmer is a system for rapidly aligning entire genomes", "seroba/run": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "ariba/getref": "Download and prepare database for Ariba analysis", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with"}}, "target": "seroba/run", "target_idx": 1}
{"id": "mod_gcta_keep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a keep file to a dense GRM using `gcta --keep` (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and ", "gcta/keep": "Apply a keep file to a dense GRM using `gcta --keep`", "gcta/calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups", "gcta/adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`", "dshbio/splitbed": "Split features in gzipped BED format"}}, "target": "gcta/keep", "target_idx": 1}
{"id": "resource_bedtools_map_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAP", "tool": "bedtools/map", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAP (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral genome sequencing on Oxford Nanopore MinION / GridION)", "question": {"type": "choice", "instructions": "Which columns are standard for Viral genome sequencing on Oxford Nanopore MinION / GridION input samplesheet?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_pediatric_trio_somatic_1_4", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_5", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_openms_idripper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split a merged identification file into their originating identification files (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat/fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "openms/idripper": "Split a merged identification file into their originating identification files", "bcftools/split": "Split a vcf file into files per chromosome", "snippy/core": "Core-SNP alignment from Snippy outputs", "atlas/splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "openms/idripper", "target_idx": 1}
{"id": "schema_std_provenancereport_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/provenancereport. Description: A simple provenance reporting pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/provenancereport.", "criteria": {"id,path": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "id,path", "target_idx": 0}
{"id": "subworkflow_pkg_bam_qc_rnaseq_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_RNASEQ", "modules": ["preseq/lcextrap", "qualimap/rnaseq", "dupradar", "subread/featurecounts", "custom/multiqccustombiotype", "samtools/sort", "bam_rseqc"], "description": "Run post-alignment QC tools on RNA-seq BAM files including library complexity"}, "question": {"type": "choice", "instructions": "How should BAM_QC_RNASEQ (preseq/lcextrap, qualimap/rnaseq, dupradar, subread/featurecounts, custom/multiqccustombiotype, samtools/sort, bam_rseqc) be structured in DSL2?", "criteria": {"Local subworkflow BAM_QC_RNASEQ": null, "Leave them out": null, "Use nf-core subworkflow bam_qc_rnaseq": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_qc_rnaseq", "target_idx": 2}
{"id": "pipe_all101_readsimulator_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data.. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]"}}, "target": "readsimulator", "target_idx": 7}
{"id": "mod_gstama_polyacleanup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3) (tools: gstama)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gstama/polyacleanup": null, "gstama/merge": null, "samtools/markdup": null, "autocycler/cluster": null, "bedtools/nuc": null}}, "target": "gstama/polyacleanup", "target_idx": 0}
{"id": "mod_lofreq_alnqual_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to for insert base and indel alignment qualities (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/concat": "Concatenate VCF files", "souporcell": "souporcell is a method for clustering mixed-genotype scRNAseq experiments by individual.", "lofreq/alnqual": "Lofreq subcommand to for insert base and indel alignment qualities", "hmmer/eslreformat": "reformats sequence files, see HMMER documentation for details. The module requires that the format is specifie", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "lofreq/alnqual", "target_idx": 2}
{"id": "pipe_all101_epitopeprediction_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A bioinformatics best-practice analysis pipeline for epitope prediction and annotation. Topics: epitope, epitope-prediction, mhc-binding-prediction. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "seqsubmit": "nf-core pipeline for data submission to ENA", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, "}}, "target": "epitopeprediction", "target_idx": 6}
{"id": "samplesheet_arch_bulk_rnaseq_se_4_3", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end FASTQ reads per library?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "resource_bracken_build_0", "category": "resource_profiling", "state": {"process": "BRACKEN_BUILD", "tool": "bracken/build", "description": "Extends a Kraken2 database to be compatible with Bracken"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BUILD (Extends a Kraken2 database to be compatible with Bracken) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_hicar_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hicar", "description": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/hicar?", "criteria": {"fastq_1,fastq_2,group,replicate,md5_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fasta": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null}}, "target": "fastq_1,fastq_2,group,replicate,md5_1", "target_idx": 0}
{"id": "mod_diamond_blastp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a DIAMOND database using blastp mode (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/positionbaseddownsamplesam": "Samples a SAM/BAM/CRAM file using flowcell position information for the best approximation of having sequenced", "bbmap/sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "diamond/blastp": "Queries a DIAMOND database using blastp mode", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "diamond/blastp", "target_idx": 3}
{"id": "resource_busco_busco_2", "category": "resource_profiling", "state": {"process": "BUSCO_BUSCO", "tool": "busco/busco", "description": "Benchmarking Universal Single Copy Orthologs"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_BUSCO (Benchmarking Universal Single Copy Orthologs) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_34", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_pigz_uncompress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: pigz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pigz/uncompress": "write your description here", "crabz/decompress": "Decompress files with crabz", "crabz/compress": "Compress files with crabz", "vcf2zarr/convert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster", "bcftools/mpileup": "Compresses VCF files"}}, "target": "pigz/uncompress", "target_idx": 0}
{"id": "pipe_all101_nanostring_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze An analysis pipeline for Nanostring nCounter expression data.. Topics: nanostring, nanostringnorm. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]"}}, "target": "nanostring", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_2_44", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_octopusv_plotcircos_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file. (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequenzautils_bam2seqz": null, "octopusv_plot": null, "octopusv_plotcircos": null, "happy_happy": null, "octopusv_svcf2bed": null}}, "target": "octopusv_plotcircos", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_2", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_ale_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ALE: assembly likelihood estimator. (tools: ale)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ariba/getref": "Download and prepare database for Ariba analysis", "ale": "ALE: assembly likelihood estimator.", "cooler/dump": "Dump a cooler’s data to a text stream."}}, "target": "ale", "target_idx": 3}
{"id": "subworkflow_pkg_orftable_fasta_gtf_buildorfcatalogue_0", "category": "subworkflow_packaging", "state": {"subworkflow": "ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE", "modules": ["custom/orfnormalise", "custom/orfmerge", "bedtools/getfasta", "seqkit/translate", "mmseqs/easycluster", "custom/orfcollapse"], "description": "Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller"}, "question": {"type": "choice", "instructions": "How should ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE (custom/orfnormalise, custom/orfmerge, bedtools/getfasta, seqkit/translate, mmseqs/easycluster, custom/orfcollapse) be structured in DSL2?", "criteria": {"Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue": null, "Keep the modules in the main workflow": null, "Local subworkflow ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE": null, "Leave them out": null}}, "target": "Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue", "target_idx": 0}
{"id": "field_constraint_strandedness_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "mod_pbsv_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pbsv/call - PacBio structural variant (SV) calling and analysis tools (tools: pbsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "pbsv/call": "pbsv/call - PacBio structural variant (SV) calling and analysis tools", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "fungtion/fungtion": "Predicts fungal effector proteins from protein FASTA sequences using ESM-1b\nprotein language model embeddings "}}, "target": "pbsv/call", "target_idx": 2}
{"id": "mod_mat2json_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converst matlab .mat files into json or csv files. (tools: mat2json)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strdrop/call": "Detect drops in STR coverage", "mat2json": "converst matlab .mat files into json or csv files.", "bcftools/index": "Index VCF tools", "openms/fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "mat2json", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_12", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_metacache_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic profiling database building with MetaCache (tools: metacache)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "quantmsutils/diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils", "metacache/build": "Taxonomic profiling database building with MetaCache", "miniprot/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "metacache/build", "target_idx": 2}
{"id": "local_subworkflow_preparereports_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should PREPAREREPORTS (custom/preparereports, multiqc) be built?", "criteria": {"Use nf-core subworkflow preparereports": null, "Leave them out": null, "Local subworkflow PREPAREREPORTS": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 2}
{"id": "resource_adapterremoval_5", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVAL", "tool": "adapterremoval", "description": "Trim sequencing adapters and collapse overlapping reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVAL (Trim sequencing adapters and collapse overlapping reads) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_viralrecon_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Assembly and intrahost/low-frequency variant calling for viral samples. Topics: amplicon, artic, assembly, covid-19, covid19, illumina. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]"}}, "target": "viralrecon", "target_idx": 4}
{"id": "noul_executor_support_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_fusioninspector_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Validation of Fusion Transcript Predictions (tools: fusioninspector)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusioninspector": "Validation of Fusion Transcript Predictions", "parabricks/starfusion": "This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. Thi", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "sortmerna": "Local sequence alignment tool for filtering, mapping and clustering.", "fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data"}}, "target": "fusioninspector", "target_idx": 0}
{"id": "mod_fastqscan_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FASTQ summary statistics in JSON format (tools: fastqscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscan": null, "bamtofastq10x": null, "art/illumina": null, "abricate/run": null, "agrvate": null}}, "target": "fastqscan", "target_idx": 0}
{"id": "resource_bff_0", "category": "resource_profiling", "state": {"process": "BFF", "tool": "bff", "description": "Generating cell hashing calls from a matrix of count data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFF (Generating cell hashing calls from a matrix of count data.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_vt_decomposeblocksub_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decomposes biallelic block substitutions into its constituent SNPs. (tools: vt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt/decomposeblocksub": "Decomposes biallelic block substitutions into its constituent SNPs.", "snpsites": "Rapidly extracts SNPs from a multi-FASTA alignment.", "vt/normalize": "normalizes variants in a VCF file", "proseg/proseg": "Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics.", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D"}}, "target": "vt/decomposeblocksub", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Metagenomic MAG assembly with comparative groups", "data_format": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "mod_deepbgc_pipeline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepBGC detects BGCs in bacterial and fungal genomes using deep learning. (tools: deepbgc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_tsv2exprofiledb": null, "antismash_antismashlite": null, "deepbgc_pipeline": null, "bigscape_bigscape": null, "miniprot_align": null}}, "target": "deepbgc_pipeline", "target_idx": 2}
{"id": "intent_build_pipeline_4", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_octopusv_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot structural variant statistics using octopusv stat output (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op", "smncopynumbercaller": "tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion ", "hamronization/fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "octopusv/plot": "Plot structural variant statistics using octopusv stat output", "gfatools/stat": "Summary statistics for GFA files"}}, "target": "octopusv/plot", "target_idx": 3}
{"id": "mod_seqkit_stats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: simple statistics of FASTA/Q files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_grep": "Select sequences from a large file based on name/ID", "seqkit_head": "Subset FASTA/FASTQ files to some number of sequences", "seqkit_stats": "simple statistics of FASTA/Q files", "vcf_filter_bcftools_ensemblvep": "Filter VCF file with bcftools and filter_vep", "plink2_extract": "Subset plink pfiles with a text file of variant identifiers"}}, "target": "seqkit_stats", "target_idx": 2}
{"id": "resource_bowtie_build_4", "category": "resource_profiling", "state": {"process": "BOWTIE_BUILD", "tool": "bowtie/build", "description": "Create bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_BUILD (Create bowtie index for reference genome) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_1_2", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs", "pipeline": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_6_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "MUTECT2", "library_inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic tumor-normal calling from pre-aligned BAM files input samplesheet?", "criteria": {"patient,sample,status,bam,bai": null, "sample,vcf": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "resource_bbmap_filterbyname_4", "category": "resource_profiling", "state": {"process": "BBMAP_FILTERBYNAME", "tool": "bbmap/filterbyname", "description": "Filter out sequences by sequence header name(s)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_FILTERBYNAME (Filter out sequences by sequence header name(s)) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_26", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_deeptools_plotheatmap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: plots values produced by deeptools_computematrix as a heatmap (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "deeptools_plotheatmap": "plots values produced by deeptools_computematrix as a heatmap", "hmmer_eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi", "blobtk_plot": "Creates differing styles of blobplots depending on provided arguments.", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}}, "target": "deeptools_plotheatmap", "target_idx": 1}
{"id": "mod_krakentools_kreport2krona_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes a Kraken report file and prints out a krona-compatible TEXT file (tools: krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krona_ktupdatetaxonomy": "KronaTools Update Taxonomy downloads a taxonomy database", "scds": "Module to use scds for doublet scoring", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "krakentools_kreport2krona": "Takes a Kraken report file and prints out a krona-compatible TEXT file", "fgumi_zipper": "Zip an unmapped UMI BAM together with its aligned BAM using fgumi"}}, "target": "krakentools_kreport2krona", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_1_5", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "field_constraint_bam_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Genome analysis from reference-compressed CRAM files", "data_format": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,cram": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "mod_deeptools_plotcorrelation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualises sample correlations using a compressed matrix generated by mutlibamsummary or multibigwigsummary as input. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/plotpca": null, "deeptools/plotheatmap": null, "bedtools/makewindows": null, "gatk4/addorreplacereadgroups": null, "deeptools/plotcorrelation": null}}, "target": "deeptools/plotcorrelation", "target_idx": 4}
{"id": "mod_picard_renamesampleinvcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: changes name of sample in the vcf file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_renamesampleinvcf": null, "cooltools_eigscis": null, "samtools_fastq": null, "picard_addorreplacereadgroups": null, "picard_createsequencedictionary": null}}, "target": "picard_renamesampleinvcf", "target_idx": 0}
{"id": "pipe_all101_rangeland_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple steps to arrive at a set of trend files related to land-cover changes.. Topics: earth-observation, landsat, satellite-imagery, spectral-unmixing, trend-analysis, trends. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnasplice": null, "imcyto": null, "rangeland": null, "viralintegration": null, "readsimulator": null}}, "target": "rangeland", "target_idx": 2}
{"id": "mod_mitohifi_findmitoreference_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download a mitochondrial genome to be used as reference for MitoHiFi.\n\nNOTE: An optional NCBI API key can be supplied to MITOHIFI_FINDMITOREFERENCE.\nThis should be set using Nextflow's secrets functionality:\n\n`nextflow secrets set NCBI_API_KEY <key>`\n\nSee https://www.nextflow.io/docs/latest/secrets.html for more information. (tools: findMitoReference.py)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect/xtract": "Queries an NCBI database using an UID", "bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file", "mitohifi/findmitoreference": "Download a mitochondrial genome to be used as reference for MitoHiFi.\n\nNOTE: An optional NCBI API key can be s", "bedtools/subtract": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining po", "svdss/index": "Index a reference genome FASTA file using SVDSS (via ropebwt3), producing either an FMD or FMR index for use w"}}, "target": "mitohifi/findmitoreference", "target_idx": 2}
{"id": "schema_std_ribomsqc_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/ribomsqc. Description: QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/ribomsqc.", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,seq_data,pbi,start_from": null, "id,raw_file": null, "sample_id,bam,vcf,library_id,lane": null}}, "target": "id,raw_file", "target_idx": 2}
{"id": "mod_getorganelle_fromreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembles organelle genomes from genomic data (tools: getorganelle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"grimer": "Generates an interactive HTML dashboard integrating taxonomy,\nannotation, and metadata to detect contamination", "getorganelle_fromreads": "Assembles organelle genomes from genomic data", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "gt_suffixerator": "Computes enhanced suffix array using GenomeTools gt-suffixerator utility", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "getorganelle_fromreads", "target_idx": 1}
{"id": "mod_samtools_flagstat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kraken2_kraken2": "Classifies metagenomic sequence data", "ltrretriever_lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric ", "bamtools_stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "samtools_flagstat": "Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type", "amulety_balmpaired": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}}, "target": "samtools_flagstat", "target_idx": 3}
{"id": "noul_subworkflow_structural_blocks_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bismark_deduplicate_2", "category": "resource_profiling", "state": {"process": "BISMARK_DEDUPLICATE", "tool": "bismark/deduplicate", "description": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_DEDUPLICATE (Removes alignments to the same position in the genome\nfrom the Bismark mapping o) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_genmod_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: for annotating regions, frequencies, cadd scores (tools: genmod)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"echtvar/anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "bcftools/annotate": "Add or remove annotations.", "genmod/annotate": "for annotating regions, frequencies, cadd scores", "genomad/download": "Download geNomad databases and related files", "snpeff/download": "Genetic variant annotation and functional effect prediction toolbox"}}, "target": "genmod/annotate", "target_idx": 2}
{"id": "resource_bwafastalign_index_5", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_INDEX", "tool": "bwafastalign/index", "description": "Create BWA-FASTALIGN index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_INDEX (Create BWA-FASTALIGN index for reference genome) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_high", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_35", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_hlala_preparegraph_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pre-compute the graph index structure. (tools: hlala)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hlala_preparegraph": "Pre-compute the graph index structure.", "hlala_typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "t1k_run": "write your description here", "diamond_cluster": "calculate clusters of highly similar sequences", "ichorcna_run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti"}}, "target": "hlala_preparegraph", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_filter_bcftools_ensemblvep_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_FILTER_BCFTOOLS_ENSEMBLVEP", "modules": ["bcftools/view", "ensemblvep/filtervep", "htslib/bgziptabix"], "description": "Filter VCF file with bcftools and filter_vep"}, "question": {"type": "choice", "instructions": "How should VCF_FILTER_BCFTOOLS_ENSEMBLVEP (bcftools/view, ensemblvep/filtervep, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow VCF_FILTER_BCFTOOLS_ENSEMBLVEP": null, "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep", "target_idx": 2}
{"id": "noul_channel_filter_operator_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Parse Biosciences Split-seq combinatorial barcoding. Input files: Combinatorial split-pool barcoded FASTQs with subpool annotations.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bedtools_groupby_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GROUPBY", "tool": "bedtools/groupby", "description": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another column."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GROUPBY (Groups features in a BED file by given column(s) and computes summary statistics) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_7", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Multi-lane Illumina sequencing run of clinical samples)", "question": {"type": "choice", "instructions": "Which columns are standard for Multi-lane Illumina sequencing run of clinical samples input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_kmcp_search_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search sequences against database (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "kmcp/search": "Search sequences against database", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "holodeck/methylate": "Generate a methylation-annotated VCF from a reference genome with holodeck", "perbase": "Per-base metrics on BAM/CRAM files."}}, "target": "kmcp/search", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_3_0", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for FAIRE-seq / DNAse-seq open chromatin profiling with entry step FASTQC.", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/riboseq --input samplesheet.csv (Assay: Ribosome profiling (Ribo-seq) footprint sequencing)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_savana_to_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tumour-only somatic SV calling with optional copy-number analysis in SAVANA (tools: savana)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"muse_sump": "Computes tier-based cutoffs from a sample-specific error model which is generated by muse/call and reports the", "caddsv_get": "Download CADD-SV annotation resources or SegmentNT model files.", "seqtk_trim": "Trim low quality bases from FastQ files", "savana_to": "Tumour-only somatic SV calling with optional copy-number analysis in SAVANA", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "savana_to", "target_idx": 3}
{"id": "local_subworkflow_nextclade_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should NEXTCLADE (nextclade/run) be built?", "criteria": {"Use nf-core subworkflow nextclade": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow NEXTCLADE": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 3}
{"id": "field_constraint_status_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "status", "validation_type": "somatic_status_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'status'.", "criteria": {"pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "resource_bedtools_flank_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_FLANK", "tool": "bedtools/flank", "description": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_FLANK (Creates two new flanking intervals for each interval in a BED/GFF/VCF file.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_file_pairing_in_channel_tuples_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fastqutils_info_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs quality control of FASTQ files (tools: fastqutils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strelka/germline": "Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation", "fastqutils/info": "Performs quality control of FASTQ files", "ariba/getref": "Download and prepare database for Ariba analysis", "ariba/run": "Query input FASTQs against Ariba formatted databases", "zip": "Compress file lists to produce ZIP archive files"}}, "target": "fastqutils/info", "target_idx": 1}
{"id": "pipe_all101_pangenome_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609.. Topics: pangenome. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a"}}, "target": "pangenome", "target_idx": 3}
{"id": "pipe_all101_nascent_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Nascent Transcription Processing Pipeline. Topics: gro-seq, nascent, pro-seq, rna, transcription, tss. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "seqsubmit": "nf-core pipeline for data submission to ENA", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab"}}, "target": "nascent", "target_idx": 5}
{"id": "resource_antismash_antismashlitedownloaddatabases_1", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES", "tool": "antismash/antismashlitedownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_variantbenchmarking_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for benchmark. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "seqsubmit": "nf-core pipeline for data submission to ENA", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]"}}, "target": "variantbenchmarking", "target_idx": 0}
{"id": "samplesheet_arch_germline_lane_split_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Multi-lane Illumina sequencing run of clinical samples. Input files: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Multi-lane Illumina sequencing run of clinical samples.", "criteria": {"sample,bam": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_strandedness_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"format: file-path": null, "pattern: ^[0-9]+$": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "mod_plink2_pmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "icountmini/peaks": "Runs iCount peaks on a BED file of crosslinks", "graphmap2/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "plink2/remove": "Remove samples from a plink2 dataset", "plink2/pca": "Perform PCA analysis using PLINK"}}, "target": "plink2/pmerge", "target_idx": 0}
{"id": "core_tool_quast_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Evaluate, compare, and compute quality metrics (N50, L50, misassemblies, completeness) for draft genome assemblies against reference genomes.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"multiqc": "MultiQC report", "checkm": "Metagenome quality", "busco": "Benchmark universal single-copy orthologs", "quast": "Quality Assessment Tool for Genome Assemblies evaluating contigs metrics (N50, misassemblies)", "mummer": "Alignment tool"}}, "target": "quast", "target_idx": 3}
{"id": "mod_vcflib_vcffixup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a VCF stream where AC and NS have been generated for each record using sample genotypes. (tools: vcflib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "vcflib_vcffixup": "Generates a VCF stream where AC and NS have been generated for each record using sample genotypes.", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "gatk4_germlinecnvcaller": "Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPlo"}}, "target": "vcflib_vcffixup", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_5_5", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking.", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_genrich_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Peak-calling for ChIP-seq and ATAC-seq enrichment experiments (tools: genrich)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genrich": null, "ngsbits_rohhunter": null, "pints_caller": null, "getorganelle_config": null, "epic2_epic2": null}}, "target": "genrich", "target_idx": 0}
{"id": "mod_deacon_indexdiff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subtract minimizers in deacon index (or fasta file) from another index (A - B) (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon_indexdiff": null, "repeatmasker_rmouttogff3": null, "bowtie_build": null, "bedtools_bamtobed": null, "bbmap_index": null}}, "target": "deacon_indexdiff", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_48", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_5_3", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: FAIRE-seq / DNAse-seq open chromatin profiling.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_cutandrun_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay": "cutandrun pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/cutandrun (Analysis pipeline for CUT&RUN and CUT&TAG experiments that i)?", "criteria": {"id,taxid,fasta_dna,fasta_aa": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,tools,file,index": null, "fastq_1,fastq_2,group,replicate,control": null}}, "target": "fastq_1,fastq_2,group,replicate,control", "target_idx": 3}
{"id": "mod_proteinortho_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Proteinortho is a tool to detect orthologous genes within different species. (tools: proteinortho)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"prokka": "Whole genome annotation of small genomes (bacterial, archeal, viral)", "syri": "Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearran", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "proteinortho": "Proteinortho is a tool to detect orthologous genes within different species.", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID"}}, "target": "proteinortho", "target_idx": 3}
{"id": "noul_channel_operator_map_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_mira_influenza_sc2_5_5", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "template": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline custom/mira-nf, determine the input samplesheet column structure for: Custom MIRA-NF Influenza / SC2 pipeline.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_ldak_kvikstep1_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run LDAK-KVIK step 1 to fit the genome-wide model and emit the minimal prediction artifact tuple consumed by ldak/kvikstep2 (tools: ldak6)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_collate": "shuffles and groups reads together by their names", "regenie_runl1": "Finish REGENIE step 1 from split level-0 prediction files", "ldak_thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "rseqc_inferexperiment": "Infer strandedness from sequencing reads", "ldak_kvikstep1": "Run LDAK-KVIK step 1 to fit the genome-wide model and emit the minimal prediction artifact tuple consumed by l"}}, "target": "ldak_kvikstep1", "target_idx": 4}
{"id": "mod_atlas_recal_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gives an estimation of the sequencing bias based on known invariant sites (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "atlas_recal": "Gives an estimation of the sequencing bias based on known invariant sites", "foldmason_msa2lddtreport": "Renders a visualization report using foldmason", "fastq_align_dedup_bwamem": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate", "atlas_call": "generate VCF file from a BAM file using various calling methods"}}, "target": "atlas_recal", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_0_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Genome analysis from reference-compressed CRAM files. Input files: Coordinate-sorted CRAM alignments with companion CRAI indexes.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,cram": null, "sample,bam,bai": null, "sample,cram,crai": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "mod_spaceranger_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data (tools: spaceranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "last/postmask": "Post-alignment masking", "spaceranger/count": "Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "vcfpgloader/load": "High-performance VCF to PostgreSQL loader using asyncpg for bulk variant ingestion"}}, "target": "spaceranger/count", "target_idx": 2}
{"id": "resource_bacphlip_2", "category": "resource_profiling", "state": {"process": "BACPHLIP", "tool": "bacphlip", "description": "A bacteriophage lifestyle prediction tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACPHLIP (A bacteriophage lifestyle prediction tool) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_5_5", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "template": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cageseq, determine the input samplesheet column structure for: CAGE-seq 5-prime capped transcript end sequencing.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_clustalo_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align sequences using Clustal Omega (tools: clustalo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "clustalo_align": "Align sequences using Clustal Omega", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "catpack_summarise": "Summarises results from CAT/BAT/RAT classification steps"}}, "target": "clustalo_align", "target_idx": 2}
{"id": "resource_angsd_docounts_5", "category": "resource_profiling", "state": {"process": "ANGSD_DOCOUNTS", "tool": "angsd/docounts", "description": "Calculates base frequency statistics across reference positions from BAM."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOCOUNTS (Calculates base frequency statistics across reference positions from BAM.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_status_1_9", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "mod_platypus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Platypus is a tool that efficiently and accurately calling genetic variants from next-generation DNA sequencing data (tools: platypus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ferrohgvs/normalize": "Normalize HGVS variant descriptions to canonical form with ferro", "clair3": "Clair3 is a germline small variant caller for long-reads", "fasta_classify_catpack": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack).", "gedi/indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "platypus": "Platypus is a tool that efficiently and accurately calling genetic variants from next-generation DNA sequencin"}}, "target": "platypus", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_0_1", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_mafft_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare channels for running MAFFT/align (tools: mafft_align)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mafft_align": "Multiple sequence alignment using MAFFT", "foldmason/createdb": "Creates a database for Foldmason.", "famsa/guidetree": "Renders a guidetree in famsa", "samtools/idxstats": "Reports alignment summary statistics for a BAM/CRAM/SAM file", "samtools/quickcheck": "Quickly check that input files appear to be intact. Checks that beginning of the file contains a valid header "}}, "target": "mafft_align", "target_idx": 0}
{"id": "mod_ucsc_gtftogenepred_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert GTF files to GenePred format (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "custom/filterdifferentialtable": "Filters a differential expression table based on logFC and adjusted p-value thresholds", "ucsc/gtftogenepred": "Convert GTF files to GenePred format", "leviosam2/index": "Index chain files for lift over"}}, "target": "ucsc/gtftogenepred", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: ATAC-seq chromatin accessibility with biological replicates)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "schema_std_evexplorer_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/evexplorer", "description": "nf-core/evexplorer is a pipeline for analyzing RNA data from extracellular vesicles, compatible with technologies such as nextflex, comboSeq, and ONT with further support forthcoming. evexplorer handles QC, expressed region detection, library size normalization and Differential RNA Expression (DRE)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/evexplorer?", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq_1": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null}}, "target": "sample,fastq_1,fastq_2,batch,condition", "target_idx": 0}
{"id": "noul_channel_join_operator_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_allelecounter_1", "category": "resource_profiling", "state": {"process": "ALLELECOUNTER", "tool": "allelecounter", "description": "Generates a count of coverage of alleles"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALLELECOUNTER (Generates a count of coverage of alleles) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_5_2", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification", "pipeline": "nf-core/hic"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/hic, determine the input samplesheet column structure for: Hi-C chromosome conformation capture mapping.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_expected_cells_0_3", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "noul_module_metadata_propagation_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "schema_std_scrnaseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "description": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/scrnaseq?", "criteria": {"ID,R1,R2,LongFastQ,Fast5": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "patient,sample,vcf,status,cna": null}}, "target": "sample,fastq_1,fastq_2,fastq_barcode,expected_cells", "target_idx": 1}
{"id": "resource_ampir_3", "category": "resource_profiling", "state": {"process": "AMPIR", "tool": "ampir", "description": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ampir uses a supervised statistical machine learning approach to predict AMPs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPIR (A fast and user-friendly method to predict antimicrobial peptides (AMPs) from an) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_backsub_3", "category": "resource_profiling", "state": {"process": "BACKSUB", "tool": "backsub", "description": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACKSUB (Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data.) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "core_tool_spades_metaspades_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? De novo assembler specifically optimized for complex microbial metagenomic mixtures, recovering contigs across unequal coverage depths.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"unicycler": "Hybrid assembler", "spades_metaspades": "metaSPAdes is a sub-tool of SPAdes designed for metagenomics assembly", "flye": "Long read assembler", "canu": "Long read assembler", "megahit": "Metagenomic assembler"}}, "target": "spades_metaspades", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/dualrnaseq --input samplesheet.csv (Assay: Dual RNA-seq simultaneous host and pathogen transcriptomics)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_2", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_core10_mag_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? De novo assembly and binning of metagenomic contigs across short and long reads into Metagenome-Assembled Genomes.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": null, "sarek": null, "rnaseq": null, "chipseq": null, "taxprofiler": null, "viralrecon": null, "mag": null, "atacseq": null, "eager": null, "scrnaseq": null}}, "target": "mag", "target_idx": 6}
{"id": "intent_debug_error_12", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "debug_error", "target_idx": 2}
{"id": "resource_bwa_samse_0", "category": "resource_profiling", "state": {"process": "BWA_SAMSE", "tool": "bwa/samse", "description": "Convert bwa SA coordinate file to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMSE (Convert bwa SA coordinate file to SAM format) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_high", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_28", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_tidk_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search` (tools: tidk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "tidk/plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "sawfish/discover": "SV candidate discovery from PacBio HiFi data", "slimfastq": "Fast, efficient, lossless compression of FASTQ files."}}, "target": "tidk/plot", "target_idx": 2}
{"id": "field_constraint_strandedness_0_13", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "mod_tetranscripts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs TEtranscripts which summarises transposable element content of a bam file. (tools: tetranscripts)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qualimap_bamqccram": null, "ngscheckmate_fastq": null, "tetranscripts": null, "ciri2": null, "arcane_filter": null}}, "target": "tetranscripts", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_23", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "subworkflow_pkg_bam_dedup_stats_samtools_umitools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS", "modules": ["umitools/dedup", "samtools/index", "samtools/view", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS (umitools/dedup, samtools/index, samtools/view, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_dedup_stats_samtools_umitools": null, "Local subworkflow BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umitools", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_strandedness_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "mod_pbsv_discover_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pbsv - PacBio structural variant (SV) signature discovery tool (tools: pbsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ferrohgvs_parse": null, "graphtyper_genotype": null, "pbsv_discover": null, "sentieon_coveragemetrics": null, "strdrop_call": null}}, "target": "pbsv_discover", "target_idx": 2}
{"id": "field_constraint_bam_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "mod_samtools_bgzip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldcomp_compress": "Efficient compression tool for protein structures", "pairix": "a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates", "gunzip": "Compresses and decompresses files.", "kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "samtools_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP"}}, "target": "samtools_bgzip", "target_idx": 4}
{"id": "field_constraint_bam_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "mod_gcta_makebksparse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a sparse GRM from a dense GRM for downstream fastGWA analyses (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"flye": null, "gcta_makebksparse": null, "gcta_fastgwa": null, "gcta_adjustgrm": null, "gatk4_filtermutectcalls": null}}, "target": "gcta_makebksparse", "target_idx": 1}
{"id": "resource_abricate_run_4", "category": "resource_profiling", "state": {"process": "ABRICATE_RUN", "tool": "abricate/run", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_RUN (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_26", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_core10_scrnaseq_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Single-cell gene expression analysis for 10x Genomics Chromium data from FASTQ generation to UMI counts and Seurat matrices.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "scrnaseq", "target_idx": 9}
{"id": "mod_fairy_coverage_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a MetaBAT2-compatible TSV with per-contig\nmean depth and variance columns. (tools: fairy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fairy/coverage": "Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a Meta", "umitools/dedup": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "cnvkit/target": "Transform bait intervals into targets more suitable for CNVkit."}}, "target": "fairy/coverage", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_16", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "pipe_all101_hicar_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for atac. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "callingcards": "A pipeline for processing calling cards data", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c"}}, "target": "hicar", "target_idx": 1}
{"id": "local_subworkflow_variantsofint_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should VARIANTSOFINT (custom/variantsofint) be built?", "criteria": {"Use nf-core subworkflow variantsofint": null, "Local subworkflow VARIANTSOFINT": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_45", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_seqtk_sample_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subsample reads from FASTQ files (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"summarizedexperiment_summarizedexperiment": "SummarizedExperiment container", "seqkit_sample": "Sample sequences from FASTA/FASTQ files by number or proportion", "samtools_markdup": "mark duplicate alignments in a coordinate sorted file", "seqtk_sample": "Subsample reads from FASTQ files", "merquryfk_hapmaker": "Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables"}}, "target": "seqtk_sample", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_5", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_force_cube_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spatially restrict downstream analysis tasks. (tools: force)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"force/cube": null, "stacks/refmap": null, "hmmer/eslalimask": null, "gcta/makegrmpart": null, "repeatmasker/repeatmasker": null}}, "target": "force/cube", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_28", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_metacache_query_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metacache query command for taxonomic classification (tools: metacache)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sgdemux": null, "amps": null, "metacache_query": null, "argnorm": null, "bwamem2_mem": null}}, "target": "metacache_query", "target_idx": 2}
{"id": "mod_adapterremovalfixprefix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with DeDup. (tools: adapterremovalfixprefix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_fasta_cluster": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file.", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "propr/propd": "Perform differential proportionality analysis", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "ariba/getref": "Download and prepare database for Ariba analysis"}}, "target": "adapterremovalfixprefix", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_1_6", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_2", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_0_3", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "template": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "intent_debug_error_24", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "debug_error", "target_idx": 1}
{"id": "mod_last_mafswap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reorder alignments in a MAF file (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/cluster": "calculate clusters of highly similar sequences", "minimap2/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "last/lastal": "Aligns query sequences to target sequences indexed with lastdb", "last/split": "Find split or spliced alignments in a MAF file", "last/mafswap": "Reorder alignments in a MAF file"}}, "target": "last/mafswap", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_2_43", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "intent_ask_question_4", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 0}
{"id": "mod_bedgovcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a BED file to a VCF file according to a YAML config (tools: bedgovcf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan_cazymeannotation": "CAZyme annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (", "ska_fasta": "Create genome sketch using split k-mers", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "bedops_gtf2bed": "Convert gtf format to bed format", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file"}}, "target": "bedgovcf", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq", "data_format": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bowtie_align_0", "category": "resource_profiling", "state": {"process": "BOWTIE_ALIGN", "tool": "bowtie/align", "description": "Align reads to a reference genome using bowtie"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_ALIGN (Align reads to a reference genome using bowtie) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_0_0", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions", "pipeline": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,mzml": null, "sample,raw_file,condition": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wes_pe_0_4", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_5_3", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Tumor-only somatic variant calling without matched normal.", "criteria": {"patient,normal,tumor": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wes_pe_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Paired-end Whole Exome Sequencing (WES) target capture)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_nanomonsv_get_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call somatic structural variants with nanomonsv get using tumor/control\nparse outputs and a reference genome. (tools: nanomonsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dysgu/run": null, "bacphlip": null, "nanomonsv/get": null, "annotsv/installannotations": null, "semibin/singleeasybin": null}}, "target": "nanomonsv/get", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_46", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_adapterremoval_1", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVAL", "tool": "adapterremoval", "description": "Trim sequencing adapters and collapse overlapping reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVAL (Trim sequencing adapters and collapse overlapping reads) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_agat_spextractsequences_0", "category": "resource_profiling", "state": {"process": "AGAT_SPEXTRACTSEQUENCES", "tool": "agat/spextractsequences", "description": "This script extracts sequences in fasta format according to features described\nin a gff file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPEXTRACTSEQUENCES (This script extracts sequences in fasta format according to features described\ni) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic cancer variant calling with tumor-normal pairs)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic cancer variant calling with tumor-normal pairs.", "criteria": {"patient,sample,status,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_angsd_docounts_4", "category": "resource_profiling", "state": {"process": "ANGSD_DOCOUNTS", "tool": "angsd/docounts", "description": "Calculates base frequency statistics across reference positions from BAM."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOCOUNTS (Calculates base frequency statistics across reference positions from BAM.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bamstats_generalstats_3", "category": "resource_profiling", "state": {"process": "BAMSTATS_GENERALSTATS", "tool": "bamstats/generalstats", "description": "write your description here"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMSTATS_GENERALSTATS (write your description here) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bismark_report_1", "category": "resource_profiling", "state": {"process": "BISMARK_REPORT", "tool": "bismark/report", "description": "Collects bismark alignment reports"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_REPORT (Collects bismark alignment reports) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_references_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core/references is a bioinformatics pipeline that build references, for multiple use cases. Topics: genome, references, reproducibility. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pacvar": null, "bactmap": null, "smrnaseq": null, "references": null, "rangeland": null}}, "target": "references", "target_idx": 3}
{"id": "field_constraint_status_2_14", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "resource_bio2zarr_vcfpartition_4", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCFPARTITION", "tool": "bio2zarr/vcfpartition", "description": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCFPARTITION (Outputs a set of region strings that partition indexed VCF/BCF files for paralle) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_bam_stringtie_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a unified annotation. (tools: bam_stringtie_merge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"disambiguate": "Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ fi", "learnmsa/align": "Align sequences using learnMSA", "gatk4/filtervarianttranches": "Apply tranche filtering", "bam_stringtie_merge": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a ", "arriba/arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}}, "target": "bam_stringtie_merge", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_39", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_wisecondorx_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert and filter aligned reads to .npz (tools: wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wisecondorx/convert": "Convert and filter aligned reads to .npz", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "motus/preplong": "Taxonomic meta-omics profiling using universal marker genes", "wipertools/fastqgather": "A tool of the wipertools suite that merges FASTQ chunks produced by wipertools_fastqscatter", "ascat": "copy number profiles of tumour cells."}}, "target": "wisecondorx/convert", "target_idx": 0}
{"id": "pipe_all101_funcscan_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for amp analysis? Specific context: (Meta-)genome screening for functional and natural product gene sequences. Topics: amp, amr, antibiotic-resistance, antimicrobial-peptides, antimicrobial-resistance-genes, arg. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]"}}, "target": "funcscan", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Paired-end Whole Exome Sequencing (WES) target capture)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Paired-end Whole Exome Sequencing (WES) target capture.", "criteria": {"sample,bam,bai": null, "sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_tcoffee_extractfrompdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reformats the header of PDB files with t-coffee (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_extractfrompdb": null, "fgbio_copyumifromreadname": null, "octopusv_svcf2bed": null, "folddisco_query": null, "folddisco_index": null}}, "target": "tcoffee_extractfrompdb", "target_idx": 0}
{"id": "intent_ask_question_18", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_34", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_2_5", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_30", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_vizgenpostprocessing_preparesegmentation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module prepares the specification JSON file for Vizgen's post-processing tool\ncell segmentation workflow. (tools: vizgenpostprocessing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"syri": "Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearran", "tiff_segmentation_vpt": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool", "rpbp_estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "baysor_run": "Bayesian segmentation of spatial transcriptomics data.", "vizgenpostprocessing_preparesegmentation": "The module prepares the specification JSON file for Vizgen's post-processing tool\ncell segmentation workflow."}}, "target": "vizgenpostprocessing_preparesegmentation", "target_idx": 4}
{"id": "pipe_all101_ampliseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Amplicon sequencing analysis workflow using DADA2 and QIIME2. Topics: 16s, 18s, amplicon-sequencing, edna, illumina, iontorrent. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ampliseq": null, "metapep": null, "mag": null, "denovotranscript": null, "genomeqc": null, "references": null, "pairgenomealign": null, "demo": null, "seqsubmit": null, "pangenome": null}}, "target": "ampliseq", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/diaproteomics --input samplesheet.csv (Assay: Data-Independent Acquisition (DIA) quantitative mass spectrometry)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/diaproteomics, determine the input samplesheet column structure for: Data-Independent Acquisition (DIA) quantitative mass spectrometry.", "criteria": {"sample,peptides_tsv": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "noul_modular_subworkflow_composition_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_3_2", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Longitudinal cancer monitoring across multiple timepoints with entry step FASTQC.", "criteria": {"sample,timepoint,fastq": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_channel_factory_inside_process_body_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_1_29", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_vcf_impute_beagle5_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow\ntakes VCF files, phased reference panel, genetic maps and chunks region to perform imputation\nand outputs phased and imputed VCF files.\nMeta map of all channels, except ch_input, will be used to perform joint operations.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: vcf_impute_beagle5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_impute_beagle5": "Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow\ntakes VCF files, phased reference pane", "carveme/carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "bcftools/annotate": "Add or remove annotations.", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "samtools/convert": "convert and then index CRAM -> BAM or BAM -> CRAM file"}}, "target": "vcf_impute_beagle5", "target_idx": 0}
{"id": "mod_mirtop_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category. (tools: mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop/counts": null, "fcs/fcsadaptor": null, "samplesheetparser/info": null, "mirtop/stats": null, "mirtop/export": null}}, "target": "mirtop/stats", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Metagenomic MAG assembly with comparative groups", "data_format": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Metagenomic MAG assembly with comparative groups with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "mod_sequali_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sequence quality metrics for FASTQ and uBAM files. (tools: sequali)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ucsc_bedclip": "Remove lines from bed file that refer to off-chromosome locations.", "gens_preparecovandbaf": "Tools for preparing inputs for visualization in Gens", "pharmcat_vcfpreprocessor": "The PharmCAT VCF Preprocessor is a script that can pre-process VCF files for PharmCAT to make sure the VCF fil", "genmap_index": "create index file for genmap", "sequali": "Sequence quality metrics for FASTQ and uBAM files."}}, "target": "sequali", "target_idx": 4}
{"id": "resource_bcftools_filter_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_FILTER", "tool": "bcftools/filter", "description": "Filters VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_FILTER (Filters VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_krakenuniq_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download and build (custom) KrakenUniq databases (tools: krakenuniq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "hmmer/jackhmmer": "iterative searches to detect distant homologs by refining an HMM profile from hits", "cellrangerarc/mkgtf": "Module to build a filtered gtf needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkgtf ", "krakenuniq/build": "Download and build (custom) KrakenUniq databases", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}}, "target": "krakenuniq/build", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_1_2", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_seqinspector_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/seqinspector. Description: Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput. .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/seqinspector.", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "sample,fastq_1,fastq_2,barcode_details": null, "sample,bundle,image": null, "sample,fastq_1,fastq_2,rundir,tags": null}}, "target": "sample,fastq_1,fastq_2,rundir,tags", "target_idx": 3}
{"id": "samplesheet_arch_mira_influenza_sc2_4_0", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels", "pipeline": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end surveillance FASTQs from respiratory pathogen panels?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_ribomsqc_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralmetagenome": null, "proteinfamilies": null, "molkart": null, "ribomsqc": null, "denovotranscript": null}}, "target": "ribomsqc", "target_idx": 3}
{"id": "mod_utils_annotation_cache_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Check the path to the annotation cache depending if local or on the cloud, or using annotation-cache itself (tools: utils_annotation_cache)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_annotate_ensemblvep": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file", "utils_annotation_cache": "Check the path to the annotation cache depending if local or on the cloud, or using annotation-cache itself", "upd": "Simple software to call UPD regions from germline exome/wgs trios.", "ssuissero": "Serotype prediction of Streptococcus suis assemblies", "vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file"}}, "target": "utils_annotation_cache", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_4_4", "category": "samplesheet_schema", "state": {"technology": "Small RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end 50bp miRNA reads with 3-prime adapter?", "criteria": {"sample,fastq_1,mirna_id": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "resource_arriba_arriba_4", "category": "resource_profiling", "state": {"process": "ARRIBA_ARRIBA", "tool": "arriba/arriba", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_ARRIBA (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_6_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns are standard for CUT&RUN / CUT&TAG chromatin profiling with IgG control input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "resource_bcftools_index_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_INDEX", "tool": "bcftools/index", "description": "Index VCF tools"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_INDEX (Index VCF tools) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_parsesdrf_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration using the `parse_sdrf\nconvert-<format>` subcommands of the sdrf-pipelines package. The chosen\n`format` selects the subcommand; the module owns the output filenames and\nemits one tuple per supported format (mhcquant, openms, maxquant, msstats,\nnormalyzerde, diann). (tools: sdrf-pipelines)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parsesdrf/convert": null, "eido/convert": null, "samplesheetparser/info": null, "picard/collectinsertsizemetrics": null, "differential_functional_enrichment": null}}, "target": "parsesdrf/convert", "target_idx": 0}
{"id": "mod_segul_aligntrim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim multiple sequence alignments by filtering columns based on missing data proportion or parsimony informative sites using SEGUL. (tools: segul)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "custom_tabulartogseagct": "Convert a TSV or CSV with features by row and observations by column to a GCT format file as consumed by GSEA", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "dia_proteomics_analysis": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,\npreliminary analysis, emp", "segul_aligntrim": "Trim multiple sequence alignments by filtering columns based on missing data proportion or parsimony informati"}}, "target": "segul_aligntrim", "target_idx": 4}
{"id": "resource_apbs_3", "category": "resource_profiling", "state": {"process": "APBS", "tool": "apbs", "description": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Boltzmann Solver). Produces electrostatic potential\nmaps and solvation energy values for large biomolecular assemblages."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to APBS (Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nus) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_multiple_script_sections_invalid_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_velocyto_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Velocyto is a library for the analysis of RNA velocity. velocyto.py CLI use\n`Path(resolve_path=True)` and breaks the nextflow logic of symbolic links.\nIf in the work dir velocyto find a file named EXACTLY `cellsorted_[ORIGINAL_BAM_NAME]`\nit will skip the samtools sort step.\nCellsorted bam file should be cell sorted with:\n```bash\n    samtools sort -t CB -O BAM -o cellsorted_input.bam input.bam\n```\nSee module test for an example with the SAMTOOLS_SORT nf-core module.\nConfig example to cellsort input bam using SAMTOOLS_SORT:\n```groovy\n    withName: SAMTOOLS_SORT {\n        ext.prefix = { \"cellsorted_${bam.baseName}\" }\n        ext.args = '-t CB -O BAM'\n    }\n```\nOptional mask must be passed with `ext.args` and option `--mask`\nThis is why I need to stage in the work dir 2 bam files (cellsorted and original).\nSee also [velocyto tutorial](https://velocyto.org/velocyto.py/tutorial/cli.html#notes-on-first-runtime-and-parallelization) (tools: velocyto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsift/dbnsfp": null, "mgnifam/generatefamilies": null, "velocyto": null, "cellrangeratac/count": null, "allelecounter": null}}, "target": "velocyto", "target_idx": 2}
{"id": "mod_coptr_estimate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates peak-to-through ratio (PTR) from metagenomic sequence data (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtk_baftest": null, "circularmapper_circulargenerator": null, "coptr_index": null, "gcta_makegrmpart": null, "coptr_estimate": null}}, "target": "coptr_estimate", "target_idx": 4}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_bedtools_nuc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Profiles the nucleotide content of intervals in a fasta file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/nuc": "Profiles the nucleotide content of intervals in a fasta file.", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "zip": "Compress file lists to produce ZIP archive files", "fastqc": "Run FastQC on sequenced reads", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file"}}, "target": "bedtools/nuc", "target_idx": 0}
{"id": "mod_multiqcsav_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregate results from bioinformatics analyses across many samples into a single report, with support for multiqc_sav plugin (tools: multiqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"multiqcsav": null, "fgumi_simplexmetrics": null, "homer_groseq": null, "artic_aligntrim": null, "bcl2fastq": null}}, "target": "multiqcsav", "target_idx": 0}
{"id": "schema_std_taxprofiler_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "assay": "taxprofiler pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/taxprofiler (Highly parallelised multi-taxonomic profiling of shotgun sho)?", "criteria": {"sample,group,path,ref,method": null, "patient,sample,vcf,status,cna": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "fastq_1,fastq_2,group,replicate,control": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_4_2", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end low-input fragment FASTQs with target antibody and IgG negative control?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_subsample_fq_salmon_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SUBSAMPLE_FQ_SALMON", "modules": ["fq/subsample", "salmon/quant", "salmon/index"], "description": "Subsample fastq"}, "question": {"type": "choice", "instructions": "How should FASTQ_SUBSAMPLE_FQ_SALMON (fq/subsample, salmon/quant, salmon/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_SUBSAMPLE_FQ_SALMON": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_subsample_fq_salmon": null}}, "target": "Use nf-core subworkflow fastq_subsample_fq_salmon", "target_idx": 3}
{"id": "mod_merquryfk_ploidyplot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An improved version of Smudgeplot using FastK (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"merquryfk/ploidyplot": "An improved version of Smudgeplot using FastK", "concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "metacache/build": "Taxonomic profiling database building with MetaCache", "blast/tblastn": "Queries a BLAST DNA database", "genescopefk": "A derivative of GenomeScope2.0 modified to work with FastK"}}, "target": "merquryfk/ploidyplot", "target_idx": 0}
{"id": "mod_merquryfk_merquryfk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FastK based version of Merqury (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio/groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "meryl/count": "A genomic k-mer counter (and sequence utility) with nice features.", "merquryfk/merquryfk": "FastK based version of Merqury", "meryl/histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with"}}, "target": "merquryfk/merquryfk", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_5_2", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry).", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/pacvar) for PacBio HiFi unaligned BAM variant calling. Input files: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "samplesheet_arch_scrna_multiome_4_4", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired FASTQs for both GEX and ATAC modalities per nucleus?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "field_constraint_sample_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"type: integer": null, "format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "noul_multiple_script_sections_invalid_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_0_0", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter", "pipeline": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_smartseq_plate_based_5_4", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq.", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bioawk_2", "category": "resource_profiling", "state": {"process": "BIOAWK", "tool": "bioawk", "description": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOAWK (Bioawk is an extension to Brian Kernighan's awk, adding the support of several c) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_34", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_atlas_recal_5", "category": "resource_profiling", "state": {"process": "ATLAS_RECAL", "tool": "atlas/recal", "description": "Gives an estimation of the sequencing bias based on known invariant sites"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_RECAL (Gives an estimation of the sequencing bias based on known invariant sites) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_provenancereport_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/provenancereport. Description: A simple provenance reporting pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/provenancereport.", "criteria": {"sample,fastq_1,fastq_2,strandedness,condition": null, "id,fasta,reference,optional_data,template": null, "id,path": null, "sample_id,name,description,path,path_2": null}}, "target": "id,path", "target_idx": 2}
{"id": "field_constraint_fastq_1_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "mod_mummer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MUMmer is a system for rapidly aligning entire genomes (tools: mummer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmsearch": "search profile(s) against a sequence database", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "mummer": "MUMmer is a system for rapidly aligning entire genomes", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "simpleaf/index": "Indexing of transcriptome for gene expression quantification using SimpleAF"}}, "target": "mummer", "target_idx": 2}
{"id": "resource_annotsv_annotsv_1", "category": "resource_profiling", "state": {"process": "ANNOTSV_ANNOTSV", "tool": "annotsv/annotsv", "description": "Annotation and Ranking of Structural Variation"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_ANNOTSV (Annotation and Ranking of Structural Variation) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_shapeit5_phasecommon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to phase common sites, typically SNP array data, or the first step of WES/WGS data. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt_gff3": null, "shapeit5_phasecommon": null, "beagle5_beagle": null, "hifiasm": null, "circularmapper_realignsamfile": null}}, "target": "shapeit5_phasecommon", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_1_5", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "template": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,bam,bai": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "samplesheet_arch_scrna_10x_v3_4_0", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/pacvar) for PacBio HiFi unaligned BAM variant calling. Input files: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities.", "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi unaligned BAM variant calling input samplesheet?", "criteria": {"sample,bam,bai": null, "sample,bam": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_3_2", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pre-aligned BAM variant calling pipeline with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "mod_vcf_impute_beagle5_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow\ntakes VCF files, phased reference panel, genetic maps and chunks region to perform imputation\nand outputs phased and imputed VCF files.\nMeta map of all channels, except ch_input, will be used to perform joint operations.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: vcf_impute_beagle5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_impute_beagle5": "Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow\ntakes VCF files, phased reference pane", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "lofreq_call": "Lofreq subcommand to call low frequency variants from alignments", "vcflib_vcfuniq": "List unique genotypes. Like GNU uniq, but for VCF records. Remove records which have the same position, ref, a"}}, "target": "vcf_impute_beagle5", "target_idx": 0}
{"id": "schema_std_ribomsqc_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ribomsqc", "assay": "ribomsqc pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/ribomsqc (QC pipeline that monitors mass spectrometer performance in r)?", "criteria": {"sample,fasta,protein,gbk,gff": null, "sample,fastq_1,fastq_2": null, "id,raw_file": null, "sample,fastq_1,fastq_2,batch,condition": null}}, "target": "id,raw_file", "target_idx": 2}
{"id": "mod_blobtk_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates differing styles of blobplots depending on provided arguments. (tools: blobtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wisecondorx/predict": "Find copy number aberrations", "blobtk/plot": "Creates differing styles of blobplots depending on provided arguments.", "kaiju/kaiju2table": "write your description here", "bbmap/bbduk": "Adapter and quality trimming of sequencing reads", "pretextsnapshot": "A module to generate images from Pretext contact maps."}}, "target": "blobtk/plot", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_phase_shapeit5_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_PHASE_SHAPEIT5", "modules": ["glimpse2/chunk", "shapeit5/phasecommon", "shapeit5/ligate", "bcftools/index"], "description": "Subworkflow to phase a reference panel VCF file using SHAPEIT5."}, "question": {"type": "choice", "instructions": "How should VCF_PHASE_SHAPEIT5 (glimpse2/chunk, shapeit5/phasecommon, shapeit5/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_phase_shapeit5": null, "Leave them out": null, "Local subworkflow VCF_PHASE_SHAPEIT5": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_phase_shapeit5", "target_idx": 0}
{"id": "field_constraint_fastq_1_1_8", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_0_3", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bed": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_vcf2zarr_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster (tools: vcf2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequenzautils/gcwiggle": "Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggl", "atlas/call": "generate VCF file from a BAM file using various calling methods", "bcftools/annotate": "Add or remove annotations.", "metacache/build": "Taxonomic profiling database building with MetaCache", "vcf2zarr/convert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster"}}, "target": "vcf2zarr/convert", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_tn_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic cancer variant calling with tumor-normal pairs", "data_format": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "patient,sample,status,bam,bai": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_channel_mix_operator_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_38", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_gatk4_annotateintervals_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates intervals with GC content, mappability, and segmental-duplication content (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"faa_seqfu_seqkit": null, "agat/spflagshortintrons": null, "agat/spfilterbyorfsize": null, "gatk4/annotateintervals": null, "motus/merge": null}}, "target": "gatk4/annotateintervals", "target_idx": 3}
{"id": "mod_scvitools_solo_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect doublets in single-cell RNA-Seq data (tools: scvitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"goat/taxonsearch": "Query metadata for any taxon across the tree of life.", "mirtrace/qc": "A tool for quality control and tracing taxonomic origins of microRNA sequencing data", "scvitools/solo": "Detect doublets in single-cell RNA-Seq data", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "doubletdetection": "Doublet detection in single-cell RNA-seq data"}}, "target": "scvitools/solo", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for Fungal ITS1/ITS2 marker gene amplicon surveillance. Input files: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads.", "question": {"type": "choice", "instructions": "Which columns are standard for Fungal ITS1/ITS2 marker gene amplicon surveillance input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_ampliseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Amplicon sequencing analysis workflow using DADA2 and QIIME2. Topics: 16s, 18s, amplicon-sequencing, edna, illumina, iontorrent. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"circdna": null, "taxprofiler": null, "eager": null, "raredisease": null, "nanoseq": null, "magmap": null, "pangenome": null, "fetchngs": null, "ampliseq": null, "multiplesequencealign": null}}, "target": "ampliseq", "target_idx": 8}
{"id": "samplesheet_arch_pediatric_trio_somatic_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents). Input files: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) with entry step FASTQC.", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_42", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_all101_bacass_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for assembly analysis? Specific context: Simple bacterial assembly and annotation pipeline. Topics: assembly, bacterial-genomes, denovo, denovo-assembly, genome-assembly, hybrid-assembly. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "bacass", "target_idx": 1}
{"id": "resource_arcane_filter_2", "category": "resource_profiling", "state": {"process": "ARCANE_FILTER", "tool": "arcane/filter", "description": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCANE_FILTER (Filter GTF annotations and genome sequence for alignment-free single-cell RNA-se) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcftools_pluginvcf2table_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINVCF2TABLE", "tool": "bcftools/pluginvcf2table", "description": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output as one row, with INFO and FORMAT fields as columns."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINVCF2TABLE (Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table ) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/hic --input samplesheet.csv (Assay: Hi-C chromosome conformation capture mapping)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hi-C chromosome conformation capture mapping?", "criteria": {"sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_15", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_motus_preplong_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic meta-omics profiling using universal marker genes (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hasheddrops": "Generating cell hashing calls from a matrix of count data.", "motus/preplong": "Taxonomic meta-omics profiling using universal marker genes", "roary": "Calculate pan-genome from annotated bacterial assemblies in GFF3 format", "centrifuge/centrifuge": "Classifies metagenomic sequence data", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files"}}, "target": "motus/preplong", "target_idx": 1}
{"id": "field_constraint_expected_cells_1_9", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_37", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_34", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "noul_channel_collect_operator_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_bam_markduplicates_picard_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_PICARD", "modules": ["picard/markduplicates", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_PICARD (picard/markduplicates, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_markduplicates_picard": null, "Local subworkflow BAM_MARKDUPLICATES_PICARD": null}}, "target": "Use nf-core subworkflow bam_markduplicates_picard", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_2_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_qc_stats_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_STATS", "modules": ["fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp"], "description": "Generate statistics for short read sequencing data using multiple tools"}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_STATS (fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_qc_stats": null, "Leave them out": null, "Local subworkflow FASTQ_QC_STATS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_qc_stats", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_26", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Metagenomic MAG assembly with comparative groups)", "question": {"type": "choice", "instructions": "Which columns are standard for Metagenomic MAG assembly with comparative groups input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_31", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_umitools_dedup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read. (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qualimap_rnaseq": null, "umitools_group": null, "fibertoolsrs_extract": null, "custom_orfcollapse": null, "umitools_dedup": null}}, "target": "umitools_dedup", "target_idx": 4}
{"id": "mod_foldcomp_decompress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Decompression tool for foldcomp compressed structures (tools: foldcomp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/csq": null, "bamtools/convert": null, "foldcomp/decompress": null, "fusioncatcher/fusioncatcher": null, "caalm/caalm": null}}, "target": "foldcomp/decompress", "target_idx": 2}
{"id": "noul_invalid_process_communication_via_globals_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_opt_flip_track_stat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Off-target probe detection (tools: opt_flip_track_stat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization_amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "sentieon_haplotyper": "Runs Sentieon's haplotyper for germline variant calling.", "deeptools_bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig ", "opt_flip_track_stat": "Off-target probe detection", "opt_track": "track aligns query probe sequences to any target transcriptome"}}, "target": "opt_flip_track_stat", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_0", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_panaroo_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast and scalable tool for bacterial pangenome analysis (tools: panaroo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "panaroo/run": "A fast and scalable tool for bacterial pangenome analysis", "umitools/group": "Group reads based on their UMI and mapping coordinates", "odgi/unchop": "Merge unitigs into a single node preserving the node order."}}, "target": "panaroo/run", "target_idx": 2}
{"id": "mod_bam_rseqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to run multiple commands in the RSeqC package (tools: bam_rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anota2seq_anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "fastq_preprocess_seqkit": "Subworkflow that preprocesses FASTQ files", "gatk4_intervallisttobed": "Converts an Picard IntervalList file to a BED file.", "bam_rseqc": "Subworkflow to run multiple commands in the RSeqC package", "custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output"}}, "target": "bam_rseqc", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Standard Paired-end Whole Genome Sequencing (WGS). Input files: Raw paired-end Illumina WGS FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/taxprofiler --input samplesheet.csv (Assay: Multi-taxonomic profiling of complex metagenomic shotgun reads)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_5_2", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Metagenomic MAG assembly with comparative groups.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "resource_anndata_getsize_1", "category": "resource_profiling", "state": {"process": "ANNDATA_GETSIZE", "tool": "anndata/getsize", "description": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_GETSIZE (Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "core_tool_quast_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Evaluate, compare, and compute quality metrics (N50, L50, misassemblies, completeness) for draft genome assemblies against reference genomes.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"multiqc": null, "mummer": null, "busco": null, "quast": null, "checkm": null}}, "target": "quast", "target_idx": 3}
{"id": "noul_single_hyphen_cli_params_error_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "core_tool_picard_markduplicates_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Identify and flag PCR and optical duplicate reads in coordinate-sorted BAM files based on 5-prime mapping coordinates.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"samtools": null, "sambamba": null, "fastp": null, "gatk_markduplicates": null, "picard_markduplicates": null}}, "target": "picard_markduplicates", "target_idx": 4}
{"id": "resource_bedtools_nuc_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_NUC", "tool": "bedtools/nuc", "description": "Profiles the nucleotide content of intervals in a fasta file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_NUC (Profiles the nucleotide content of intervals in a fasta file.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_4_1", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end Tn5 transposed FASTQs across conditions and replicates?", "criteria": {"sample,bed": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "resource_bcl2fastq_2", "category": "resource_profiling", "state": {"process": "BCL2FASTQ", "tool": "bcl2fastq", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCL2FASTQ (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_bam_0_5", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_7_2", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "noul_module_metadata_propagation_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/riboseq) for Ribosome profiling (Ribo-seq) footprint sequencing. Input files: Single-end ribosome protected RNA fragments (RPFs) with strandedness.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Ribosome profiling (Ribo-seq) footprint sequencing with entry step FASTQC.", "criteria": {"sample,cdna_fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "local_subworkflow_prepontreads_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should this step (porechop, nanoplot) be packaged: Nanopore adapter trimming and read quality visualization?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPONTREADS": null, "Use nf-core subworkflow prepontreads": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_6_5", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns are standard for RNA gene fusion detection (Arriba, STAR-Fusion) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fusion_bed": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "field_constraint_fastq_1_1_9", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_12", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Xenium in situ subcellular spatial RNA transcriptomics. Input files: Xenium output bundle with transcripts CSV, cell polygons, and morphology images.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,image": null, "sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,vcf": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "mod_geoquery_getgeo_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Retrieves GEO data from the Gene Expression Omnibus (GEO) (tools: geoquery)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"affy/justrma": "Read CEL files into an ExpressionSet and generate a matrix", "geoquery/getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "bcftools/filter": "Filters VCF files"}}, "target": "geoquery/getgeo", "target_idx": 1}
{"id": "mod_goat_taxonsearch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Query metadata for any taxon across the tree of life. (tools: goat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA.", "entrezdirect_esearch": "Searches a term in a public NCBI database", "goat_taxonsearch": "Query metadata for any taxon across the tree of life.", "stainwarpy_extractchannel": "Extract a single channel image from multiplexed tissue images using stainwarpy", "custom_sratoolsncbisettings": "Test for the presence of suitable NCBI settings or create them on the fly."}}, "target": "goat_taxonsearch", "target_idx": 2}
{"id": "noul_channel_factory_inside_process_body_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_ariba_getref_4", "category": "resource_profiling", "state": {"process": "ARIBA_GETREF", "tool": "ariba/getref", "description": "Download and prepare database for Ariba analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_GETREF (Download and prepare database for Ariba analysis) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_35", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_16", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_1_2", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,well,plate": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_5_2", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering", "pipeline": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/metatdenovo, determine the input samplesheet column structure for: Environmental community metatranscriptomics de novo assembly.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null, "sample,fastq_1": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_6_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/bacass) for Hybrid bacterial assembly combining short Illumina and long Nanopore reads. Input files: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/bacass, determine the input samplesheet column structure for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "mod_samtools_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge BAM or CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qualimap/bamqc": "Evaluate alignment data", "concoct/extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "bcftools/merge": "Merge VCF files", "samtools/merge": "Merge BAM or CRAM file", "emu/abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads."}}, "target": "samtools/merge", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_bgzip_index_dict_samtools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BGZIP_INDEX_DICT_SAMTOOLS", "modules": ["htslib/bgziptabix", "samtools/dict", "samtools/faidx"], "description": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA file."}, "question": {"type": "choice", "instructions": "How should FASTA_BGZIP_INDEX_DICT_SAMTOOLS (htslib/bgziptabix, samtools/dict, samtools/faidx) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_bgzip_index_dict_samtools": null, "Leave them out": null, "Local subworkflow FASTA_BGZIP_INDEX_DICT_SAMTOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_bgzip_index_dict_samtools", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_35", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_2_4", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_phenotype_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 1}
{"id": "mod_parabricks_dbsnp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/dbsnp": "NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database", "bam_split_by_region": "Split the reads in the input bam by specified genomic region.", "plink/exclude": "Exclude variant identifiers from plink bfiles", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "parabricks/dbsnp", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic tumor-normal calling from pre-aligned BAM files", "data_format": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "patient,sample,bam": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "mod_concoct_mergecutupclustering_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_intersect": "Allows one to screen for overlaps between two sets of genomic features.", "dastool_fastatocontig2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "concoct_mergecutupclustering": "Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py", "svtyper_svtypersso": "SVTyper-sso computes structural variant (SV) genotypes based on breakpoint depth on a SINGLE sample", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length."}}, "target": "concoct_mergecutupclustering", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_5_4", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry).", "criteria": {"sample,fastq_1,fastq_2": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_6_4", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions", "pipeline": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "Which columns are standard for Data-Independent Acquisition (DIA) quantitative mass spectrometry input samplesheet?", "criteria": {"sample,raw_file,condition": null, "sample,mzml": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_4_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads with library strandedness?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_kaiju_kaiju_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of metagenomic sequence data using a protein reference database (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_classify": "Classify FASTQ files against ganon database", "kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "icountmini_summary": "Report proportion of cross-link events/sites on each region type.", "centrifuge_centrifuge": "Classifies metagenomic sequence data", "repeatmodeler_builddatabase": "Create a database for RepeatModeler"}}, "target": "kaiju_kaiju", "target_idx": 1}
{"id": "mod_propr_propd_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform differential proportionality analysis (tools: propr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"limma_differential": null, "dotseq_dotseq": null, "propr_propd": null, "bioawk": null, "mifaser": null}}, "target": "propr_propd", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_2_5", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_0_2", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "noul_channel_mix_operator_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_index_dna_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_DNA", "modules": ["bowtie2/build", "bwa/index", "bwamem2/index", "dragmap/hashtable", "snapaligner/index"], "description": "Generate aligner index for a reference genome."}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_DNA (bowtie2/build, bwa/index, bwamem2/index, dragmap/hashtable, snapaligner/index) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fasta_index_dna": null, "Local subworkflow FASTA_INDEX_DNA": null}}, "target": "Use nf-core subworkflow fasta_index_dna", "target_idx": 2}
{"id": "field_constraint_strandedness_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "resource_angsd_soapsnpcalibration_1", "category": "resource_profiling", "state": {"process": "ANGSD_SOAPSNPCALIBRATION", "tool": "angsd/soapsnpcalibration", "description": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_SOAPSNPCALIBRATION (Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality mat) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_40", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "schema_std_alleleexpression_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/alleleexpression. Description: Alleleexpression is a nf-core pipeline for allele-specific expression (ASE) analysis using STAR-WASP for alignment, UMI-tools for deduplication, and phaser for haplotype phasing and ASE detection..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/alleleexpression.", "criteria": {"sample,group,path,ref,method": null, "sample,fastq_1,fastq_2,group": null, "sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample,fastq_1,fastq_2,vcf", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_26", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_6_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ribosome profiling (Ribo-seq) footprint sequencing input samplesheet?", "criteria": {"sample,fastq_1,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "mod_sylph_profile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sylph profile command for taxonoming profiling (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo_profile": "Compute genome-wide STR profile", "echtvar_anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "samtools_markdup": "mark duplicate alignments in a coordinate sorted file", "hmmer_hmmstat": "display summary statistics for each profile HMM in an HMM database file", "sylph_profile": "Sylph profile command for taxonoming profiling"}}, "target": "sylph_profile", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_wgs_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/genomeassembler --input samplesheet.csv (Assay: Long-read Pacific Biosciences HiFi sequencing)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Pacific Biosciences HiFi sequencing with entry step HIFIADAPTERFILT.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_0_2", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,unite_fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_methurator_gtestimator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run estimator for DNA methylation sequencing saturation. (tools: methurator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"methurator_gtestimator": "Run estimator for DNA methylation sequencing saturation.", "gt_gff3": "GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files", "bismark_align": "Performs alignment of BS-Seq reads using bismark", "methurator_plot": "Plots results produced by methurator gtestimator.", "malt_run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h"}}, "target": "methurator_gtestimator", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnafusion --input samplesheet.csv (Assay: RNA gene fusion detection (Arriba, STAR-Fusion))", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "resource_bclconvert_0", "category": "resource_profiling", "state": {"process": "BCLCONVERT", "tool": "bclconvert", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCLCONVERT (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_clipkit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference. (tools: clipkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "fgbio_fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI", "goleft_indexcov": "Quickly estimate coverage from a whole-genome bam or cram index. A bam index has 16KB resolution so that's wha", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins"}}, "target": "clipkit", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_4", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_23", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_pharokka_installdatabases_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Install databases necessary for Pharokka's functional analysis (tools: pharokka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"survivor_merge": "Compare or merge VCF files to generate a consensus or multi sample VCF files.", "pharokka_pharokka": "Functional annotation of phages", "scvitools_scar": "Module to use scAR to remove ambient RNA from single-cell RNA-seq data", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "pharokka_installdatabases": "Install databases necessary for Pharokka's functional analysis"}}, "target": "pharokka_installdatabases", "target_idx": 4}
{"id": "mod_paragraph_vcf2paragraph_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a VCF file to a JSON graph (tools: paragraph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/annotate": "Add or remove annotations.", "paragraph/vcf2paragraph": "Convert a VCF file to a JSON graph", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "meryl/count": "A genomic k-mer counter (and sequence utility) with nice features.", "plink/extract": "Subset plink bfiles with a text file of variant identifiers"}}, "target": "paragraph/vcf2paragraph", "target_idx": 1}
{"id": "resource_arriba_download_5", "category": "resource_profiling", "state": {"process": "ARRIBA_DOWNLOAD", "tool": "arriba/download", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_DOWNLOAD (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_opt_stat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: stat summarizes opt binding predictions (tools: opt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpeff/download": "Genetic variant annotation and functional effect prediction toolbox", "opt/track": "track aligns query probe sequences to any target transcriptome", "opt/stat": "stat summarizes opt binding predictions", "ska/distance": "Calculate pairwise distances and basic clustering from SKA sketches", "td2/longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se"}}, "target": "opt/stat", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "data_format": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns are standard for Fungal ITS1/ITS2 marker gene amplicon surveillance input samplesheet?", "criteria": {"sample,primer_its1,primer_its2": null, "sample,bam": null, "sample,unite_fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_oncoanalyser_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "description": "A comprehensive cancer DNA/RNA analysis and reporting pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/oncoanalyser?", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,group,path,ref,method": null, "id,path": null, "id,raw_file": null}}, "target": "sample_id,group_id,subject_id,sample_type,sequence_type", "target_idx": 0}
{"id": "mod_gatk4_createsequencedictionary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a sequence dictionary for a reference sequence (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone_check": "Check that files in source and destination paths match", "megan_rma2info": "Analyses an RMA file and exports information in text format", "gatk4_createsequencedictionary": "Creates a sequence dictionary for a reference sequence", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "picard_createsequencedictionary": "Creates a sequence dictionary for a reference sequence."}}, "target": "gatk4_createsequencedictionary", "target_idx": 2}
{"id": "mod_helitronscanner_draw_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: HelitronScanner draw tool for Helitron transposons in genomes (tools: helitronscanner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"helitronscanner_draw": "HelitronScanner draw tool for Helitron transposons in genomes", "deeptools_bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "prodigal": "Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene ", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "helitronscanner_draw", "target_idx": 0}
{"id": "pipe_all101_variantprioritization_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR).. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n"}}, "target": "variantprioritization", "target_idx": 8}
{"id": "mod_deeptools_plotpca_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or multibigwigsummary as input. (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trycycler_cluster": null, "shinyngs_staticexploratory": null, "deeptools_plotpca": null, "custom_clustervisualization": null, "scimap_mcmicro": null}}, "target": "deeptools_plotpca", "target_idx": 2}
{"id": "schema_std_methylong_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylong", "assay": "methylong pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/methylong (Extract methylation calls from long reads (ONT/ PacBio) )?", "criteria": {"sample,input,output_path,checksum_md5,checksum_sha": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,group,path,ref,method": null}}, "target": "sample,group,path,ref,method", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/oncoanalyser) for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking. Input files: Circulating tumor DNA FASTQs across patient clinical draw intervals.", "question": {"type": "choice", "instructions": "Which columns are standard for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking input samplesheet?", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_amulety_translate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety/esm2": null, "msisensorpro/pro": null, "amulety/translate": null, "amulety/balmpaired": null, "shapeit5/ligate": null}}, "target": "amulety/translate", "target_idx": 2}
{"id": "mod_angsd_soapsnpcalibration_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_docounts_contamination_angsd": null, "gatk4_estimatelibrarycomplexity": null, "angsd_realsfs": null, "angsd_soapsnpcalibration": null, "tsebra": null}}, "target": "angsd_soapsnpcalibration", "target_idx": 3}
{"id": "mod_trimmomatic_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs quality and adapter trimming on paired end and single end reads (tools: trimmomatic)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_bbduk": "Adapter and quality trimming of sequencing reads", "cutesv": "structural-variant calling with cutesv", "trimmomatic": "Performs quality and adapter trimming on paired end and single end reads", "chromap_chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "bowtie_build": "Create bowtie index for reference genome"}}, "target": "trimmomatic", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_5_5", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pre-aligned BAM variant calling pipeline.", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "schema_std_detaxizer_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/detaxizer", "description": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/detaxizer?", "criteria": {"sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,fastq,cell_count": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1", "target_idx": 0}
{"id": "mod_biscuit_mergecg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges methylation information for opposite-strand C's in a CpG context (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/index": "Indexes a reference genome for use with Biscuit", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "survivor/bedpetovcf": "Converts a bedpe file to a VCF file (beta version)", "biscuit/mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "deeptools/plotheatmap": "plots values produced by deeptools_computematrix as a heatmap"}}, "target": "biscuit/mergecg", "target_idx": 3}
{"id": "mod_samtools_depth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the depth at each position or region. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qualimap_rnaseq": null, "jvarkit_wgscoverageplotter": null, "goleft_indexcov": null, "samtools_depth": null, "hmmer_eslalipid": null}}, "target": "samtools_depth", "target_idx": 3}
{"id": "mod_dastool_scaffolds2bin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format (tools: dastool)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "fargene": "tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full", "samtools/depth": "Computes the depth at each position or region.", "comebin/runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "dastool/scaffolds2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format"}}, "target": "dastool/scaffolds2bin", "target_idx": 4}
{"id": "resource_bismark_report_4", "category": "resource_profiling", "state": {"process": "BISMARK_REPORT", "tool": "bismark/report", "description": "Collects bismark alignment reports"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_REPORT (Collects bismark alignment reports) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "core_tool_mutect2_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Somatic short variant detection (SNVs and small indels) comparing matched tumor and normal sequencing data with Bayesian somatic likelihood filtering.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"varscan2": null, "somaticsniper": null, "mutect2": null, "vardict": null, "strelka2": null}}, "target": "mutect2", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_4_1", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end ribosome protected RNA fragments (RPFs) with strandedness?", "criteria": {"sample,fastq_1,strandedness": null, "sample,bam": null, "sample,vcf": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "mod_mtmalign_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns protein structures using mTM-align (tools: mTM-align)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "emboss_revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "mtmalign_align": "Aligns protein structures using mTM-align", "concoct_concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile"}}, "target": "mtmalign_align", "target_idx": 3}
{"id": "resource_bamcmp_0", "category": "resource_profiling", "state": {"process": "BAMCMP", "tool": "bamcmp", "description": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For instance, filtering out mouse reads from patient derived xenograft mouse models (PDX)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCMP (Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "intent_debug_error_3", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "debug_error": null, "build_pipeline": null, "prepare_data": null}}, "target": "debug_error", "target_idx": 1}
{"id": "mod_gridss_gridss_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/ftxpy": "Somatic VCF Feature Extraction tool from hap.y.", "gridss/extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "gridss/generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "gridss/gridss": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "plink2/pca": "Perform PCA analysis using PLINK"}}, "target": "gridss/gridss", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_se_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Single-end Illumina RNA-seq with strandedness", "data_format": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "mod_mgnifam_generatefamilies_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Iteratively builds protein family HMM profiles from MMseqs2 sequence clusters and expands them against a protein database (tools: mgnifam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/createsequencedictionary": "Creates a sequence dictionary for a reference sequence.", "hmmer/hmmemit": "emit sequences from a profile HMM", "hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment", "hmtnote/annotate": "Human mitochondrial variants annotation using HmtVar. Contains .plk file with annotation, so can be run offlin", "mgnifam/generatefamilies": "Iteratively builds protein family HMM profiles from MMseqs2 sequence clusters and expands them against a prote"}}, "target": "mgnifam/generatefamilies", "target_idx": 4}
{"id": "samplesheet_arch_prealigned_cram_indexed_6_5", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns are standard for Genome analysis from reference-compressed CRAM files input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,cram": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "intent_prepare_data_14", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "prepare_data", "target_idx": 0}
{"id": "intent_prepare_data_1", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "build_pipeline": null, "prepare_data": null}}, "target": "prepare_data", "target_idx": 3}
{"id": "mod_antismash_antismashdownloaddatabases_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs. (tools: antismash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash_antismashdownloaddatabases": null, "antismash_antismashlitedownloaddatabases": null, "telogator2": null, "antismash_antismashlite": null, "gatk4_asereadcounter": null}}, "target": "antismash_antismashdownloaddatabases", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_5_5", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Trio exome/genome sequencing (Proband, Mother, Father).", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_22", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pre-aligned BAM variant calling pipeline. Input files: Aligned BAM files.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pre-aligned BAM variant calling pipeline.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "pipe_all101_fetchngs_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for ddbj. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T"}}, "target": "fetchngs", "target_idx": 1}
{"id": "mod_modkit_pileup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A bioinformatics tool for working with modified bases (tools: modkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "modkit/pileup": "A bioinformatics tool for working with modified bases", "deepbgc/pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "bismark/methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "samtools/fasta": "Converts a SAM/BAM/CRAM file to FASTA"}}, "target": "modkit/pileup", "target_idx": 1}
{"id": "mod_bwamem3_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create bwa-mem3 index for reference genome (tools: bwamem3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"suppa_generateevents": null, "biscuit_index": null, "bwameth_index": null, "bwamem3_index": null, "bowtie_build": null}}, "target": "bwamem3_index", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_49", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "noul_deprecated_dsl1_set_keyword_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_7", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_6_0", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "PBMM2_ALIGN", "library_inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi unaligned BAM variant calling input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "mod_fusionreport_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build DB for fusionreport (tools: fusionreport)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscreen/buildfromindex": "Build fastq screen config file from bowtie index files", "fusionreport/download": "Build DB for fusionreport", "csvtk/sort": "Sort  CSV (or TSV) tables", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "biobambam/bamsormadup": "Parallel sorting and duplicate marking"}}, "target": "fusionreport/download", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "schema_std_mhcquant_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mhcquant", "description": "Identify and quantify MHC eluted peptides from mass spectrometry raw data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/mhcquant?", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,seed": null, "seeds,network,perturbed_networks": null, "patient,vcf,tbi,dataset,tumour_sample": null}}, "target": "ID,Sample,Condition,ReplicateFileName,Fasta", "target_idx": 0}
{"id": "pipe_all101_epitopeprediction_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for epitope analysis? Specific context: A bioinformatics best-practice analysis pipeline for epitope prediction and annotation. Topics: epitope, epitope-prediction, mhc-binding-prediction. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H"}}, "target": "epitopeprediction", "target_idx": 1}
{"id": "mod_vcf_annotate_ensemblvep_snpeff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkflow uses the scatter-gather method to run VEP/snpEff in parallel to increase throughput. The input VCF is split into multiple smaller VCFs of fixed size, which are annotated separately and concatenated back together to a single output file per sample. Only VCF/BCF outputs are currently supported. (tools: vcf_annotate_ensemblvep_snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_annotate_ensemblvep_snpeff": "Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkf", "atlas_call": "generate VCF file from a BAM file using various calling methods", "plink2_score": "Apply a scoring system to each sample in a plink 2 fileset", "abacas": "Contiguate draft genome assembly", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "vcf_annotate_ensemblvep_snpeff", "target_idx": 0}
{"id": "resource_bbmap_bbmerge_5", "category": "resource_profiling", "state": {"process": "BBMAP_BBMERGE", "tool": "bbmap/bbmerge", "description": "Merging overlapping paired reads into a single read."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBMERGE (Merging overlapping paired reads into a single read.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_0", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "pipe_all101_diaproteomics_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Automated quantitative analysis of DIA proteomics mass spectrometry measurements.. Topics: data-independent-proteomics, dia-proteomics, openms, proteomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot"}}, "target": "diaproteomics", "target_idx": 7}
{"id": "resource_bedtools_jaccard_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_JACCARD", "tool": "bedtools/jaccard", "description": "Calculate Jaccard statistic b/w two feature files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_JACCARD (Calculate Jaccard statistic b/w two feature files.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_0_4", "category": "samplesheet_schema", "state": {"technology": "Spatial Transcriptomics", "workflow_entry": "FASTQC", "library_inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,image": null, "sample,image": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "mod_seqkit_split2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split single or paired-end fastq.gz files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_pluginsplit": "Split VCF by sample, creating single- or multi-sample VCFs.", "bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "seqkit_split2": "Split single or paired-end fastq.gz files", "cpc2": "Coding Potential Calculator 2", "openms_fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX"}}, "target": "seqkit_split2", "target_idx": 2}
{"id": "mod_pilon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Automatically improve draft assemblies and find variation among strains, including large event detection (tools: pilon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star_starsolo": "Create a counts matrix for single-cell data using STARSolo, handling cell barcodes and UMI information.", "blobtk_depth": "Creates a bed file containing the depth of data at intervals of an aligned bam.", "pilon": "Automatically improve draft assemblies and find variation among strains, including large event detection", "abacas": "Contiguate draft genome assembly", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "pilon", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_27", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_19", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_opt_track_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: track aligns query probe sequences to any target transcriptome (tools: opt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_extract_relate_somalier": null, "opt_flip_track_stat": null, "td2/longorfs": null, "gt/stat": null, "opt/track": null}}, "target": "opt/track", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_0_11", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_strelka_germline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation (tools: strelka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strelka_germline": null, "parabricks_deepvariant": null, "gapseq_findtransport": null, "dragen_germline": null, "cellrangerarc_count": null}}, "target": "strelka_germline", "target_idx": 0}
{"id": "mod_snippy_core_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Core-SNP alignment from Snippy outputs (tools: snippy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_split": null, "bwa_mem": null, "mmseqs_linclust": null, "abra2": null, "snippy_core": null}}, "target": "snippy_core", "target_idx": 4}
{"id": "resource_arcashla_extract_0", "category": "resource_profiling", "state": {"process": "ARCASHLA_EXTRACT", "tool": "arcashla/extract", "description": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCASHLA_EXTRACT (Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alterna) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_bedtools_groupby_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Groups features in a BED file by given column(s) and computes summary statistics for each group to another column. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "apbs": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Bol", "bedtools_groupby": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another col", "nanomonsv_parse": "Parse all the supporting reads of putative somatic SVs using nanomonsv.\nAfter successful completion, you will "}}, "target": "bedtools_groupby", "target_idx": 3}
{"id": "mod_mcstaging_phenoimager2mc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per cycle, compatible as ASHLAR input. (tools: mcstaging)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging_phenoimager2mc": "Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per c", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "bftools_showinf": "Extract OME xml data from OME-tif", "happy_sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic ", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope"}}, "target": "mcstaging_phenoimager2mc", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_4_3", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "template": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_hmmer_hmmlogo_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: extract logo data from a profile HMM file to produce an HMM logo (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmlogo": null, "hmmer/hmmpress": null, "bigscape/bigscape": null, "odgi/sort": null, "hmmer/hmmbuild": null}}, "target": "hmmer/hmmlogo", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_2_4", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform", "pipeline": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bamtools_convert_0", "category": "resource_profiling", "state": {"process": "BAMTOOLS_CONVERT", "tool": "bamtools/convert", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_CONVERT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_rnadnavar_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for RNA and DNA integrated analysis for somatic mutation detection. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc"}}, "target": "rnadnavar", "target_idx": 8}
{"id": "resource_blobtk_plot_5", "category": "resource_profiling", "state": {"process": "BLOBTK_PLOT", "tool": "blobtk/plot", "description": "Creates differing styles of blobplots depending on provided arguments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_PLOT (Creates differing styles of blobplots depending on provided arguments.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_channel_filter_operator_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "core_tool_kraken2_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Exact k-mer matching taxonomic classifier mapping metagenomic reads to bacterial and viral reference genomes with lowest common ancestor algorithm.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"centrifuge": "Taxonomic classifier", "motus": "Marker gene classifier", "diamond": "Protein aligner", "kraken2": "Taxonomic sequence classification system that uses exact k-mer matches", "metaphlan": "Marker gene classifier"}}, "target": "kraken2", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_6_4", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin", "pipeline": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for ChIP-seq with IP and input control design input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "noul_named_output_channel_access_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_prokka_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Whole genome annotation of small genomes (bacterial, archeal, viral) (tools: prokka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "finaletoolkit_fraglengthbins": "Generate a binned fragment profile and a fragment distribution histogram", "prokka": "Whole genome annotation of small genomes (bacterial, archeal, viral)", "mapad_map": "Map short-reads to an indexed reference genome", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "prokka", "target_idx": 2}
{"id": "field_constraint_sex_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_4_2", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities?", "criteria": {"sample,bam,bai": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "resource_alignoth_5", "category": "resource_profiling", "state": {"process": "ALIGNOTH", "tool": "alignoth", "description": "Creating alignment plots from bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALIGNOTH (Creating alignment plots from bam files) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_bowtie2_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bowtie2 (tools: bowtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_parsetables": null, "numorph_intensity": null, "bowtie2_align": null, "bamclipper": null, "ampcombi": null}}, "target": "bowtie2_align", "target_idx": 2}
{"id": "resource_authentict_deam2cont_1", "category": "resource_profiling", "state": {"process": "AUTHENTICT_DEAM2CONT", "tool": "authentict/deam2cont", "description": "Use deamination patterns to estimate contamination in single-stranded libraries"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTHENTICT_DEAM2CONT (Use deamination patterns to estimate contamination in single-stranded libraries) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_scrnaseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay": "scrnaseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/scrnaseq (Single-cell RNA-Seq pipeline for barcode-based protocols suc)?", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,seq_data,pbi,start_from": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,fastq_barcode,expected_cells", "target_idx": 3}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP", "modules": ["ensemblvep/vep", "tabix/tabix"], "description": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP (ensemblvep/vep, tabix/tabix) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_annotate_ensemblvep": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow VCF_ANNOTATE_ENSEMBLVEP": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_0_0", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_mifaser_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functional annotation of metagenomic reads by assigning enzyme commission (EC) numbers (tools: mifaser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "mifaser": "Functional annotation of metagenomic reads by assigning enzyme commission (EC) numbers", "snippy/core": "Core-SNP alignment from Snippy outputs", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "qcat": "Demultiplexer for Nanopore samples"}}, "target": "mifaser", "target_idx": 1}
{"id": "mod_kofamscan_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces annotation using kofamscan against a Profile database and a KO list (tools: kofamscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kofamscan": "Produces annotation using kofamscan against a Profile database and a KO list", "bedtools/map": "Allows one to screen for overlaps between two sets of genomic features.", "propr/propr": "Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coeff", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}}, "target": "kofamscan", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_5_3", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic cancer variant calling with tumor-normal pairs.", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_8_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "MUTECT2", "library_inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "field_constraint_bai_0_11", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_15", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_mm2plus_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: mm2plus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mudskipper/index": "Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM fi", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "mm2plus/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "rpbp/selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ"}}, "target": "mm2plus/align", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pre-aligned BAM variant calling pipeline)", "question": {"type": "choice", "instructions": "Which columns are standard for Pre-aligned BAM variant calling pipeline input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "field_constraint_status_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_1", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_megahit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An ultra-fast metagenomic assembler for large and complex metagenomics (tools: megahit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abyss/abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "krakentools/combinekreports": "Takes multiple kraken-style reports and combines them into a single report file", "msisensorpro/scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "megahit": "An ultra-fast metagenomic assembler for large and complex metagenomics", "ale": "ALE: assembly likelihood estimator."}}, "target": "megahit", "target_idx": 3}
{"id": "core_tool_spades_metaspades_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? De novo assembler specifically optimized for complex microbial metagenomic mixtures, recovering contigs across unequal coverage depths.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"unicycler": "Hybrid assembler", "canu": "Long read assembler", "flye": "Long read assembler", "megahit": "Metagenomic assembler", "spades_metaspades": "metaSPAdes is a sub-tool of SPAdes designed for metagenomics assembly"}}, "target": "spades_metaspades", "target_idx": 4}
{"id": "pipe_all101_funcscan_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze (Meta-)genome screening for functional and natural product gene sequences. Topics: amp, amr, antibiotic-resistance, antimicrobial-peptides, antimicrobial-resistance-genes, arg. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralmetagenome": null, "readsimulator": null, "proteogenomicsdb": null, "variantbenchmarking": null, "pathogensurveillance": null, "viralrecon": null, "crisprseq": null, "funcscan": null, "phyloplace": null, "hgtseq": null}}, "target": "funcscan", "target_idx": 7}
{"id": "mod_bcftools_roh_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered. (tools: roh)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellranger/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkref command.", "rhocall/annotate": "Markup VCF file using rho-calls.", "ngsbits/rohhunter": "RohHunter is a tool for run of homozygosity (ROH) detection based on a variant list in VCF format.", "bcftools/roh": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered.", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "bcftools/roh", "target_idx": 3}
{"id": "noul_channel_collect_operator_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_bai_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "resource_biscuit_vcf2bed_4", "category": "resource_profiling", "state": {"process": "BISCUIT_VCF2BED", "tool": "biscuit/vcf2bed", "description": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_VCF2BED (Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compl) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_variantbenchmarking_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research. Topics: benchmark, small-variants, structural-variants, variant-calling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo"}}, "target": "variantbenchmarking", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_20", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_genomeassembler_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "description": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/genomeassembler?", "criteria": {"sample,bam,pbi,fail,repeat_id": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample,fastq_1,fastq_2,vcf": null, "sample,type,level,msfile": null}}, "target": "sample,group,ref_fasta,ref_gff,use_ref", "target_idx": 1}
{"id": "pipe_all101_sarek_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for annotation. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab"}}, "target": "sarek", "target_idx": 6}
{"id": "mod_hhsuite_reformat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reformat a Multiple Sequence Alignment (MSA) file (tools: hhsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"emu/abundance": null, "hhsuite/reformat": null, "samtools/view": null, "clustalo/guidetree": null, "clustalo/align": null}}, "target": "hhsuite/reformat", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_21", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_kallistobustools_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: quantifies scRNA-seq data from fastq files using kb-python. (tools: kb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"universc": "Module to run UniverSC an open-source pipeline to demultiplex and process single-cell RNA-Seq data", "kallistobustools_count": "quantifies scRNA-seq data from fastq files using kb-python.", "irescue": "Quantification of transposable elements expression in scRNA-seq", "fastq_align_mapad": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and index", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "kallistobustools_count", "target_idx": 1}
{"id": "mod_tailfindr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA (tools: tailfindr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "emu_abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads.", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "gridss_call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads"}}, "target": "tailfindr", "target_idx": 2}
{"id": "mod_shinyngs_staticexploratory_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots (tools: shinyngs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "deeptools_multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "singlem_dbdownload": "Download the SingleM metapackage database used for metagenome profiling", "shinyngs_staticexploratory": "Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots", "plink_genome": "Calculates identity-by-descent over autosomal SNPs"}}, "target": "shinyngs_staticexploratory", "target_idx": 3}
{"id": "field_constraint_phenotype_1_10", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [normal, tumor]": null, "type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "noul_single_hyphen_cli_params_error_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "pipe_core10_viralrecon_2_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Viral metagenomics, reference-guided assembly, and mutation calling for amplicon and metagenomic libraries.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "viralrecon", "target_idx": 4}
{"id": "resource_bedtools_merge_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MERGE", "tool": "bedtools/merge", "description": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MERGE (combines overlapping or “book-ended” features in an interval file into a single ) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_bam_split_by_region_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SPLIT_BY_REGION", "modules": ["samtools/view", "samtools/index"], "description": "Split the reads in the input bam by specified genomic region."}, "question": {"type": "choice", "instructions": "How should BAM_SPLIT_BY_REGION (samtools/view, samtools/index) be structured in DSL2?", "criteria": {"Local subworkflow BAM_SPLIT_BY_REGION": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_split_by_region": null}}, "target": "Use nf-core subworkflow bam_split_by_region", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_2_11", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Paired-end Whole Exome Sequencing (WES) target capture. Input files: Paired-end FASTQs from Agilent/Twist exome target capture.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Paired-end Whole Exome Sequencing (WES) target capture.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_metatdenovo_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses.. Topics: eukaryotes, metagenomics, metatranscriptomics, prokaryotes, viruses. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we"}}, "target": "metatdenovo", "target_idx": 1}
{"id": "subworkflow_pkg_cache_download_ensemblvep_snpeff_2", "category": "subworkflow_packaging", "state": {"subworkflow": "CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "snpeff/download"], "description": "downlad annotation cache for snpeff and ensemblvep"}, "question": {"type": "choice", "instructions": "How should CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF (ensemblvep/download, snpeff/download) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF": null, "Use nf-core subworkflow cache_download_ensemblvep_snpeff": null}}, "target": "Use nf-core subworkflow cache_download_ensemblvep_snpeff", "target_idx": 3}
{"id": "samplesheet_arch_ont_demux_barcodes_7_0", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,bam": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "subworkflow_pkg_bam_variant_demix_boot_freyja_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_DEMIX_BOOT_FREYJA", "modules": ["freyja/variants", "freyja/demix", "freyja/update", "freyja/boot"], "description": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to the Hu-1 reference)"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_DEMIX_BOOT_FREYJA (freyja/variants, freyja/demix, freyja/update, freyja/boot) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VARIANT_DEMIX_BOOT_FREYJA": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_variant_demix_boot_freyja": null}}, "target": "Use nf-core subworkflow bam_variant_demix_boot_freyja", "target_idx": 3}
{"id": "resource_abritamr_run_2", "category": "resource_profiling", "state": {"process": "ABRITAMR_RUN", "tool": "abritamr/run", "description": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRITAMR_RUN (A NATA accredited tool for reporting the presence of antimicrobial resistance ge) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bcftools_csq_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CSQ", "tool": "bcftools/csq", "description": "bcftools Haplotype-aware consequence caller"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CSQ (bcftools Haplotype-aware consequence caller) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_4_0", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads?", "criteria": {"sample,primer_its1,primer_its2": null, "sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_jasminesv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Jointly Accurate Sv Merging with Intersample Network Edges (tools: jasminesv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caddsv/get": "Download CADD-SV annotation resources or SegmentNT model files.", "seqkit/sort": "Sorts sequences by id/name/sequence/length", "jasminesv": "Jointly Accurate Sv Merging with Intersample Network Edges", "dysgu/run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "geoquery/getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)"}}, "target": "jasminesv", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/cutandrun) for CUT&RUN / CUT&TAG chromatin profiling with IgG control. Input files: Paired-end low-input fragment FASTQs with target antibody and IgG negative control.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cutandrun, determine the input samplesheet column structure for: CUT&RUN / CUT&TAG chromatin profiling with IgG control.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "mod_trycycler_subsample_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subsample a long-read sequencing fastq file for multiple assemblies (tools: trycycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trycycler/subsample": null, "blast/tblastn": null, "fgumi/downsample": null, "fq/subsample": null, "ucsc/gtftogenepred": null}}, "target": "trycycler/subsample", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_4", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_all101_mhcquant_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Identify and quantify MHC eluted peptides from mass spectrometry raw data. Topics: dda, immunopeptidomics, mass-spectrometry, mhc, openms, peptides. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"isoseq": null, "references": null, "proteinfamilies": null, "dualrnaseq": null, "rnadnavar": null, "drop": null, "mnaseseq": null, "diaproteomics": null, "hadge": null, "mhcquant": null}}, "target": "mhcquant", "target_idx": 9}
{"id": "qc_adapt_illumina_novaseq_2_31", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_5_5", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Metagenomic MAG assembly with comparative groups.", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "mod_cnvkit_batch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number variant detection from high-throughput sequencing data (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmfetch": null, "cnvkit/reference": null, "gcta/makebksparse": null, "cnvkit/fix": null, "cnvkit/batch": null}}, "target": "cnvkit/batch", "target_idx": 4}
{"id": "resource_bcftools_pluginvcf2table_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINVCF2TABLE", "tool": "bcftools/pluginvcf2table", "description": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output as one row, with INFO and FORMAT fields as columns."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINVCF2TABLE (Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table ) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_callingcards_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/callingcards", "assay": "callingcards pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/callingcards (A pipeline for processing calling cards data)?", "criteria": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fastq_1,fastq_2,batch,condition": null, "sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,barcode_details": null}}, "target": "sample,fastq_1,fastq_2,barcode_details", "target_idx": 3}
{"id": "resource_angsd_gl_2", "category": "resource_profiling", "state": {"process": "ANGSD_GL", "tool": "angsd/gl", "description": "Calculated genotype likelihoods from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_GL (Calculated genotype likelihoods from BAM files.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_phispy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict prophages in bacterial genomes (tools: phispy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spaceranger_mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command", "phispy": "Predict prophages in bacterial genomes", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "alignoth": "Creating alignment plots from bam files", "gatk4_variantstotable": "Extract fields from a VCF file to a tab-delimited table"}}, "target": "phispy", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_2_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_2_14", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_bamclipper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This module is used to clip primer sequences from your alignments. (tools: bamclipper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "lima": "lima - The PacBio Barcode Demultiplexer and Primer Remover", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "bamclipper", "target_idx": 4}
{"id": "mod_glimpse2_phase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool for imputation and phasing from vcf file or directly from bam files. (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"molkartgarage/clahe": null, "diamond/blastx": null, "hifiasm": null, "eagle2": null, "glimpse2/phase": null}}, "target": "glimpse2/phase", "target_idx": 4}
{"id": "intent_build_pipeline_12", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_bedtools_bamtobed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a bam file to a bed12 file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": null, "gatk4_getpileupsummaries": null, "kmcp_index": null, "bedtools_bamtobed": null, "atlas_pmd": null}}, "target": "bedtools_bamtobed", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_dragmap_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a reference using DRAGMAP (tools: dragmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa/mem": "Performs fastq alignment to a fasta reference using BWA", "dragmap/align": "Performs fastq alignment to a reference using DRAGMAP", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "seqcluster/collapse": "Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file."}}, "target": "dragmap/align", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for 16S rRNA / ITS microbiome amplicon profiling. Input files: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fasta": null, "sample,otu_table": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_singlecell_parse_splitseq_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Parse Biosciences Split-seq combinatorial barcoding", "data_format": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Parse Biosciences Split-seq combinatorial barcoding with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,well,plate": null, "sample,fastq_1": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_fastani_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Alignment-free computation of Average Nucleotide Identity (ANI) (tools: fastani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "fastani": "Alignment-free computation of Average Nucleotide Identity (ANI)", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "entrezdirect_xtract": "Queries an NCBI database using an UID", "opt_flip_track_stat": "Off-target probe detection"}}, "target": "fastani", "target_idx": 1}
{"id": "mod_knotannotsv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simple tool to create a customizable html file (to be displayed on a web browser) from an AnnotSV output (tools: knotannotsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlasgeneannotationmanipulation/gtf2featureannotation": null, "annosine": null, "t1k/run": null, "knotannotsv": null, "merquryfk/katgc": null}}, "target": "knotannotsv", "target_idx": 3}
{"id": "local_subworkflow_positionsofint_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for POSITIONSOFINT (custom/positionsofint).", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow POSITIONSOFINT": null, "Leave them out": null, "Use nf-core subworkflow positionsofint": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_35", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_channel_join_operator_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_fastq_1_1_7", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_9", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_blobtk_snail_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates blobtk snail plots. (tools: btk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk_depth": "Creates a bed file containing the depth of data at intervals of an aligned bam.", "blobtk_plot": "Creates differing styles of blobplots depending on provided arguments.", "blobtk_snail": "Creates blobtk snail plots.", "openms_idfilter": "Filters peptide/protein identification results by different criteria.", "bff": "Generating cell hashing calls from a matrix of count data."}}, "target": "blobtk_snail", "target_idx": 2}
{"id": "pipe_all101_riboseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo"}}, "target": "riboseq", "target_idx": 8}
{"id": "noul_mix_operator_async_emission_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/pacvar --input samplesheet.csv (Assay: PacBio HiFi unaligned BAM variant calling)", "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "FAIRE-seq / DNAse-seq open chromatin profiling", "data_format": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_4", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "core_tool_gatk_haplotypecaller_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Germline SNP and Indel variant calling via local de novo haplotype assembly across active genomic regions.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"strelka2": "Fast variant caller", "mutect2": "Somatic variant caller", "gatk_haplotypecaller": "Call germline SNPs and indels via local de-novo assembly of haplotypes", "freebayes": "Bayesian genetic variant detector", "deepvariant": "Deep learning-based variant caller"}}, "target": "gatk_haplotypecaller", "target_idx": 2}
{"id": "mod_bam_sort_stats_samtools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort SAM/BAM/CRAM file (tools: bam_sort_stats_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk_sort": null, "plink_bmerge": null, "bam_sort_stats_samtools": null, "jvarkit_vcfpolyx": null, "bedtools_sort": null}}, "target": "bam_sort_stats_samtools", "target_idx": 2}
{"id": "core_tool_fastp_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? All-in-one FASTQ preprocessor performing automated adapter trimming, polyG tail clipping, quality filtering, and base correction.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"trimmomatic": "Read trimming tool", "cutadapt": "Removes adapter sequences", "fastqc": "Quality control for FASTQ", "fastp": "An ultra-fast all-in-one FASTQ preprocessor (QC, adapter trimming, filtering, splitting)", "multiqc": "Report aggregator"}}, "target": "fastp", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_0_1", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "mod_dupradar_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assessment of duplication rates in RNA-Seq datasets (tools: dupradar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "agat_convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "coptr_map": "Maps the reads to the reference database", "dupradar": "Assessment of duplication rates in RNA-Seq datasets"}}, "target": "dupradar", "target_idx": 4}
{"id": "mod_wisecondorx_gender_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Returns the gender of a .npz resulting from convert, based on a Gaussian mixture model trained during the newref phase (tools: wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wisecondorx/gender": "Returns the gender of a .npz resulting from convert, based on a Gaussian mixture model trained during the newr", "lofreq/filter": "Lofreq subcommand to remove variants with low coverage or strand bias potential", "wisecondorx/predict": "Find copy number aberrations", "wisecondorx/newref": "Create a new reference using healthy reference samples", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "wisecondorx/gender", "target_idx": 0}
{"id": "pipe_all101_hadge_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Comprehensive pipeline for donor demultiplexing in single cell. Topics: cell-hashing, deconvolution, demultiplexing, donor-assignment, donor-deconvolution, genetic-demultiplexing. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]"}}, "target": "hadge", "target_idx": 2}
{"id": "resource_baysor_preview_1", "category": "resource_profiling", "state": {"process": "BAYSOR_PREVIEW", "tool": "baysor/preview", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_PREVIEW (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_concoct_extractfastabins_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a FASTA file for each new cluster assigned by CONCOCT (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct_concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "hamronization_fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "openms_peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length."}}, "target": "concoct_extractfastabins", "target_idx": 1}
{"id": "mod_genmod_score_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score the variants of a vcf based on their annotation (tools: genmod)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmod_score": "Score the variants of a vcf based on their annotation", "tmb_pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "last_lastal": "Aligns query sequences to target sequences indexed with lastdb", "krakenuniq_download": "Download KrakenUniq databases and related fles", "plink2_score": "Apply a scoring system to each sample in a plink 2 fileset"}}, "target": "genmod_score", "target_idx": 0}
{"id": "mod_agat_sqstatbasic_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides basic statistics in text format from a GFF/GTF annotation file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "agat_sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file", "methyldackel_mbias": "Generates methylation bias plots from alignments", "angsd_contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome.", "agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file"}}, "target": "agat_sqstatbasic", "target_idx": 1}
{"id": "resource_atlas_recal_3", "category": "resource_profiling", "state": {"process": "ATLAS_RECAL", "tool": "atlas/recal", "description": "Gives an estimation of the sequencing bias based on known invariant sites"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_RECAL (Gives an estimation of the sequencing bias based on known invariant sites) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_channel_mix_operator_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_amps_0", "category": "resource_profiling", "state": {"process": "AMPS", "tool": "amps", "description": "Post-processing script of the MaltExtract component of the HOPS package"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPS (Post-processing script of the MaltExtract component of the HOPS package) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_49", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bcftools_view_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_VIEW", "tool": "bcftools/view", "description": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_VIEW (View, subset and filter VCF or BCF files by position and filtering expression. C) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_humann3_humann_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functional analysis of metagenome or metatranscriptome data (tools: humann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"duckdb/table2parquet": null, "humann3/renorm": null, "humann3/humann": null, "smoothxg": null, "argnorm": null}}, "target": "humann3/humann", "target_idx": 2}
{"id": "resource_bcftools_concat_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONCAT", "tool": "bcftools/concat", "description": "Concatenate VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONCAT (Concatenate VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_confusing_combine_with_mix_semantics_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_apbs_0", "category": "resource_profiling", "state": {"process": "APBS", "tool": "apbs", "description": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Boltzmann Solver). Produces electrostatic potential\nmaps and solvation energy values for large biomolecular assemblages."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to APBS (Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nus) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_agat_convertgff2bed_5", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTGFF2BED", "tool": "agat/convertgff2bed", "description": "Takes a GFF3 file and converts to a bed12 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTGFF2BED (Takes a GFF3 file and converts to a bed12 file) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_snapaligner_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using SNAP (tools: snapaligner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_tnfilter": "Filters the raw output of sentieon/tnhaplotyper2.", "nanoq": "Nanoq implements ultra-fast read filters and summary reports for high-throughput nanopore reads.", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "snapaligner_align": "Performs fastq alignment to a fasta reference using SNAP", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins"}}, "target": "snapaligner_align", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_4", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_bam2fastx_bam2fastq_3", "category": "resource_profiling", "state": {"process": "BAM2FASTX_BAM2FASTQ", "tool": "bam2fastx/bam2fastq", "description": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAM2FASTX_BAM2FASTQ (Conversion of PacBio BAM files into gzipped fastq files, including splitting of ) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_bftools_showinf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract OME xml data from OME-tif (tools: bftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crabz_compress": null, "parsesdrf_convert": null, "bamaligncleaner": null, "bftools_showinf": null, "ffq": null}}, "target": "bftools_showinf", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_19", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Multiplexed Oxford Nanopore run with barcode demultiplexing)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Multiplexed Oxford Nanopore run with barcode demultiplexing.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "samplesheet_arch_pediatric_trio_somatic_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents))", "question": {"type": "choice", "instructions": "Which columns are standard for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) input samplesheet?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_21", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_survivor_simsv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simulate an SV VCF file based on a reference genome (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender/removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "caddsv/run": "Score structural variants with CADD-SV.", "yara/index": "Builds a YARA index for a reference genome", "annotsv/installannotations": "Install the AnnotSV annotations", "survivor/simsv": "Simulate an SV VCF file based on a reference genome"}}, "target": "survivor/simsv", "target_idx": 4}
{"id": "pipe_all101_kmermaid_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze k-mer similarity analysis pipeline. Topics: k-mer, kmer, kmer-counting, kmer-frequency-count. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 "}}, "target": "kmermaid", "target_idx": 5}
{"id": "mod_ganon_table_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a multi-sample report file from the output of ganon report runs (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "leafcutter/differentialsplicing": null, "binette": null, "ganon/table": null, "quarto/prerender": null}}, "target": "ganon/table", "target_idx": 3}
{"id": "pipe_all101_pairgenomealign_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for comparative-genomics. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]"}}, "target": "pairgenomealign", "target_idx": 2}
{"id": "mod_fasta_consensus_autocycler_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler (tools: fasta_consensus_autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_compress": "Package candidate assemblies for clustering by Autocycler.", "rpbp_preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "busco_plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "autocycler_combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler.", "fasta_consensus_autocycler": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler"}}, "target": "fasta_consensus_autocycler", "target_idx": 4}
{"id": "samplesheet_arch_cutandrun_pe_8_0", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control", "pipeline": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "mod_falco_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run falco on sequenced reads (tools: fastqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dssp_mkdssp": null, "biscuit_qc": null, "falco": null, "samtools_quickcheck": null, "busco_plot": null}}, "target": "falco", "target_idx": 2}
{"id": "resource_bwafastalign_index_4", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_INDEX", "tool": "bwafastalign/index", "description": "Create BWA-FASTALIGN index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_INDEX (Create BWA-FASTALIGN index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "resource_bismark_align_3", "category": "resource_profiling", "state": {"process": "BISMARK_ALIGN", "tool": "bismark/align", "description": "Performs alignment of BS-Seq reads using bismark"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_ALIGN (Performs alignment of BS-Seq reads using bismark) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_expected_cells_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "mod_ultraplex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ultraplex is an all-in-one software package for processing and demultiplexing fastq files. (tools: ultraplex)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mgikit/demultiplex": "Demultiplex MGI fastq files", "bcl2fastq": "Demultiplex Illumina BCL files", "trust4": "Run TRUST4 on RNA-seq data", "deeptools/plotheatmap": "plots values produced by deeptools_computematrix as a heatmap", "ultraplex": "Ultraplex is an all-in-one software package for processing and demultiplexing fastq files."}}, "target": "ultraplex", "target_idx": 4}
{"id": "mod_muse_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pre-filtering and calculating position-specific summary statistics using the Markov substitution model (tools: MuSE)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "somalier/relate": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "bcftools/concat": "Concatenate VCF files", "muse/call": "pre-filtering and calculating position-specific summary statistics using the Markov substitution model"}}, "target": "muse/call", "target_idx": 4}
{"id": "mod_suppa_psiperevent_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate PSI values for alternative splicing events using SUPPA (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_minimap2": "NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference da", "suppa_psiperevent": "Calculate PSI values for alternative splicing events using SUPPA", "fastq_align_bamcmp_bwa": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better", "leafcutter_differentialsplicing": "Perform differential splicing analysis to identify junctions with significant changes in splicing between cond", "suppa_generateevents": "Generates alternative splicing events from a GTF file using SUPPA."}}, "target": "suppa_psiperevent", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Parse Biosciences Split-seq combinatorial barcoding)", "question": {"type": "choice", "instructions": "Which columns are standard for Parse Biosciences Split-seq combinatorial barcoding input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 2}
{"id": "local_subworkflow_irma_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should IRMA (irma) be built?", "criteria": {"Local subworkflow IRMA": null, "Use nf-core subworkflow irma": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow IRMA", "target_idx": 0}
{"id": "schema_std_callingcards_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/callingcards", "description": "A pipeline for processing calling cards data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/callingcards?", "criteria": {"sample,fastq_1,fastq_2,barcode_details": null, "sample,id,data_path,fastq_dir,cytaimage": null, "sample,fastq_1,fastq_2,library_id,lane": null, "ID,R1,R2,LongFastQ,Fast5": null}}, "target": "sample,fastq_1,fastq_2,barcode_details", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral amplicon sequencing with primers", "data_format": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end tiled viral amplicon FASTQs per clinical swab sample?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_hlala_typing_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs HLA typing based on a population reference graph and employs a new linear projection method to align reads to the graph. (tools: hlala)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"t1k_run": "write your description here", "pyrodigal": "Pyrodigal is a Python module that provides bindings to Prodigal, a fast, reliable protein-coding gene predicti", "antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "hlala_typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}}, "target": "hlala_typing", "target_idx": 3}
{"id": "mod_gatk4_leftalignandtrimvariants_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Left align and trim variants using GATK4 LeftAlignAndTrimVariants. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4_leftalignandtrimvariants": "Left align and trim variants using GATK4 LeftAlignAndTrimVariants.", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}}, "target": "gatk4_leftalignandtrimvariants", "target_idx": 1}
{"id": "mod_freyja_variants_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: call variant and sequencing depth information of the variant (tools: freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja_demix": "specify the relative abundance of each known haplotype", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3", "gatk4_mergebamalignment": "Merge unmapped with mapped BAM files", "freyja_update": "downloads new versions of the curated SARS-CoV-2 lineage file and barcodes", "freyja_variants": "call variant and sequencing depth information of the variant"}}, "target": "freyja_variants", "target_idx": 4}
{"id": "noul_include_modular_process_syntax_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "field_constraint_phenotype_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null, "format: file-path": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "mod_samtools_coverage_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: produces a histogram or table of coverage per chromosome (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/coverage": "produces a histogram or table of coverage per chromosome", "jvarkit/wgscoverageplotter": "Plot whole genome coverage from BAM/CRAM file as SVG", "fastq_removeadapters_merge": "Remove adapters and merge reads based on various module choices", "pilon": "Automatically improve draft assemblies and find variation among strains, including large event detection", "metabat2/metabat2": "Metagenome binning of contigs"}}, "target": "samtools/coverage", "target_idx": 0}
{"id": "field_constraint_phenotype_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 1}
{"id": "mod_rseqc_inferexperiment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Infer strandedness from sequencing reads (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "taxonkit/lineage": "Convert taxonids to taxon lineages", "rseqc/inferexperiment": "Infer strandedness from sequencing reads", "entrezdirect/esearch": "Searches a term in a public NCBI database"}}, "target": "rseqc/inferexperiment", "target_idx": 3}
{"id": "mod_seqtk_comp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes sequence statistics from FASTQ or FASTA files (tools: seqtk_comp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_fastqtosam": "Converts a FASTQ file to an unaligned BAM or SAM file.", "seqtk_trim": "Trim low quality bases from FastQ files", "manta_germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "seqtk_sample": "Subsample reads from FASTQ files", "seqtk_comp": "Computes sequence statistics from FASTQ or FASTA files"}}, "target": "seqtk_comp", "target_idx": 4}
{"id": "noul_confusing_combine_with_mix_semantics_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "schema_std_funcscan_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/funcscan. Description: (Meta-)genome screening for functional and natural product gene sequences.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/funcscan.", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,fasta,protein,gbk,gff": null, "sample,fastq_1,fastq_2,rundir,tags": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null}}, "target": "sample,fasta,protein,gbk,gff", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Single-end Oxford Nanopore direct RNA", "data_format": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fast5": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_checkv_updatedatabase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct the database necessary for checkv's quality assessment (tools: checkv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star/genomegenerate": "Create index for STAR", "checkm2/predict": "CheckM2 bin quality prediction", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "checkm/lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "checkv/updatedatabase": "Construct the database necessary for checkv's quality assessment"}}, "target": "checkv/updatedatabase", "target_idx": 4}
{"id": "resource_bigslice_bigslice_4", "category": "resource_profiling", "state": {"process": "BIGSLICE_BIGSLICE", "tool": "bigslice/bigslice", "description": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenBank format along with an HMM database and produces a SQLite database and FASTA outputs of predicted features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_BIGSLICE (A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nI) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gcta_calculateldscores_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate LD scores with GCTA and derive GREML-LDMS SNP groups (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "scvitools/solo": "Detect doublets in single-cell RNA-Seq data", "gcta/calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups", "sourcepredict": "Classifies and predicts the origin of metagenomic samples", "gcta/grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`"}}, "target": "gcta/calculateldscores", "target_idx": 2}
{"id": "mod_sageproteomics_sage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: sage is a search software for proteomics data (tools: sageproteomics)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_vcf": "Import variant genetic data using plink2", "diamond_linclust": "Fast protein sequence clustering using a greedy incremental approach", "diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "samtools_cramsize": "List CRAM Content-ID and Data-Series sizes", "sageproteomics_sage": "sage is a search software for proteomics data"}}, "target": "sageproteomics_sage", "target_idx": 4}
{"id": "mod_meryl_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A genomic k-mer counter (and sequence utility) with nice features. (tools: meryl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon/classify": null, "meryl/count": null, "fastk/fastk": null, "barrnap": null, "force/tileextent": null}}, "target": "meryl/count", "target_idx": 1}
{"id": "subworkflow_pkg_bam_qc_picard_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_PICARD", "modules": ["picard/collectmultiplemetrics", "picard/collectwgsmetrics", "picard/collecthsmetrics"], "description": "Produces comprehensive statistics from BAM file"}, "question": {"type": "choice", "instructions": "How should BAM_QC_PICARD (picard/collectmultiplemetrics, picard/collectwgsmetrics, picard/collecthsmetrics) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_qc_picard": null, "Local subworkflow BAM_QC_PICARD": null}}, "target": "Use nf-core subworkflow bam_qc_picard", "target_idx": 2}
{"id": "field_constraint_sex_1_7", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "mod_suppa_diffsplice_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform differential splicing analysis using SUPPA. (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rmats_prep": "MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data.", "bedtools_groupby": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another col", "suppa_diffsplice": "Perform differential splicing analysis using SUPPA.", "gapseq_fill": "Perform gap filling on draft metabolic model", "leafcutter_differentialsplicing": "Perform differential splicing analysis to identify junctions with significant changes in splicing between cond"}}, "target": "suppa_diffsplice", "target_idx": 2}
{"id": "mod_mosdepth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates genome-wide sequencing coverage. (tools: mosdepth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/haplotypecaller": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating GATK haplotypecaller.", "mosdepth": "Calculates genome-wide sequencing coverage.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bamclipper": "This module is used to clip primer sequences from your alignments.", "fastq_removeadapters_merge": "Remove adapters and merge reads based on various module choices"}}, "target": "mosdepth", "target_idx": 1}
{"id": "noul_default_empty_channel_behavior_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "local_subworkflow_nextclade_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for NEXTCLADE (nextclade/run).", "criteria": {"Use nf-core subworkflow nextclade": null, "Leave them out": null, "Local subworkflow NEXTCLADE": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 2}
{"id": "mod_emboss_revseq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: the revseq program from emboss reverse complements a nucleotide sequence (tools: emboss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_cluster": "Cluster replicons in compressed assemblies with Autocycler.", "president": "Calculate pairwise nucleotide identity with respect to a reference sequence", "emboss_revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "miniasm": "A very fast OLC-based de novo assembler for noisy long reads", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "emboss_revseq", "target_idx": 2}
{"id": "mod_vt_normalize_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: normalizes variants in a VCF file (tools: vt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon/table": "Generate a multi-sample report file from the output of ganon report runs", "variantextractor": "Deterministic and standard extractor of SNVs, indels and structural variants (SVs)\nfrom VCF files. Homogenizes", "vt/normalize": "normalizes variants in a VCF file", "truvari/segment": "Normalization of SVs into disjointed genomic regions", "hmmer/hmmpress": "compress and index profile database for hmmscan"}}, "target": "vt/normalize", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_5", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_abricate_run_0", "category": "resource_profiling", "state": {"process": "ABRICATE_RUN", "tool": "abricate/run", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_RUN (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_deprecated_dsl1_set_keyword_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_44", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_4_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Nanopore sequencing run with sample to barcode assignment and flowcell type?", "criteria": {"sample,barcode": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_1_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_5_5", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "template": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/taxprofiler, determine the input samplesheet column structure for: Multi-taxonomic profiling of complex metagenomic shotgun reads.", "criteria": {"sample,bam": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Downstream functional annotation of pre-called VCF files", "data_format": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,bam,bai": null, "sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "noul_channel_join_operator_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_bracken_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extends a Kraken2 database to be compatible with Bracken (tools: bracken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_lastdb": "Prepare sequences for subsequent alignment with lastal.", "kraken2_add": "Adds fasta files to a Kraken2 taxonomic database", "conifer": "Calculate confidence scores from Kraken2 output", "bracken_build": "Extends a Kraken2 database to be compatible with Bracken", "fasta_classify_catpack": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack)."}}, "target": "bracken_build", "target_idx": 3}
{"id": "mod_fastq_taxonomic_profile_metaphlan_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn (tools: fastq_taxonomic_profile_metaphlan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_taxonomic_profile_metaphlan": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "fastq_taxonomic_profile_metaphlan", "target_idx": 0}
{"id": "resource_bcftools_stats_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_STATS", "tool": "bcftools/stats", "description": "Generates stats from VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_STATS (Generates stats from VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_gzrt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupted (tools: gzrt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_pair": null, "adapterremoval": null, "gzrt": null, "utils_references": null, "adapterremovalfixprefix": null}}, "target": "gzrt", "target_idx": 2}
{"id": "mod_amplify_predict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: AMPlify is an attentive deep learning model for antimicrobial peptide prediction. (tools: amplify)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "eklipse": "tool for detection and quantification of large mtDNA rearrangements.", "macrel/contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "amplify/predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction."}}, "target": "amplify/predict", "target_idx": 4}
{"id": "mod_motus_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic meta-omics profiling using universal marker genes (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep2_classify": "classification into haplogroups", "haplogrep3_classify": "classification into haplogroups", "seqtk_rename": "Rename sequence names in FASTQ or FASTA files.", "gappa_examinegraft": "Grafts query sequences from phylogenetic placement on the reference tree", "motus_merge": "Taxonomic meta-omics profiling using universal marker genes"}}, "target": "motus_merge", "target_idx": 4}
{"id": "mod_trgt_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualize tandem repeats genotyped by TRGT (tools: trgt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "pairtools/stats": "Calculate pairs statistics", "transdecoder/predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "trgt/plot": "Visualize tandem repeats genotyped by TRGT"}}, "target": "trgt/plot", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_4_1", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "noul_process_conditional_execution_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_ask_question_12", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "ask_question", "target_idx": 1}
{"id": "resource_aardvark_compare_0", "category": "resource_profiling", "state": {"process": "AARDVARK_COMPARE", "tool": "aardvark/compare", "description": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_COMPARE (A tool to evaluate variant calling performance by comparing a query VCF against ) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_0_3", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_nanofilt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtering and trimming of Oxford Nanopore Sequencing data (tools: nanofilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nanofilt": "Filtering and trimming of Oxford Nanopore Sequencing data", "gem2/gemmappability": "Define the mappability of a reference", "mcroni": "Analysis of mcr-1 gene (mobilized colistin resistance) for sequence variation", "chopper": "Filter and trim long read data.", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads."}}, "target": "nanofilt", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cageseq", "assay_type": "CAGE-seq 5-prime capped transcript end sequencing", "data_format": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,tss_bed": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "noul_mix_operator_async_emission_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_fastq_find_mirna_mirdeep2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, processes and replaces any whitespace in sequence IDs, builds a Bowtie index of the genome, and then maps reads using miRDeep2 mapper before identifying known and novel miRNAs. (tools: fastq_find_mirna_mirdeep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirtop_stats": null, "fastq_find_mirna_mirdeep2": null, "leafcutter_clusterregtools": null, "mirtop_counts": null, "ucsc_bigwigaverageoverbed": null}}, "target": "fastq_find_mirna_mirdeep2", "target_idx": 1}
{"id": "field_constraint_bam_0_2", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "pipe_all101_metapep_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: From metagenomes to epitopes and beyond. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": null, "rnafusion": null, "mag": null, "eager": null, "callingcards": null}}, "target": "metapep", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_3", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_include_modular_process_syntax_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_snpsift_annmemcreate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create memory-optimized SnpSift vardb databases from VCF files for use with SnpSift annMem annotation.\nConverts VCF files (e.g. ClinVar, dbSNP, Cosmic) into indexed dataframes for fast lookup. (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "seqkit_split2": "Split single or paired-end fastq.gz files", "picard_mergesamfiles": "Merges multiple BAM files into a single file", "snpsift_annmemcreate": "Create memory-optimized SnpSift vardb databases from VCF files for use with SnpSift annMem annotation.\nConvert", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "snpsift_annmemcreate", "target_idx": 3}
{"id": "resource_bwa_mem_2", "category": "resource_profiling", "state": {"process": "BWA_MEM", "tool": "bwa/mem", "description": "Performs fastq alignment to a fasta reference using BWA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_MEM (Performs fastq alignment to a fasta reference using BWA) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "resource_ascat_5", "category": "resource_profiling", "state": {"process": "ASCAT", "tool": "ascat", "description": "copy number profiles of tumour cells."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASCAT (copy number profiles of tumour cells.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_1", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_5", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_svtk_standardize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert SV calls to a standardized format. (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_gtf_bam_rpbp": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). R", "svtk_baftest": "Performs tests on BAF files", "fastq_trim_fastp_fastqc": "Read QC, fastp trimming and read qc", "svtk_rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format.", "svtk_standardize": "Convert SV calls to a standardized format."}}, "target": "svtk_standardize", "target_idx": 4}
{"id": "subworkflow_pkg_gtf_hybridmerge_gffcompare_2", "category": "subworkflow_packaging", "state": {"subworkflow": "GTF_HYBRIDMERGE_GFFCOMPARE", "modules": ["gffcompare", "gawk", "bedtools/intersect"], "description": "Build a hybrid GTF by classifying a novel-transcript GTF against a reference"}, "question": {"type": "choice", "instructions": "How should GTF_HYBRIDMERGE_GFFCOMPARE (gffcompare, gawk, bedtools/intersect) be structured in DSL2?", "criteria": {"Local subworkflow GTF_HYBRIDMERGE_GFFCOMPARE": null, "Use nf-core subworkflow gtf_hybridmerge_gffcompare": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow gtf_hybridmerge_gffcompare", "target_idx": 1}
{"id": "mod_regenie_step1_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deacon_filter": "Filter DNA sequences using index of reference genome", "gcta_fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "plink_fastepistasis": "Fast Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others.", "regenie_step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions", "regenie_splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs"}}, "target": "regenie_step1", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "data_format": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq with entry step FASTQC.", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "sample,matrix": null, "plate,sample,bam": null, "sample,well,fastq": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_11", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "subworkflow_pkg_bam_dedup_umi_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_UMI", "modules": ["umitools/prepareforrsem", "samtools/sort", "bam_dedup_stats_samtools_umicollapse", "bam_dedup_stats_samtools_umitools", "bam_sort_stats_samtools"], "description": "BAM deduplication with UMI processing for both genome and transcriptome alignments"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_UMI (umitools/prepareforrsem, samtools/sort, bam_dedup_stats_samtools_umicollapse, bam_dedup_stats_samtools_umitools, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow BAM_DEDUP_UMI": null, "Use nf-core subworkflow bam_dedup_umi": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_dedup_umi", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_5_2", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_deprecated_file_output_syntax_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_48", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_12", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_1_4", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,status,bam,bai": null, "sample,vcf": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "mod_fastavalidator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: \"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror log upon validation failure.\" (tools: fasta_validate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastavalidator": "\"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror lo", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "kma/index": "This module wraps the index module of the KMA alignment tool.", "plasmidid": "assembles bacterial plasmids"}}, "target": "fastavalidator", "target_idx": 0}
{"id": "mod_happy_sompy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic variations. (tools: sompy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"truvari/segment": "Normalization of SVs into disjointed genomic regions", "happy/ftxpy": "Somatic VCF Feature Extraction tool from hap.y.", "happy/sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic ", "fgbio/groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "megan/rma2info": "Analyses an RMA file and exports information in text format"}}, "target": "happy/sompy", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_3_1", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for FAIRE-seq / DNAse-seq open chromatin profiling with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_mitorsaw_haplotype_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mitorsaw analyses mitochondrial variants and identifies heteroplasmy and homoplasmy (tools: mitorsaw)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mitorsaw_haplotype": "Mitorsaw analyses mitochondrial variants and identifies heteroplasmy and homoplasmy", "gatk4_haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "cafe": "Analysis of gene family evolution", "fastq_extract_kraken_krakentools": "Extract classified Kraken2 reads by taxonomic id", "gatk4_mutect2": "Call somatic SNVs and indels via local assembly of haplotypes."}}, "target": "mitorsaw_haplotype", "target_idx": 0}
{"id": "mod_pcgr_getref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Get reference to run Personal Cancer Genome Reporter (PCGR) (tools: pcgr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/import": null, "ctatsplicing/startocancerintrons": null, "arriba/download": null, "fqtk": null, "pcgr/getref": null}}, "target": "pcgr/getref", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_2_10", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "schema_std_radseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/radseq. Description: Variant-calling pipeline for Restriction site-associated DNA sequencing (RADseq)..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/radseq.", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "family_id,sample,file_path,hpo_terms,sex": null, "sample,fastq_1,fastq_2,bam,cram": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,fastq_2,umi_barcodes", "target_idx": 0}
{"id": "mod_bam_stats_samtools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces comprehensive statistics from SAM/BAM/CRAM file (tools: bam_stats_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_jaccard": "Calculate Jaccard statistic b/w two feature files.", "assemblyscan": "Assembly summary statistics in JSON format", "fastk_merge": "A tool to merge FastK histograms", "bam_stats_samtools": "Produces comprehensive statistics from SAM/BAM/CRAM file", "mirtop_counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns "}}, "target": "bam_stats_samtools", "target_idx": 3}
{"id": "resource_bcftools_call_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CALL", "tool": "bcftools/call", "description": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily lost in the process of transition under htslib, but will be added back on popular demand.\nThe original calling model can be invoked with the -c option."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CALL (This command replaces the former bcftools view caller.\nSome of the original func) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_bam_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "mod_phantompeakqualtools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: \"This package computes informative enrichment and quality measures\nfor ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq data. It can also be used\nto obtain robust estimates of the predominant fragment length or\ncharacteristic tag shift values in these assays.\" (tools: phantompeakqualtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt/decomposeblocksub": null, "sentieon/readwriter": null, "phantompeakqualtools": null, "genrich": null, "macs2/callpeak": null}}, "target": "phantompeakqualtools", "target_idx": 2}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Single-end Oxford Nanopore direct RNA", "data_format": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Oxford Nanopore direct RNA with entry step NANOPLOT.", "criteria": {"sample,fast5": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_kallisto_quant_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes equivalence classes for reads and quantifies abundances (tools: kallisto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "smoove/call": "smoove simplifies and speeds calling and genotyping SVs for short reads. It also improves specificity by remov", "kallisto/quant": "Computes equivalence classes for reads and quantifies abundances", "fasta_newick_epang_gappa": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in ", "kallistobustools/ref": "index creation for kb count quantification of single-cell data."}}, "target": "kallisto/quant", "target_idx": 2}
{"id": "schema_std_pacvar_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay": "pacvar pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/pacvar (Longread PacBio sequencing processing for WGS and PureTarget)?", "criteria": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,bam,pbi,fail,repeat_id": null, "sample,fastq_1,fastq_2": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "sample,bam,pbi,fail,repeat_id", "target_idx": 1}
{"id": "noul_default_empty_channel_behavior_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_picard_crosscheckfingerprints_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Checks that all data in the set of input files appear to come from the same individual (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa/mem": "Performs fastq alignment to a fasta reference using BWA", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins", "viennarna/rnalfold": "calculate locally stable secondary structures of RNAs", "simpleaf/quant": "simpleaf is a program to simplify and customize the running and configuration of single-cell processing with a", "picard/crosscheckfingerprints": "Checks that all data in the set of input files appear to come from the same individual"}}, "target": "picard/crosscheckfingerprints", "target_idx": 4}
{"id": "mod_bracken_bracken_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken. (tools: bracken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "bracken_build": "Extends a Kraken2 database to be compatible with Bracken", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "custom_addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field", "megan_rma2info": "Analyses an RMA file and exports information in text format"}}, "target": "bracken_bracken", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_46", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_single_hyphen_cli_params_error_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_cnaqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality control of copy number data from bulk WGS assays (tools: cnaqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnaqc": "Quality control of copy number data from bulk WGS assays", "mlst": "Run Torsten Seemann's classic MLST on a genome assembly", "chewbbaca/allelecall": "Determine the allelic profiles of a genome using a pre-defined schema", "minimac4/compressref": "Compression of a reference panel for genotype imputation to `.msav` format", "cnvpytor/callcnvs": "Command line tool for calling CNVs in whole genome sequencing data"}}, "target": "cnaqc", "target_idx": 0}
{"id": "noul_dynamic_resource_allocation_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_oncoanalyser_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A comprehensive cancer DNA/RNA analysis and reporting pipeline. Topics: cancer, clinical, ctdna, dna, exome, longitudinal. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"oncoanalyser": null, "demultiplex": null, "drugresponseeval": null, "crisprseq": null, "hicar": null}}, "target": "oncoanalyser", "target_idx": 0}
{"id": "pipe_all101_oncoanalyser_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for cancer. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "seqsubmit": "nf-core pipeline for data submission to ENA", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri"}}, "target": "oncoanalyser", "target_idx": 1}
{"id": "mod_picard_collectrnaseqmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics from a RNAseq BAM file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_collectrnaseqmetrics": "Collect metrics from a RNAseq BAM file", "circexplorer2_annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse", "ctatsplicing_prepgenomelib": "Reference preparation for CTAT-splicing", "hmmer_hmmemit": "emit sequences from a profile HMM", "custom_addmostseverepli": "Annotate a VEP annotated VCF with the most severe pLi field"}}, "target": "picard_collectrnaseqmetrics", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_0_1", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,mirna_id": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Visium spatial transcriptomics with histology image", "data_format": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,fastq_1,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "noul_confusing_combine_with_mix_semantics_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_spatialaxe_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data. Topics: 10x-genomics, atera, image-processing, spatial, spatial-data-analysis, spatial-transcriptomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"spatialaxe": null, "genomeqc": null, "seqsubmit": null, "cageseq": null, "differentialabundance": null}}, "target": "spatialaxe", "target_idx": 0}
{"id": "resource_bcftools_query_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_QUERY", "tool": "bcftools/query", "description": "Extracts fields from VCF or BCF files and outputs them in user-defined format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_QUERY (Extracts fields from VCF or BCF files and outputs them in user-defined format.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_arriba_visualisation_2", "category": "resource_profiling", "state": {"process": "ARRIBA_VISUALISATION", "tool": "arriba/visualisation", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_VISUALISATION (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_interproscan_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces protein annotations and predictions from an amino acids FASTA file (tools: interproscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlasgeneannotationmanipulation/gtf2featureannotation": null, "interproscan": null, "gmmdemux": null, "last/train": null, "agat/spflagshortintrons": null}}, "target": "interproscan", "target_idx": 1}
{"id": "subworkflow_pkg_bam_create_som_pon_gatk_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CREATE_SOM_PON_GATK", "modules": ["gatk4/mutect2", "gatk4/genomicsdbimport", "gatk4/createsomaticpanelofnormals", "gatk4/mergevcfs", "gatk4/mergemutectstats"], "description": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a genomicsdbworkspace using genomicsdbimport, then use this to create a panel of normals using createsomaticpanelofnormals."}, "question": {"type": "choice", "instructions": "How should BAM_CREATE_SOM_PON_GATK (gatk4/mutect2, gatk4/genomicsdbimport, gatk4/createsomaticpanelofnormals, gatk4/mergevcfs, gatk4/mergemutectstats) be structured in DSL2?", "criteria": {"Local subworkflow BAM_CREATE_SOM_PON_GATK": null, "Use nf-core subworkflow bam_create_som_pon_gatk": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_create_som_pon_gatk", "target_idx": 1}
{"id": "mod_grabix_check_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Checks if the input file is bgzip compressed or not (tools: grabix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crabz/compress": "Compress files with crabz", "grabix/check": "Checks if the input file is bgzip compressed or not", "spaceranger/mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command", "scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler."}}, "target": "grabix/check", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_38", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_odgi_draw_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Draw previously-determined 2D layouts of the graph with diverse annotations. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi_unchop": "Merge unitigs into a single node preserving the node order.", "bowtie2_build": "Builds bowtie index for reference genome", "odgi_draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "panacus_visualize": "Create visualizations from a tsv coverage histogram created with panacus.", "odgi_build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1."}}, "target": "odgi_draw", "target_idx": 2}
{"id": "schema_std_bamtofastq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/bamtofastq. Description: Converts bam or cram files to fastq format and does quality control..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/bamtofastq.", "criteria": {"sample,tools,file,index": null, "sample_id,mapped,index,file_type": null, "sample,fastq_1,fastq_2,antibody,control": null, "vcf,fasta,genome,site,source": null}}, "target": "sample_id,mapped,index,file_type", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_consensus_autocycler_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CONSENSUS_AUTOCYCLER", "modules": ["autocycler/compress", "autocycler/cluster", "autocycler/trim", "autocycler/resolve", "autocycler/combine"], "description": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler"}, "question": {"type": "choice", "instructions": "How should FASTA_CONSENSUS_AUTOCYCLER (autocycler/compress, autocycler/cluster, autocycler/trim, autocycler/resolve, autocycler/combine) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTA_CONSENSUS_AUTOCYCLER": null, "Leave them out": null, "Use nf-core subworkflow fasta_consensus_autocycler": null}}, "target": "Use nf-core subworkflow fasta_consensus_autocycler", "target_idx": 3}
{"id": "mod_genometester4_glistmaker_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create and count k-mer lists from nucelotide sequences. (tools: genometester4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast_updateblastdb": "Downloads a BLAST database from NCBI", "hypo": "Assembly polisher using short (and long) reads", "metacache_build": "Taxonomic profiling database building with MetaCache", "cobiontid_kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written", "genometester4_glistmaker": "Create and count k-mer lists from nucelotide sequences."}}, "target": "genometester4_glistmaker", "target_idx": 4}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_4_0", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate", "pipeline": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_4_3", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "template": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "field_constraint_fastq_2_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "resource_abra2_3", "category": "resource_profiling", "state": {"process": "ABRA2", "tool": "abra2", "description": "Assembly Based ReAligner for next-generation sequencing data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRA2 (Assembly Based ReAligner for next-generation sequencing data) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_gcta_fastgwa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/adjustgrm": null, "gcta/fastgwa": null, "caalm/caalm": null, "bamclipper": null, "gcta/bivariateremlldms": null}}, "target": "gcta/fastgwa", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: Fungal ITS1/ITS2 marker gene amplicon surveillance)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,primer_its1,primer_its2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_cellrangerarc_mkref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkref command. (tools: cellrangerarc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc_mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkref c", "plink2_pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "gatk4_germlinecnvcaller": "Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPlo", "bowtie_build": "Create bowtie index for reference genome", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously"}}, "target": "cellrangerarc_mkref", "target_idx": 0}
{"id": "field_constraint_fastq_1_1_5", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"type: integer": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "field_constraint_sex_3_9", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "resource_bwafastalign_mem_5", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_MEM", "tool": "bwafastalign/mem", "description": "Performs fastq alignment to a fasta reference using BWA-FastAlign."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_MEM (Performs fastq alignment to a fasta reference using BWA-FastAlign.) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "mod_bamstats_generalstats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: bamstats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_pmd": null, "chopper": null, "picard_meanqualitybycycle": null, "ascat": null, "bamstats_generalstats": null}}, "target": "bamstats_generalstats", "target_idx": 4}
{"id": "subworkflow_pkg_vcf_impute_minimac4_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_MINIMAC4", "modules": ["minimac4/compressref", "minimac4/impute", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute VCF files using MINIMAC4 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_MINIMAC4 (minimac4/compressref, minimac4/impute, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Use nf-core subworkflow vcf_impute_minimac4": null, "Leave them out": null, "Local subworkflow VCF_IMPUTE_MINIMAC4": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_impute_minimac4", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_23", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_hicap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify cap locus serotype and structure in your Haemophilus influenzae assemblies (tools: hicap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "bowtie2_build": "Builds bowtie index for reference genome", "hicap": "Identify cap locus serotype and structure in your Haemophilus influenzae assemblies", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "yara_index": "Builds a YARA index for a reference genome"}}, "target": "hicap", "target_idx": 2}
{"id": "mod_abricate_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Screen assemblies for antimicrobial resistance against multiple databases (tools: abricate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"splitubam": "split one ubam into multiple, per line, fast", "antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "cat_fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "abricate_run", "target_idx": 4}
{"id": "mod_comebin_runcomebin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning (tools: comebin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"comebin/runcomebin": null, "bracken/bracken": null, "utils_nfschema_plugin": null, "amps": null, "samtools/quickcheck": null}}, "target": "comebin/runcomebin", "target_idx": 0}
{"id": "mod_vcfanno_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: quickly annotate your VCF with any number of INFO fields from any number of VCFs or BED files (tools: vcfanno)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/cleansam": null, "parabricks/minimap2": null, "bcftools/annotate": null, "atlas/call": null, "vcfanno": null}}, "target": "vcfanno", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_align_mapad_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_MAPAD", "modules": ["mapad/map", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_MAPAD (mapad/map, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_MAPAD": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_mapad": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_mapad", "target_idx": 2}
{"id": "schema_std_mhcquant_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mhcquant", "description": "Identify and quantify MHC eluted peptides from mass spectrometry raw data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/mhcquant?", "criteria": {"sample,fastq_1,strandedness": null, "sample,fasta,protein,gbk,gff": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "ID,Sample,Condition,ReplicateFileName,Fasta", "target_idx": 3}
{"id": "mod_foldseek_createdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a database from protein structures (tools: foldseek)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cdhit/cdhit": "Cluster protein sequences using sequence similarity", "bcftools/csq": "bcftools Haplotype-aware consequence caller", "plink2/filter": "Filters plink bfiles or pfiles with filters such as maf or var", "deacon/indexunion": "Combine multiple deacon indexes (A ∪ B ...)", "foldseek/createdb": "Create a database from protein structures"}}, "target": "foldseek/createdb", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_2_40", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_1", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "schema_std_methylarray_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylarray", "assay": "methylarray pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/methylarray (Process methylation data from Illumina arrays. Pre-processin)?", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample_id,idat_red,idat_green,group": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "sample_id,idat_red,idat_green,group", "target_idx": 2}
{"id": "mod_hiphase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across multiple BAM files and samples (tools: hiphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hiphase": "Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across ", "hifiasm": "Whole-genome assembly using PacBio HiFi reads", "seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA", "blast/blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database"}}, "target": "hiphase", "target_idx": 0}
{"id": "mod_gatk4_asereadcounter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_query": null, "gatk4_baserecalibrator": null, "vcflib_vcfbreakmulti": null, "jupyternotebook": null, "gatk4_asereadcounter": null}}, "target": "gatk4_asereadcounter", "target_idx": 4}
{"id": "mod_paraclu_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Paraclu finds clusters in data attached to sequences. (tools: paraclu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_collectduplexseqmetrics": "Collects a suite of metrics to QC duplex sequencing data.", "csvtk_sort": "Sort  CSV (or TSV) tables", "paraclu": "Paraclu finds clusters in data attached to sequences.", "clame": "binning of metagenomic sequences", "shapeit5_phasecommon": "Tool to phase common sites, typically SNP array data, or the first step of WES/WGS data."}}, "target": "paraclu", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_5_3", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral amplicon sequencing with primers.", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bwamem2_index_3", "category": "resource_profiling", "state": {"process": "BWAMEM2_INDEX", "tool": "bwamem2/index", "description": "Create BWA-mem2 index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAMEM2_INDEX (Create BWA-mem2 index for reference genome) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_high", "target_idx": 1}
{"id": "resource_bff_1", "category": "resource_profiling", "state": {"process": "BFF", "tool": "bff", "description": "Generating cell hashing calls from a matrix of count data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFF (Generating cell hashing calls from a matrix of count data.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_pypgx_runngspipeline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PyPGx pharmacogenomics genotyping pipeline for NGS data. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx_computecontrolstatistics": "Compute summary statistics for control gene from BAM files.", "pypgx_runngspipeline": "PyPGx pharmacogenomics genotyping pipeline for NGS data.", "seqkit_tab2fx": "Convert tabular format (first two/three columns) to FASTA/Q format.", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "cellsnp_modea": "Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A "}}, "target": "pypgx_runngspipeline", "target_idx": 1}
{"id": "pipe_all101_crisprseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`).. Topics: crispr, crispr-analysis, crispr-cas, ngs. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous"}}, "target": "crisprseq", "target_idx": 6}
{"id": "samplesheet_arch_cutandrun_pe_8_1", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,spikein,fastq": null, "sample,bam": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "mod_mindagap_duplicatefinder_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: marks duplicate spots along gridline edges. (tools: mindagap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope", "bftools_showinf": "Extract OME xml data from OME-tif", "mindagap_duplicatefinder": "marks duplicate spots along gridline edges.", "fungtion_fungtion": "Predicts fungal effector proteins from protein FASTA sequences using ESM-1b\nprotein language model embeddings ", "tcoffee_irmsd": "Computes the irmsd score for a given alignment and the structures."}}, "target": "mindagap_duplicatefinder", "target_idx": 2}
{"id": "noul_named_process_output_emits_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_8_0", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_31", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_channel_join_operator_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_5_4", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic cancer variant calling with tumor-normal pairs.", "criteria": {"patient,sample,status,bam,bai": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_42", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_blat_2", "category": "resource_profiling", "state": {"process": "BLAT", "tool": "blat", "description": "Queries a sequence subject"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAT (Queries a sequence subject) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_agat_spfilterbyorfsize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The script reads a gff annotation file, and create two output files, one contains the gene models with ORF passing the test, the other contains the rest. By default the test is \"> 100\" that means all gene models that have ORF longer than 100 Amino acids, will pass the test. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": null, "fgbio_sortbam": null, "angsd_dosaf": null, "agat_spfilterbyorfsize": null, "ampcombi2_cluster": null}}, "target": "agat_spfilterbyorfsize", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Standard Paired-end Whole Genome Sequencing (WGS)", "data_format": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Standard Paired-end Whole Genome Sequencing (WGS) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,group": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_angsd_docounts_2", "category": "resource_profiling", "state": {"process": "ANGSD_DOCOUNTS", "tool": "angsd/docounts", "description": "Calculates base frequency statistics across reference positions from BAM."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOCOUNTS (Calculates base frequency statistics across reference positions from BAM.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_exit_code_137_cause_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_scvitools_scar_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use scAR to remove ambient RNA from single-cell RNA-seq data (tools: scvitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "scvitools/scar": "Module to use scAR to remove ambient RNA from single-cell RNA-seq data", "cellbender/merge": "Module to use CellBender to remove ambient RNA from single-cell RNA-seq data", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "scvitools/scar", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_0", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_channel_mix_operator_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_drop_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": null, "genomeqc": null, "drop": null, "raredisease": null, "ampliseq": null, "scrnaseq": null, "hlatyping": null, "mag": null, "sopa": null, "dualrnaseq": null}}, "target": "drop", "target_idx": 2}
{"id": "resource_atlasgeneannotationmanipulation_gtf2featureannotation_3", "category": "resource_profiling", "state": {"process": "ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION", "tool": "atlasgeneannotationmanipulation/gtf2featureannotation", "description": "Generate tables of feature metadata from GTF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION (Generate tables of feature metadata from GTF files) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_glimpse_phase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"authentict/deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries", "quantmsutils/diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils", "glimpse/phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods", "bcftools/pluginimputeinfo": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO met", "whatshap/stats": "Compute statistics from phased variant file using Whatshap"}}, "target": "glimpse/phase", "target_idx": 2}
{"id": "mod_bcftools_query_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts fields from VCF or BCF files and outputs them in user-defined format. (tools: query)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ssuissero": "Serotype prediction of Streptococcus suis assemblies", "parabricks/genotypegvcf": "NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs", "bcftools/query": "Extracts fields from VCF or BCF files and outputs them in user-defined format.", "sylph/query": "Sylph query command for querying genome databases against reads/metagenomes", "entrezdirect/esummary": "Queries an NCBI database using Unique Identifier(s)"}}, "target": "bcftools/query", "target_idx": 2}
{"id": "field_constraint_phenotype_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [normal, tumor]": null, "type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "mod_humid_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: HUMID is a tool to quickly and easily remove duplicate reads from FASTQ files, with or without UMIs. (tools: humid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"barrnap": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files", "topas/gencons": "Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage presen", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "humid": "HUMID is a tool to quickly and easily remove duplicate reads from FASTQ files, with or without UMIs.", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl"}}, "target": "humid", "target_idx": 3}
{"id": "schema_std_cutandrun_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "description": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/cutandrun?", "criteria": {"sample,fastq_1,fastq_2,fasta,run_accession": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,bam,pbi,fail,repeat_id": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "fastq_1,fastq_2,group,replicate,control", "target_idx": 1}
{"id": "mod_scramble_clusteridentifier_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The cluster_identifier tool of Scramble identifies soft clipped clusters (tools: scramble)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": null, "ascat": null, "scramble/clusteridentifier": null, "humann3/regroup": null, "seqkit/stats": null}}, "target": "scramble/clusteridentifier", "target_idx": 2}
{"id": "mod_mudskipper_bulk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert genomic BAM/SAM files to transcriptomic BAM/RAD files. (tools: mudskipper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "mudskipper_bulk": "Convert genomic BAM/SAM files to transcriptomic BAM/RAD files.", "fastawindows": "Quickly compute statistics over a fasta file in windows.", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "bcftools_filter": "Filters VCF files"}}, "target": "mudskipper_bulk", "target_idx": 1}
{"id": "resource_biscuit_index_4", "category": "resource_profiling", "state": {"process": "BISCUIT_INDEX", "tool": "biscuit/index", "description": "Indexes a reference genome for use with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_INDEX (Indexes a reference genome for use with Biscuit) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_agat_spextractsequences_3", "category": "resource_profiling", "state": {"process": "AGAT_SPEXTRACTSEQUENCES", "tool": "agat/spextractsequences", "description": "This script extracts sequences in fasta format according to features described\nin a gff file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPEXTRACTSEQUENCES (This script extracts sequences in fasta format according to features described\ni) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_angsd_contamination_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink/vcf": "Analyses variant calling files using plink", "angsd/gl": "Calculated genotype likelihoods from BAM files.", "carveme/carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "angsd/docounts": "Calculates base frequency statistics across reference positions from BAM.", "angsd/contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome."}}, "target": "angsd/contamination", "target_idx": 4}
{"id": "resource_bedtools_map_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAP", "tool": "bedtools/map", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAP (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_45", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_10", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_parabricks_fq2bammeth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to a reference genome, performing local alignment, and producing alignment for different parts of the query sequence (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/estimatelibrarycomplexity": "Estimates the numbers of unique molecules in a sequencing library.", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "rattle/cluster": "Reference-free reconstruction and quantification of transcriptomes from long-read sequencing", "parabricks/fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to "}}, "target": "parabricks/fq2bammeth", "target_idx": 4}
{"id": "pipe_all101_drop_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for drop analysis? Specific context: Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]"}}, "target": "drop", "target_idx": 3}
{"id": "field_constraint_bai_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "pipe_all101_metaboigniter_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for identification analysis? Specific context: Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data.. Topics: identification, mass-spectrometry, metabolomics, ms1, ms2, quantification. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]"}}, "target": "metaboigniter", "target_idx": 1}
{"id": "mod_hifitrimmer_processblast_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrimary output is a BED describing regions to exclude, a json of summary information, and an optional hits file. (tools: hifi-trimmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dedup": null, "hifitrimmer/processblast": null, "hificnv": null, "coptr/estimate": null, "hifiasm": null}}, "target": "hifitrimmer/processblast", "target_idx": 1}
{"id": "resource_biscuit_bsconv_4", "category": "resource_profiling", "state": {"process": "BISCUIT_BSCONV", "tool": "biscuit/bsconv", "description": "Summarize and/or filter reads based on bisulfite conversion rate"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BSCONV (Summarize and/or filter reads based on bisulfite conversion rate) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcftools_sort_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SORT", "tool": "bcftools/sort", "description": "Sorts VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SORT (Sorts VCF files) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_medium", "target_idx": 0}
{"id": "schema_std_atacseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay": "atacseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/atacseq (ATAC-seq peak-calling and QC analysis pipeline)?", "criteria": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,fastq_2,replicate,control": null}}, "target": "sample,fastq_1,fastq_2,replicate,control", "target_idx": 3}
{"id": "resource_bedtools_unionbedg_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_UNIONBEDG", "tool": "bedtools/unionbedg", "description": "Combines multiple BedGraph files into a single file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_UNIONBEDG (Combines multiple BedGraph files into a single file) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_rnafusion_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: RNA-seq analysis pipeline for detection of gene-fusions. Topics: fusion, fusion-genes, gene-fusion, rna, rna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": null, "multiplesequencealign": null, "rnafusion": null, "references": null, "crisprseq": null, "phaseimpute": null, "circdna": null, "spatialaxe": null}}, "target": "rnafusion", "target_idx": 2}
{"id": "subworkflow_pkg_quantify_rsem_1", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_RSEM", "modules": ["rsem/calculateexpression", "sentieon/rsemcalculateexpression", "custom/rsemmergecounts", "quant_tximport_summarizedexperiment"], "description": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_RSEM (rsem/calculateexpression, sentieon/rsemcalculateexpression, custom/rsemmergecounts, quant_tximport_summarizedexperiment) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow quantify_rsem": null, "Local subworkflow QUANTIFY_RSEM": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow quantify_rsem", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_3_0", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking with entry step FASTQC.", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_rpbp_extractmetageneprofiles_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\". For each read length, the profile\ncounts how many reads of that length have their 5' end at each position\nin a window around every annotated start codon, summed across all\ntranscripts. Looking at the profile across the window reveals whether\nreads of that length show the 3-nucleotide periodicity characteristic\nof translating ribosomes.\n\nThis per-length view matters because different ribosome footprint\nlengths place the ribosomal P-site (the codon being decoded) at\ndifferent offsets from the read's 5' end, so each length needs its\nown offset calibration. Output is consumed by\n`rpbp/estimatemetagenebayesfactors`, which scores each (length, offset)\ncombination for periodicity. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "rpbp/estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "rpbp/extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "qsv/cat": "Concatenate two or more CSV (or TSV) tables into a single table", "cellranger/mkvdjref": "Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref co"}}, "target": "rpbp/extractmetageneprofiles", "target_idx": 2}
{"id": "pipe_all101_demo_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos.. Topics: demo, minimal-example, training, tutorial. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demo": null, "hlatyping": null, "kmermaid": null, "bamtofastq": null, "epitopeprediction": null}}, "target": "demo", "target_idx": 0}
{"id": "subworkflow_pkg_bam_sort_stats_samtools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SORT_STATS_SAMTOOLS", "modules": ["samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Sort SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_SORT_STATS_SAMTOOLS (samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Local subworkflow BAM_SORT_STATS_SAMTOOLS": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_sort_stats_samtools": null}}, "target": "Use nf-core subworkflow bam_sort_stats_samtools", "target_idx": 3}
{"id": "mod_dotseq_dotseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with matched RNA-seq using\nDOTSeq. Wraps DOTSeqDataSetsFromSummarizeOverlaps() + DOTSeq() +\ngetContrasts() and emits the package's native contrast tables plus\nplotDOT() visualisations. (tools: dotseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem3/gem3indexer": "Create a GEM index from a FASTA file", "dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "plastid/metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}}, "target": "dotseq/dotseq", "target_idx": 1}
{"id": "mod_biscuit_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit. (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "fairy_coverage": "Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a Meta", "biscuit_align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "biscuit_index": "Indexes a reference genome for use with Biscuit"}}, "target": "biscuit_align", "target_idx": 2}
{"id": "subworkflow_pkg_vcf_impute_glimpse_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_GLIMPSE", "modules": ["glimpse/chunk", "glimpse/phase", "glimpse/ligate", "bcftools/index"], "description": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_GLIMPSE (glimpse/chunk, glimpse/phase, glimpse/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Local subworkflow VCF_IMPUTE_GLIMPSE": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_impute_glimpse": null}}, "target": "Use nf-core subworkflow vcf_impute_glimpse", "target_idx": 3}
{"id": "pipe_all101_phaseimpute_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A bioinformatics pipeline to phase and impute genetic data. Topics: genomics, genotype, imputation, low-pass-sequencing, phasing. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]"}}, "target": "phaseimpute", "target_idx": 1}
{"id": "noul_channel_factory_inside_process_body_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_1_24", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_samtools_ampliconclip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clips read alignments where they match BED file defined regions (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_ampliconclip": null, "shinyngs_validatefomcomponents": null, "crabs_insilicopcr": null, "apbs": null, "crispresso2": null}}, "target": "samtools_ampliconclip", "target_idx": 0}
{"id": "mod_soupx_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.\n\nThe filtered counts are preprocessed with Seurat (LogNormalize, PCA, kNN graph, clustering) to\nprovide cluster assignments to SoupX, which then estimates per-cluster contamination and adjusts\ncounts. The adjusted counts are written to the output H5AD as an `ambient` layer. (tools: soupx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anndata_barcodes": null, "soupx": null, "anndata_getsize": null, "fastk_histex": null, "graphmap2_align": null}}, "target": "soupx", "target_idx": 1}
{"id": "resource_adapterremovalfixprefix_3", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVALFIXPREFIX", "tool": "adapterremovalfixprefix", "description": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with DeDup."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVALFIXPREFIX (Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names a) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_deprecated_file_output_syntax_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_2_36", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral genome sequencing on Oxford Nanopore MinION / GridION. Input files: Demultiplexed single-end long reads from tiled viral amplicons.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "resource_blobtk_snail_3", "category": "resource_profiling", "state": {"process": "BLOBTK_SNAIL", "tool": "blobtk/snail", "description": "Creates blobtk snail plots."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_SNAIL (Creates blobtk snail plots.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_bam_qc_rnaseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC (featureCounts), RNA-seq-specific QC metrics\n(Qualimap), duplicate rate analysis (dupRadar), and comprehensive RSeQC analysis. (tools: bam_qc_rnaseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paraclu": "Paraclu finds clusters in data attached to sequences.", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "bam_qc_rnaseq": "Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC ", "custom/multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output", "msisensor2/msi": "msisensor2 detection of MSI regions."}}, "target": "bam_qc_rnaseq", "target_idx": 2}
{"id": "mod_kraken2_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds Kraken2 database (tools: kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "bracken_combinebrackenoutputs": null, "seqfu_check": null, "kraken2_build": null, "mmseqs_taxonomy": null}}, "target": "kraken2_build", "target_idx": 3}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/bacass --input samplesheet.csv (Assay: Hybrid bacterial assembly combining short Illumina and long Nanopore reads)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_pydamage_analyze_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Damage parameter estimation for ancient DNA (tools: pydamage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"damageprofiler": "A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage", "ragtag/scaffold": "Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. G", "pydamage/analyze": "Damage parameter estimation for ancient DNA", "seqtk/comp": "Computes sequence statistics from FASTQ or FASTA files", "endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen"}}, "target": "pydamage/analyze", "target_idx": 2}
{"id": "samplesheet_arch_pediatric_trio_somatic_5_5", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents).", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_baysor_run_2", "category": "resource_profiling", "state": {"process": "BAYSOR_RUN", "tool": "baysor/run", "description": "Bayesian segmentation of spatial transcriptomics data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_RUN (Bayesian segmentation of spatial transcriptomics data.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_2_39", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_6_4", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for ATAC-seq chromatin accessibility with biological replicates input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "mod_mlst_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run Torsten Seemann's classic MLST on a genome assembly (tools: mlst)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio/groupreadsbyumi": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,", "ilastik/pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA", "mobsuite/typer": "Bacterial plasmid typing and mobility prediction", "mlst": "Run Torsten Seemann's classic MLST on a genome assembly"}}, "target": "mlst", "target_idx": 4}
{"id": "pipe_all101_pixelator_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB). Topics: molecular-pixelation, pixelator, pixelgen-technologies, proteins, single-cell, single-cell-omics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": null, "mcmicro": null, "pixelator": null, "pathogensurveillance": null, "riboseq": null, "viralrecon": null, "demultiplex": null, "sopa": null, "oncoanalyser": null, "pacvar": null}}, "target": "pixelator", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_3_2", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "MUTECT2", "library_inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic tumor-normal calling from pre-aligned BAM files with entry step MUTECT2.", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "field_constraint_phenotype_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "mod_cobs_classicconstruct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a classic bloom filter COBS index (tools: cobs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_index": "Index VCF tools", "samtools_bedcov": "reports coverage over regions in a supplied BED file", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "cobs_classicconstruct": "Builds a classic bloom filter COBS index", "tbprofiler_profile": "A tool to detect resistance and lineages of M. tuberculosis genomes"}}, "target": "cobs_classicconstruct", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_wgs_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/genomeassembler --input samplesheet.csv (Assay: Long-read Pacific Biosciences HiFi sequencing)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/genomeassembler, determine the input samplesheet column structure for: Long-read Pacific Biosciences HiFi sequencing.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "noul_exit_code_137_cause_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "field_constraint_expected_cells_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "resource_arriba_download_1", "category": "resource_profiling", "state": {"process": "ARRIBA_DOWNLOAD", "tool": "arriba/download", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_DOWNLOAD (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: ATAC-seq chromatin accessibility with biological replicates)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "resource_abyss_abysspe_5", "category": "resource_profiling", "state": {"process": "ABYSS_ABYSSPE", "tool": "abyss/abysspe", "description": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABYSS_ABYSSPE (ABySS is a de novo sequence assembler intended for short paired-end reads and ge) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_trtools_mergestr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file. (tools: trtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization/abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "expansionhunterdenovo/profile": "Compute genome-wide STR profile", "pairtools/merge": "Merge multiple pairs/pairsam files", "expansionhunter": "Estimate repeat sizes using NGS data", "trtools/mergestr": "MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file."}}, "target": "trtools/mergestr", "target_idx": 4}
{"id": "mod_samclip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters SAM/BAM/CRAM files for soft and hard clipped alignments (tools: samclip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rtgtools/rocplot": "Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI is", "diann/insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "bamutil/clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo", "leehom": "Bayesian reconstruction of ancient DNA fragments", "samclip": "Filters SAM/BAM/CRAM files for soft and hard clipped alignments"}}, "target": "samclip", "target_idx": 4}
{"id": "mod_caddsv_get_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download CADD-SV annotation resources or SegmentNT model files. (tools: caddsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_printsvevidence": "WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end an", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "caddsv_get": "Download CADD-SV annotation resources or SegmentNT model files.", "sratools_prefetch": "Download sequencing data from the NCBI Sequence Read Archive (SRA).", "tcoffee_seqreformat": "Reformats files with t-coffee"}}, "target": "caddsv_get", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_7_1", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_bamtofastq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for bamtofastq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods."}}, "target": "bamtofastq", "target_idx": 6}
{"id": "mod_pbtk_pbindex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Minimalistic tool which creates an index file that enables random access into PacBio BAM files (tools: pbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "pbtk_pbindex": "Minimalistic tool which creates an index file that enables random access into PacBio BAM files", "alignoth": "Creating alignment plots from bam files", "vclust_prefilter": "The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by ", "gatk4_createsomaticpanelofnormals": "Create a panel of normals constraining germline and artifactual sites for use with mutect2."}}, "target": "pbtk_pbindex", "target_idx": 1}
{"id": "intent_build_pipeline_16", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "build_pipeline", "target_idx": 0}
{"id": "mod_controlfreec_freec_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number and genotype annotation from whole genome and whole exome sequencing data (tools: controlfreec/freec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krakenuniq/build": "Download and build (custom) KrakenUniq databases", "controlfreec/freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "controlfreec/freec2circos": "Format Freec output to circos input format", "controlfreec/freec2bed": "Plot Freec output", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration"}}, "target": "controlfreec/freec", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_4_1", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "mod_bwa_aln_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find SA coordinates of the input reads for bwa short-read mapping (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3", "picard_collectmultiplemetrics": "Collect multiple metrics from a BAM file", "bwa_aln": "Find SA coordinates of the input reads for bwa short-read mapping"}}, "target": "bwa_aln", "target_idx": 4}
{"id": "mod_deepvariant_callvariants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call variants from the examples produced by make_examples (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_bamcmp_bwa": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better", "atlas/call": "generate VCF file from a BAM file using various calling methods", "deepvariant/callvariants": "Call variants from the examples produced by make_examples", "bcftools/concat": "Concatenate VCF files", "holodeck/simulate": "Simulate sequencing reads from a reference genome with holodeck"}}, "target": "deepvariant/callvariants", "target_idx": 2}
{"id": "mod_gridss_somaticfilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_rsemmergecounts": null, "htseq_count": null, "gridss_extractoverlappingfragments": null, "gridss_annotate": null, "gridss_somaticfilter": null}}, "target": "gridss_somaticfilter", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_0_22", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "field_constraint_status_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "schema_std_createtaxdb_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createtaxdb", "description": "Parallelised and automated construction of metagenomic classifier databases of different tools", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/createtaxdb?", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "id,taxid,fasta_dna,fasta_aa": null}}, "target": "id,taxid,fasta_dna,fasta_aa", "target_idx": 3}
{"id": "mod_kofamscan_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces annotation using kofamscan against a Profile database and a KO list (tools: kofamscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "kofamscan": "Produces annotation using kofamscan against a Profile database and a KO list", "clame": "binning of metagenomic sequences", "stitch": "STITCH is an R program for reference panel free, read aware, low coverage sequencing genotype imputation. STIT", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "kofamscan", "target_idx": 1}
{"id": "pipe_all101_differentialabundance_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for atac-seq analysis? Specific context: Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq. Topics: atac-seq, chip-seq, deseq2, differential-abundance, differential-expression, gsea. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "seqsubmit": "nf-core pipeline for data submission to ENA", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]"}}, "target": "differentialabundance", "target_idx": 5}
{"id": "qc_adapt_targeted_amplicon_2_46", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_rseqc_readduplication_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate read duplication rate (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "rseqc_readduplication": "Calculate read duplication rate", "bcftools_concat": "Concatenate VCF files", "midas_run": "A tool to estimate bacterial species abundance"}}, "target": "rseqc_readduplication", "target_idx": 2}
{"id": "resource_antismash_antismashdownloaddatabases_3", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHDOWNLOADDATABASES", "tool": "antismash/antismashdownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "data_format": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,fasta": null, "sample,bam": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_39", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_45", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_hicar_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/hicar. Description: Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/hicar.", "criteria": {"sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample,bam,pbi,fail,repeat_id": null, "id,taxid,fasta_dna,fasta_aa": null, "fastq_1,fastq_2,group,replicate,md5_1": null}}, "target": "fastq_1,fastq_2,group,replicate,md5_1", "target_idx": 3}
{"id": "resource_arcashla_extract_2", "category": "resource_profiling", "state": {"process": "ARCASHLA_EXTRACT", "tool": "arcashla/extract", "description": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCASHLA_EXTRACT (Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alterna) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_bam_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/hic) for Hi-C chromosome conformation capture mapping. Input files: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hi-C chromosome conformation capture mapping with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wgs_pe_5_3", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Standard Paired-end Whole Genome Sequencing (WGS).", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_octopusv_plotcircos_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file. (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nanoplot": "Run NanoPlot on nanopore-sequenced reads", "fastq_align_dna": "Align fastq files to a reference genome", "svanalyzer/svbenchmark": "SVbenchmark compares a set of “test” structural variants in VCF format to a known truth set (also in VCF forma", "octopusv/plotcircos": "Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file.", "octopusv/stat": "Summarize structural variant statistics from octopusv SVCF files"}}, "target": "octopusv/plotcircos", "target_idx": 3}
{"id": "resource_bclconvert_5", "category": "resource_profiling", "state": {"process": "BCLCONVERT", "tool": "bclconvert", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCLCONVERT (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_dedup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments). (tools: dedup)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools_group": null, "dedup": null, "pints_caller": null, "hapibd": null, "pairtools_dedup": null}}, "target": "dedup", "target_idx": 1}
{"id": "resource_abyss_abysspe_0", "category": "resource_profiling", "state": {"process": "ABYSS_ABYSSPE", "tool": "abyss/abysspe", "description": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABYSS_ABYSSPE (ABySS is a de novo sequence assembler intended for short paired-end reads and ge) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_core10_scrnaseq_2_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Single-cell RNA-seq quantification and cellular barcode demultiplexing for droplet-based protocols.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)"}}, "target": "scrnaseq", "target_idx": 1}
{"id": "noul_invalid_process_communication_via_globals_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_metaeuk_easypredict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotation of eukaryotic metagenomes using MetaEuk (tools: metaeuk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spring_compress": "Fast, efficient, lossless compression of FASTQ files.", "metaeuk_easypredict": "Annotation of eukaryotic metagenomes using MetaEuk", "samtools_markdup": "mark duplicate alignments in a coordinate sorted file", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "metaeuk_easypredict", "target_idx": 1}
{"id": "subworkflow_pkg_bam_dedup_stats_samtools_umicollapse_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_STATS_SAMTOOLS_UMICOLLAPSE", "modules": ["umicollapse", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_STATS_SAMTOOLS_UMICOLLAPSE (umicollapse, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_dedup_stats_samtools_umicollapse": null, "Leave them out": null, "Local subworkflow BAM_DEDUP_STATS_SAMTOOLS_UMICOLLAPSE": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umicollapse", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_5_4", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Single-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "mod_bam_impute_stitch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute BAM files using STITCH software.\nVariants location to impute are obtain through the legend file given.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: bam_impute_stitch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_mpileup": null, "bamclipper": null, "gamma_gamma": null, "bam_impute_stitch": null, "abra2": null}}, "target": "bam_impute_stitch", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_5_2", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Tumor-only somatic variant calling without matched normal.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_krona_ktimporttext_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a Krona chart from text files listing quantities and lineages. (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shinyngs/app": "build and deploy Shiny apps for interactively mining differential abundance data", "deeptools/multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "krona/ktimporttext": "Creates a Krona chart from text files listing quantities and lineages.", "krona/ktimportkrona": "Collect multiple krona reports into a single html file", "cnvpytor/histogram": "calculates read depth histograms"}}, "target": "krona/ktimporttext", "target_idx": 2}
{"id": "noul_publishdir_directive_usage_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_43", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hic", "assay_type": "Hi-C chromosome conformation capture mapping", "data_format": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification?", "criteria": {"sample,bed": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_proteogenomicsdb_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis.. Topics: cosmic, gnomad, protein-databases, proteogenomics, proteomics, pypgatk. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pixelator": null, "dualrnaseq": null, "pacvar": null, "proteogenomicsdb": null, "pathogensurveillance": null, "detaxizer": null, "stableexpression": null, "lsmquant": null}}, "target": "proteogenomicsdb", "target_idx": 3}
{"id": "pipe_all101_seqsubmit_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: nf-core pipeline for data submission to ENA. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": null, "seqsubmit": null, "hlatyping": null, "viralrecon": null, "proteogenomicsdb": null}}, "target": "seqsubmit", "target_idx": 1}
{"id": "resource_antismash_antismashlitedownloaddatabases_0", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES", "tool": "antismash/antismashlitedownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_sample_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "pipe_all101_coproid_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Coprolite host Identification pipeline. Topics: adna, ancient-dna, coprolite, microbiome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeqc": null, "chipseq": null, "diaproteomics": null, "metaboigniter": null, "seqinspector": null, "coproid": null, "pacvar": null, "scnanoseq": null}}, "target": "coproid", "target_idx": 5}
{"id": "mod_snakemake_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Snakemake workflow management system is a tool to create reproducible and scalable data analyses. This module runs a simple Snakemake pipeline based on input snakefile. Expect many limitations.\" (tools: snakemake)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"windowmasker/convert": "Masks out highly repetitive DNA sequences with low complexity in a genome", "bioawk": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats.", "snakemake": "The Snakemake workflow management system is a tool to create reproducible and scalable data analyses. This mod", "hamronization/amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "genmod/annotate": "for annotating regions, frequencies, cadd scores"}}, "target": "snakemake", "target_idx": 2}
{"id": "subworkflow_pkg_vcf_filter_bcftools_ensemblvep_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_FILTER_BCFTOOLS_ENSEMBLVEP", "modules": ["bcftools/view", "ensemblvep/filtervep", "htslib/bgziptabix"], "description": "Filter VCF file with bcftools and filter_vep"}, "question": {"type": "choice", "instructions": "How should VCF_FILTER_BCFTOOLS_ENSEMBLVEP (bcftools/view, ensemblvep/filtervep, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep": null, "Leave them out": null, "Local subworkflow VCF_FILTER_BCFTOOLS_ENSEMBLVEP": null}}, "target": "Use nf-core subworkflow vcf_filter_bcftools_ensemblvep", "target_idx": 1}
{"id": "mod_gatk4_collectreadcounts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects read counts at specified intervals. The count for each interval is calculated by counting the number of read starts that lie in the interval. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "gatk4_collectreadcounts": "Collects read counts at specified intervals. The count for each interval is calculated by counting the number ", "samtools_import": "converts FASTQ files to unmapped SAM/BAM/CRAM", "ascat": "copy number profiles of tumour cells."}}, "target": "gatk4_collectreadcounts", "target_idx": 2}
{"id": "noul_container_environment_specification_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_arcane_filter_1", "category": "resource_profiling", "state": {"process": "ARCANE_FILTER", "tool": "arcane/filter", "description": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCANE_FILTER (Filter GTF annotations and genome sequence for alignment-free single-cell RNA-se) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_pairgenomealign_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results. Topics: comparative-genomics, dot-plot, genomics, last, pairwise-alignment, synteny. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "metapep": "From metagenomes to epitopes and beyond", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]"}}, "target": "pairgenomealign", "target_idx": 0}
{"id": "mod_bam_create_som_pon_gatk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a genomicsdbworkspace using genomicsdbimport, then use this to create a panel of normals using createsomaticpanelofnormals. (tools: bam_create_som_pon_gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "genin2": "Genin2 is a lightining-fast bioinformatic tool to predict genotypes for H5 viruses belonging to the European c", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "bam_create_som_pon_gatk": "Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a geno", "suppa_psiperevent": "Calculate PSI values for alternative splicing events using SUPPA"}}, "target": "bam_create_som_pon_gatk", "target_idx": 3}
{"id": "mod_faa_seqfu_seqkit_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that optionally preprocesses amino acid FASTA sequences\n(seqkit seq/replace/rmdup), computes sequence statistics before and\nafter preprocessing using seqfu stats, and exports MultiQC-compatible\nstatistics and software versions. (tools: faa_seqfu_seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"muscle5_super5": "Muscle is a program for creating multiple alignments of amino acid or nucleotide sequences. This particular mo", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "faa_seqfu_seqkit": "Subworkflow that optionally preprocesses amino acid FASTA sequences\n(seqkit seq/replace/rmdup), computes seque"}}, "target": "faa_seqfu_seqkit", "target_idx": 4}
{"id": "pipe_all101_circdna_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that were generated from cancer and other eukaryotic cells.. Topics: ampliconarchitect, ampliconsuite, circle-seq, circular, dna, eccdna. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": null, "circdna": null, "pacvar": null, "sarek": null, "bacass": null}}, "target": "circdna", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_4_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads with library strandedness?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_openms_peakpickerhires_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool for peak detection in high-resolution profile data (Orbitrap or FTICR) (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms/peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)", "cellrangerarc/count": "Module to use Cell Ranger's ARC pipelines analyze sequencing data produced from Chromium Single Cell ARC. Uses", "barrnap": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files", "thermorawfileparser": "Parses a Thermo RAW file containing mass spectra to an open file format", "openms/fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX"}}, "target": "openms/peakpickerhires", "target_idx": 0}
{"id": "mod_ferrohgvs_normalize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalize HGVS variant descriptions to canonical form with ferro (tools: ferrohgvs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clair3": null, "parabricks_minimap2": null, "graphtyper_genotype": null, "ferrohgvs_normalize": null, "gatk4_unmarkduplicates": null}}, "target": "ferrohgvs_normalize", "target_idx": 3}
{"id": "noul_retry_errorstrategy_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_fastq_align_hisat2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using hisat2 then sort with samtools (tools: fastq_align_hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gfastats": null, "ampcombi2_cluster": null, "samtools_view": null, "fastq_align_hisat2": null, "bbmap_align": null}}, "target": "fastq_align_hisat2", "target_idx": 3}
{"id": "mod_glimpse_phase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_vcf_impute_glimpse2": null, "paragraph_vcf2paragraph": null, "glimpse_phase": null, "rpbp_preparegenome": null, "bcftools_pluginimputeinfo": null}}, "target": "glimpse_phase", "target_idx": 2}
{"id": "resource_busco_plot_2", "category": "resource_profiling", "state": {"process": "BUSCO_PLOT", "tool": "busco/plot", "description": "BUSCO summary plot generation using the built-in 'busco --plot' command"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PLOT (BUSCO summary plot generation using the built-in 'busco --plot' command) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_hisat2_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds HISAT2 index for reference genome (tools: hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metaphlan/metaphlan": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing", "hisat3n/build": "Build HISAT-3N index for nucleotide conversion sequencing alignment", "hisat2/build": "Builds HISAT2 index for reference genome", "plotsr": "Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes.", "bracken/build": "Extends a Kraken2 database to be compatible with Bracken"}}, "target": "hisat2/build", "target_idx": 2}
{"id": "field_constraint_fastq_2_3_13", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_taxonomic_profile_metaphlan_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TAXONOMIC_PROFILE_METAPHLAN", "modules": ["metaphlan/makedb", "metaphlan/metaphlan", "metaphlan/mergemetaphlantables"], "description": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn"}, "question": {"type": "choice", "instructions": "How should FASTQ_TAXONOMIC_PROFILE_METAPHLAN (metaphlan/makedb, metaphlan/metaphlan, metaphlan/mergemetaphlantables) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_taxonomic_profile_metaphlan": null, "Leave them out": null, "Local subworkflow FASTQ_TAXONOMIC_PROFILE_METAPHLAN": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_taxonomic_profile_metaphlan", "target_idx": 0}
{"id": "resource_bigscape_bigscape_0", "category": "resource_profiling", "state": {"process": "BIGSCAPE_BIGSCAPE", "tool": "bigscape/bigscape", "description": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSCAPE_BIGSCAPE (BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clust) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_1_2", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,bam,bai": null, "sample,vcf,tbi": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_41", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: FAIRE-seq / DNAse-seq open chromatin profiling)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for FAIRE-seq / DNAse-seq open chromatin profiling with entry step FASTQC.", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_rastair_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assess positive C->T conversion as a readout for methylation on a genome-wide basis (tools: rastair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_deduplicate": null, "pychopper": null, "bismark_report": null, "trnascanse": null, "rastair_call": null}}, "target": "rastair_call", "target_idx": 4}
{"id": "field_constraint_expected_cells_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "mod_sentieon_tnscope_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, using a Haplotyper algorithm. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clusty": null, "sentieon_collectvcmetrics": null, "sentieon_tnscope": null, "miniprot_align": null, "sentieon_bwamem": null}}, "target": "sentieon_tnscope", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_gxf_busco_plot_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_GXF_BUSCO_PLOT", "modules": ["busco/busco", "busco/plot", "gffread"], "description": "Runs BUSCO for input assemblies and their annotations in GFF/GFF3/GTF format, and creates summary plots using `busco --plot`"}, "question": {"type": "choice", "instructions": "How should FASTA_GXF_BUSCO_PLOT (busco/busco, busco/plot, gffread) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_gxf_busco_plot": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_GXF_BUSCO_PLOT": null}}, "target": "Use nf-core subworkflow fasta_gxf_busco_plot", "target_idx": 0}
{"id": "noul_channel_operator_map_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_proteinannotator_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Generation of sequence-level annotations for amino acid sequences. Topics: annotation, proteomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drop": null, "sopa": null, "nanostring": null, "nanoseq": null, "reportho": null, "bacass": null, "proteinannotator": null, "eager": null}}, "target": "proteinannotator", "target_idx": 6}
{"id": "qc_adapt_illumina_novaseq_2_33", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bam2fastx_bam2fastq_1", "category": "resource_profiling", "state": {"process": "BAM2FASTX_BAM2FASTQ", "tool": "bam2fastx/bam2fastq", "description": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAM2FASTX_BAM2FASTQ (Conversion of PacBio BAM files into gzipped fastq files, including splitting of ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_5_3", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: 16S rRNA / ITS microbiome amplicon profiling.", "criteria": {"sample,otu_table": null, "sample,fasta": null, "sample,primer_fwd,primer_rev": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_slamdunk_all_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification (tools: slamdunk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"slamdunk/all": "Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification", "slamdunk/map": "Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings.", "arriba/arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt"}}, "target": "slamdunk/all", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Longitudinal cancer monitoring across multiple timepoints", "data_format": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns are standard for Longitudinal cancer monitoring across multiple timepoints input samplesheet?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "local_subworkflow_prepilluminareads_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should this step (trimmomatic) be packaged: Single-step adapter trimming for Illumina reads?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow PREPILLUMINAREADS": null, "Leave them out": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral amplicon sequencing with primers. Input files: Paired-end tiled viral amplicon FASTQs per clinical swab sample.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral amplicon sequencing with primers with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_geofetch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA (tools: geofetch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "nucmer": "NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences.", "limma_differential": "runs a differential expression analysis with Limma", "artic_minion": "Run the alignment/variant-call/consensus logic of the artic pipeline", "propr_propd": "Perform differential proportionality analysis"}}, "target": "geofetch", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should VARIANTSOFINT (custom/variantsofint) be built?", "criteria": {"Use nf-core subworkflow variantsofint": null, "Keep the modules in the main workflow": null, "Local subworkflow VARIANTSOFINT": null, "Leave them out": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 2}
{"id": "mod_biscuit_epiread_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format. (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups", "biscuit/epiread": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compl", "biscuit/mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "manta/germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "biscuit/epiread", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_4_3", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Nanopore sequencing run with sample to barcode assignment and flowcell type?", "criteria": {"sample,bam": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "pipe_all101_spatialaxe_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data. Topics: 10x-genomics, atera, image-processing, spatial, spatial-data-analysis, spatial-transcriptomics. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, "}}, "target": "spatialaxe", "target_idx": 4}
{"id": "mod_umitools_dedup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read. (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "jvarkit/vcf2table": "Convert VCF to a user friendly table", "umitools/dedup": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "umitools/prepareforrsem": "Make the output from umi_tools dedup or group compatible with RSEM", "umitools/group": "Group reads based on their UMI and mapping coordinates"}}, "target": "umitools/dedup", "target_idx": 2}
{"id": "mod_s4pred_runmodel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prediction of a protein's secondary structure from its amino acid sequence (tools: s4pred)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "bcftools_csq": "bcftools Haplotype-aware consequence caller", "s4pred_runmodel": "Prediction of a protein's secondary structure from its amino acid sequence", "kmcp_index": "Construct KMCP database from k-mer files", "caalm_caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES"}}, "target": "s4pred_runmodel", "target_idx": 2}
{"id": "mod_strdrop_call_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect drops in STR coverage (tools: strdrop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo/merge": "Merge STR profiles into a multi-sample STR profile", "strdrop/call": "Detect drops in STR coverage", "somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "isoseq3/tag": "Extract UMI and cell barcodes", "expansionhunterdenovo/profile": "Compute genome-wide STR profile"}}, "target": "strdrop/call", "target_idx": 1}
{"id": "schema_std_atacseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "description": "ATAC-seq peak-calling and QC analysis pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/atacseq?", "criteria": {"sample,fastq_1,fastq_2,replicate,control": null, "sample,nuclear_image,spot_table,membrane_image": null, "id,fasta,sequence": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "sample,fastq_1,fastq_2,replicate,control", "target_idx": 0}
{"id": "mod_gatk4spark_baserecalibrator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate recalibration table for Base Quality Score Recalibration (BQSR) (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4spark_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "mitorsaw_haplotype": "Mitorsaw analyses mitochondrial variants and identifies heteroplasmy and homoplasmy", "hhsuite_hhsearch": "Sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "gatk4spark_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)"}}, "target": "gatk4spark_baserecalibrator", "target_idx": 3}
{"id": "resource_ampcombi2_cluster_4", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_CLUSTER", "tool": "ampcombi2/cluster", "description": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete using MMseqs2 cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_CLUSTER (A submodule that clusters the merged AMP hits generated from ampcombi2/parsetabl) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_1_6", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_gatk4_indexfeaturefile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates an index for a feature file, e.g. VCF or BED file. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/indexfeaturefile": "Creates an index for a feature file, e.g. VCF or BED file.", "dshbio/filtergff3": "Filter features in gzipped GFF3 format", "deepmased/predict": "DeepMAsED predict subcommand: runs the pre-trained deep learning model on feature tables produced by DeepMAsED", "plasmidfinder": "Identify plasmids in bacterial sequences and assemblies", "dshbio/filterbed": "Filter features in gzipped BED format"}}, "target": "gatk4/indexfeaturefile", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_2_14", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_clair3_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clair3 is a germline small variant caller for long-reads (tools: clair3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_dbsnp": "NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database", "dragen_germline": "The DRAGEN DNA Germline Pipeline accelerates the secondary analysis of NGS data by harnessing the tremendous p", "sentieon_dnamodelapply": "modifies the input VCF file by adding the MLrejected FILTER to the variants", "clair3": "Clair3 is a germline small variant caller for long-reads", "mmseqs_createtsv": "Create a tsv file from a query and a target database as well as the result database"}}, "target": "clair3", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_43", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "field_constraint_phenotype_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_3_1", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "template": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ChIP-seq with IP and input control design with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "field_constraint_strandedness_0_0", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_24", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_cancer_longitudinal_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Longitudinal cancer monitoring across multiple timepoints)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/oncoanalyser, determine the input samplesheet column structure for: Longitudinal cancer monitoring across multiple timepoints.", "criteria": {"patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_iphop_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict phage host using iPHoP (tools: iphop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "mirdeep2_mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs.", "ribocode_metaplots": "Set up RiboCode ORF calling with metaplots", "iphop_predict": "Predict phage host using iPHoP", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}}, "target": "iphop_predict", "target_idx": 3}
{"id": "mod_mafft_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare channels for running MAFFT/align (tools: mafft_align)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clustalo_guidetree": null, "tiara_tiara": null, "controlfreec_freec": null, "foldmason_createdb": null, "mafft_align": null}}, "target": "mafft_align", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wes_pe_5_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Paired-end Whole Exome Sequencing (WES) target capture.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_holodeck_methylate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a methylation-annotated VCF from a reference genome with holodeck (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "artic_aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "mapdamage2": "Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads ge", "holodeck_methylate": "Generate a methylation-annotated VCF from a reference genome with holodeck", "holodeck_eval": "Evaluate alignment accuracy of holodeck-simulated reads"}}, "target": "holodeck_methylate", "target_idx": 3}
{"id": "resource_ascat_4", "category": "resource_profiling", "state": {"process": "ASCAT", "tool": "ascat", "description": "copy number profiles of tumour cells."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASCAT (copy number profiles of tumour cells.) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry))", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry).", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 3}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking with entry step FASTQC.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_4_0", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed single-end long reads from tiled viral amplicons?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_picard_collectinsertsizemetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics about the insert size distribution of a paired-end library. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_collectinsertsizemetrics": null, "samtools_mpileup": null, "gatk4_collectsvevidence": null, "odgi_layout": null, "fgumi_simplexmetrics": null}}, "target": "picard_collectinsertsizemetrics", "target_idx": 0}
{"id": "schema_std_createpanelrefs_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createpanelrefs", "description": "Generate Panel of Normals, models or other similar references from lots of samples", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/createpanelrefs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample,bam,bai,cram,crai", "target_idx": 2}
{"id": "noul_mix_operator_async_emission_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bcftools_stats_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_STATS", "tool": "bcftools/stats", "description": "Generates stats from VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_STATS (Generates stats from VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_channel_operator_map_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_38", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: 16S rRNA / ITS microbiome amplicon profiling)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,primer_fwd,primer_rev": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_happy_happy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row, hap.py will generate and match alternate sequences in a superlocus. A superlocus is a small region of the genome (sized between 1 and around 1000 bp) that contains one or more variants. (tools: happy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/het": null, "happy/happy": null, "llamacpppython/run": null, "happy/sompy": null, "truvari/segment": null}}, "target": "happy/happy", "target_idx": 1}
{"id": "mod_gatk4_samtofastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts BAM/SAM file to FastQ format (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmcopy/readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows", "gatk4/samtofastq": "Converts BAM/SAM file to FastQ format", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "nanomonsv/parse": "Parse all the supporting reads of putative somatic SVs using nanomonsv.\nAfter successful completion, you will "}}, "target": "gatk4/samtofastq", "target_idx": 1}
{"id": "mod_bcftools_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split a vcf file into files per chromosome (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_split": "Split a vcf file into files per chromosome", "atlas_call": "generate VCF file from a BAM file using various calling methods", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "parabricks_rnafq2bam": "This tool is the equivalent of fq2bam for RNA-Seq samples, receiving inputs in FASTQ format, performing alignm", "finaletoolkit_adjustwps": "Adjusts raw Windowed Protection Score (WPS) by applying a median filter\nand Savitsky-Golay filter."}}, "target": "bcftools_split", "target_idx": 0}
{"id": "pipe_all101_clipseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for clip. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti"}}, "target": "clipseq", "target_idx": 4}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_4_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Circulating tumor DNA FASTQs across patient clinical draw intervals?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_index_filter_deacon_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_INDEX_FILTER_DEACON", "modules": ["deacon/index", "deacon/filter"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon"}, "question": {"type": "choice", "instructions": "How should FASTQ_INDEX_FILTER_DEACON (deacon/index, deacon/filter) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_index_filter_deacon": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_INDEX_FILTER_DEACON": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_index_filter_deacon", "target_idx": 0}
{"id": "mod_gatk4_markduplicates_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originating from a single fragment of DNA. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "merquryfk_ploidyplot": "An improved version of Smudgeplot using FastK", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "eido_validate": "Validate samplesheet or PEP config against a schema", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "gatk4_markduplicates", "target_idx": 0}
{"id": "mod_catpack_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads the required files for either Nr or GTDB for building into a CAT database (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack_bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "gtdbtk_classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "pydamage_filter": "Damage parameter estimation for ancient DNA", "deeptools_bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "catpack_download": "Downloads the required files for either Nr or GTDB for building into a CAT database"}}, "target": "catpack_download", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_0_1", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "noul_channel_operator_map_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_ferrohgvs_normalize_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalize HGVS variant descriptions to canonical form with ferro (tools: ferrohgvs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju/kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "ferrohgvs/normalize": "Normalize HGVS variant descriptions to canonical form with ferro", "clair3": "Clair3 is a germline small variant caller for long-reads", "jvarkit/vcffilterjdk": "Filtering VCF with dynamically-compiled java expressions", "staramr/search": "Scans genome contigs against the ResFinder, PlasmidFinder, and PointFinder databases."}}, "target": "ferrohgvs/normalize", "target_idx": 1}
{"id": "resource_baysor_run_4", "category": "resource_profiling", "state": {"process": "BAYSOR_RUN", "tool": "baysor/run", "description": "Bayesian segmentation of spatial transcriptomics data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_RUN (Bayesian segmentation of spatial transcriptomics data.) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_staphopiasccmec_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts Staphylococcus aureus SCCmec type based on primers. (tools: staphopiasccmec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"staphopiasccmec": "Predicts Staphylococcus aureus SCCmec type based on primers.", "hamronization_abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "oarfish_alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "fasta_bgzip_index_dict_samtools": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA f", "hamronization_fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification"}}, "target": "staphopiasccmec", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_1_16", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/raredisease) for Downstream functional annotation of pre-called VCF files. Input files: BGZF-compressed VCF files with companion Tabix index files.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,vcf,tbi": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wes_pe_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Paired-end Whole Exome Sequencing (WES) target capture", "data_format": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_picard_filtersamreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters SAM/BAM files to include/exclude either aligned/unaligned reads or based on a read list (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngsbits/samplegender": null, "picard/filtersamreads": null, "islandpath": null, "abra2": null, "ascat": null}}, "target": "picard/filtersamreads", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_5_4", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral genome sequencing on Oxford Nanopore MinION / GridION.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_1_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "mod_picard_scatterintervalsbyns_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into intervals of alternating regions of N and ACGT bases (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtk/vcf2bed": null, "gatk4/samtofastq": null, "picard/scatterintervalsbyns": null, "bed_scatter_bedtools": null, "saltshaker/plot": null}}, "target": "picard/scatterintervalsbyns", "target_idx": 2}
{"id": "resource_bwa_sampe_2", "category": "resource_profiling", "state": {"process": "BWA_SAMPE", "tool": "bwa/sampe", "description": "Convert paired-end bwa SA coordinate files to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMPE (Convert paired-end bwa SA coordinate files to SAM format) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_high", "target_idx": 0}
{"id": "noul_confusing_combine_with_mix_semantics_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_6_0", "category": "samplesheet_schema", "state": {"technology": "3D Chromatin Structure", "workflow_entry": "FASTQC", "library_inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns are standard for Hi-C chromosome conformation capture mapping input samplesheet?", "criteria": {"sample,matrix,contacts": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_custom_collectstats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and optionally taxonomy/function summaries) from a set of\nheterogeneous log/table files into a single overall-stats table per run. (tools: collectstats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_collectstats": null, "gstama_polyacleanup": null, "ngsbits_samplegender": null, "bcftools_plotvcfstats": null, "ltrretriever_lai": null}}, "target": "custom_collectstats", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_8_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "data_format": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "schema_std_chipseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/chipseq. Description: ChIP-seq peak-calling, QC and differential analysis pipeline..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/chipseq.", "criteria": {"sample,fastq_1,fastq_2,replicate,antibody": null, "sample,fastq_1,fastq_2,library_id,lane": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,nuclear_image,spot_table,membrane_image": null}}, "target": "sample,fastq_1,fastq_2,replicate,antibody", "target_idx": 0}
{"id": "intent_debug_error_6", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "debug_error", "target_idx": 2}
{"id": "mod_deacon_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter DNA sequences using index of reference genome (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leehom": "Bayesian reconstruction of ancient DNA fragments", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "deacon/filter": "Filter DNA sequences using index of reference genome", "bbmap/filterbyname": "Filter out sequences by sequence header name(s)", "gatk4/cnnscorevariants": "Apply a Convolutional Neural Net to filter annotated variants"}}, "target": "deacon/filter", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_19", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_0_2", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,bam": null, "sample,fastq_1": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "schema_std_phaseimpute_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/phaseimpute. Description: A bioinformatics pipeline to phase and impute genetic data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/phaseimpute.", "criteria": {"id,path": null, "sample_id,idat_red,idat_green,group": null, "sample,tools,file,index": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,tools,file,index", "target_idx": 2}
{"id": "mod_star_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using STAR (tools: star)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coverm_contig": "Map reads to contigs and estimate coverage", "csvtk_join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "star_align": "Align reads to a reference genome using STAR", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap"}}, "target": "star_align", "target_idx": 3}
{"id": "resource_arriba_arriba_5", "category": "resource_profiling", "state": {"process": "ARRIBA_ARRIBA", "tool": "arriba/arriba", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_ARRIBA (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_diamond_makedb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a DIAMOND database (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": null, "shasta": null, "diamond_makedb": null, "kalign_align": null, "abritamr_run": null}}, "target": "diamond_makedb", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_21", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_scrna_multiome_5_4", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: 10x Multiome single-cell joint RNA and ATAC chromatin.", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "field_constraint_sex_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"type: boolean": null, "format: file-path": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Metagenomic MAG assembly with comparative groups. Input files: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "subworkflow_pkg_bam_taps_conversion_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TAPS_CONVERSION", "modules": ["rastair/mbias", "rastair/call", "rastair/methylkit", "rastair/mbiasparser"], "description": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis"}, "question": {"type": "choice", "instructions": "How should BAM_TAPS_CONVERSION (rastair/mbias, rastair/call, rastair/methylkit, rastair/mbiasparser) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_TAPS_CONVERSION": null, "Use nf-core subworkflow bam_taps_conversion": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_taps_conversion", "target_idx": 2}
{"id": "mod_ganon_buildcustom_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build ganon database using custom reference sequences. (tools: ganon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_filter": "Filters consensus reads generated by simplex or duplex consensus calling.\nThis is a high-performance replaceme", "cramino": "Quality assessment of long-read bam files using cramino.", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "ganon_buildcustom": "Build ganon database using custom reference sequences.", "ganon_report": "Generate a ganon report file from the output of ganon classify"}}, "target": "ganon_buildcustom", "target_idx": 3}
{"id": "mod_diamond_blastx_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a DIAMOND database using blastx mode (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/blastx": "Queries a DIAMOND database using blastx mode", "pigz/uncompress": "write your description here", "gatk4/collectreadcounts": "Collects read counts at specified intervals. The count for each interval is calculated by counting the number ", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences"}}, "target": "diamond/blastx", "target_idx": 0}
{"id": "field_constraint_bam_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Long-read Oxford Nanopore environmental metagenomic sequencing", "data_format": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: High molecular weight environmental metagenomic long reads per sampling site?", "criteria": {"sample,bam": null, "sample,fastq_1,group": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: Fungal ITS1/ITS2 marker gene amplicon surveillance)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_evigene_tr2aacds_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly (tools: evigene)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"evigene/tr2aacds": "Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "mcroni": "Analysis of mcr-1 gene (mobilized colistin resistance) for sequence variation", "alignoth": "Creating alignment plots from bam files", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "evigene/tr2aacds", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_dia_proteomics_analysis_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Complete DIA-NN proteomics analysis pipeline including in-silico library generation,\npreliminary analysis, empirical library assembly, individual analysis, and final quantification.\nThis subworkflow combines DIA-NN modules with quantms-utils for comprehensive\ndata-independent acquisition (DIA) proteomics data processing. (tools: dia_proteomics_analysis)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_fileconverter": null, "diamond_cluster": null, "quantmsutils_diann2mztab": null, "cellranger_multi": null, "dia_proteomics_analysis": null}}, "target": "dia_proteomics_analysis", "target_idx": 4}
{"id": "noul_process_conditional_execution_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_10", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_trinity_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembles a de novo transcriptome from RNAseq reads (tools: trinity)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trinity": null, "abacas": null, "abra2": null, "fastq_find_mirna_mirdeep2": null, "plink_recode": null}}, "target": "trinity", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_4_3", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted CRAM alignments with companion CRAI indexes?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cram,crai": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay_type": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "data_format": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_0_0", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering", "pipeline": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,fastq_1,fastq_2,environment": null, "sample,fastq_1,fastq_2": null, "sample,rrna_fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq)", "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_biscuit_bsconv_5", "category": "resource_profiling", "state": {"process": "BISCUIT_BSCONV", "tool": "biscuit/bsconv", "description": "Summarize and/or filter reads based on bisulfite conversion rate"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BSCONV (Summarize and/or filter reads based on bisulfite conversion rate) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_1_2", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Tumor-only somatic variant calling without matched normal?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_gmmdemux_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MULTI-seq). (tools: gmmdemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gmmdemux": null, "deeptools_multibamsummary": null, "fastq_align_dedup_bwameth": null, "bff": null, "popscle_demuxlet": null}}, "target": "gmmdemux", "target_idx": 0}
{"id": "resource_bedtools_split_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SPLIT", "tool": "bedtools/split", "description": "Split BED files into several smaller BED files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SPLIT (Split BED files into several smaller BED files) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_hamronization_amrfinderplus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification. (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization_amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "snakemake": "The Snakemake workflow management system is a tool to create reproducible and scalable data analyses. This mod", "hamronization_summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "hamronization_fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "haplogrep2_classify": "classification into haplogroups"}}, "target": "hamronization_amrfinderplus", "target_idx": 0}
{"id": "mod_seqkit_rmdup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...) (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuger/build": "Build centrifuger database for taxonomic profiling", "poolsnp": "PoolSNP is a heuristic SNP caller, which uses an MPILEUP file and a reference genome in FASTA format as inputs", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "seqkit/rmdup": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "seqkit/rmdup", "target_idx": 3}
{"id": "mod_optitype_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform HLA-I typing of sequencing data (tools: optitype)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"damageprofiler": "A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage", "seqfu_stats": "Statistics for FASTA or FASTQ files", "autocycler_resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "optitype": "Perform HLA-I typing of sequencing data", "telogator2": "Allele-specific telomere length estimation and TVR characterization from long reads"}}, "target": "optitype", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_4_2", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Xenium output bundle with transcripts CSV, cell polygons, and morphology images?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,image": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_bam_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic tumor-normal calling from pre-aligned BAM files", "data_format": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic tumor-normal calling from pre-aligned BAM files with entry step MUTECT2.", "criteria": {"patient,sample,bam": null, "sample,bam,bai": null, "sample,vcf": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "field_constraint_fastq_1_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "resource_aardvark_merge_0", "category": "resource_profiling", "state": {"process": "AARDVARK_MERGE", "tool": "aardvark/merge", "description": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_MERGE (A tool to evaluate and merge multiple variant calls into a consensus VCF.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_7_1", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "mod_hisat3n_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align nucleotide conversion sequencing reads (e.g., bisulfite-seq, SLAM-seq) to a reference genome with HISAT-3N (tools: hisat-3n)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamaps/classify": "Strain-level metagenomic assignment", "hisat3n/align": "Align nucleotide conversion sequencing reads (e.g., bisulfite-seq, SLAM-seq) to a reference genome with HISAT-", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin"}}, "target": "hisat3n/align", "target_idx": 1}
{"id": "local_subworkflow_checkirma_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should this step (custom/checkirma) be packaged: Custom validation of assembly output?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow checkirma": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "pipe_all101_lsmquant_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline for processing and analysis of light-sheet microscopy images.. Topics: 3dunet, image-analysis, image-processing, light-sheet-microcopy, segmentation, stitching. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pangenome": null, "sopa": null, "viralrecon": null, "nascent": null, "longraredisease": null, "isoseq": null, "clipseq": null, "lsmquant": null, "drugresponseeval": null, "denovotranscript": null}}, "target": "lsmquant", "target_idx": 7}
{"id": "resource_baysor_segfree_1", "category": "resource_profiling", "state": {"process": "BAYSOR_SEGFREE", "tool": "baysor/segfree", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_SEGFREE (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_fastquorum_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/fastquorum", "assay": "fastquorum pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/fastquorum (Pipeline to produce consensus reads using unique molecular i)?", "criteria": {"sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1,fastq_2,library_id,lane": null, "sample,fastq_1,fastq_2,bam,seq_type": null}}, "target": "sample,fastq_1,fastq_2,library_id,lane", "target_idx": 2}
{"id": "schema_std_genephylomodeler_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/genephylomodeler. Description: A bioinformatics pipeline that fits evolutionary models and detects natural selection from multiple sequence alignments.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/genephylomodeler.", "criteria": {"id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "gene_name,alignment,tree,suite,tool": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "gene_name,alignment,tree,suite,tool", "target_idx": 2}
{"id": "mod_checkv_endtoend_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assess the quality of metagenome-assembled viral genomes. (tools: checkv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm2_databasedownload": "CheckM2 database download", "samtools_view": "filter/convert SAM/BAM/CRAM file", "checkm_lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "checkv_endtoend": "Assess the quality of metagenome-assembled viral genomes.", "snpeff_snpeff": "Genetic variant annotation and functional effect prediction toolbox"}}, "target": "checkv_endtoend", "target_idx": 3}
{"id": "mod_genmod_compound_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score compounds (tools: genmod)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmod_compound": null, "genmod_score": null, "treerecs": null, "genmod_annotate": null, "gapseq_find": null}}, "target": "genmod_compound", "target_idx": 0}
{"id": "mod_bismark_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of BS-Seq reads using bismark (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_coverage2cytosine": null, "bismark_align": null, "chopper": null, "faa_seqfu_seqkit": null, "bismark_deduplicate": null}}, "target": "bismark_align", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_4_0", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs", "pipeline": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs?", "criteria": {"sample,cpg,methylation": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_gcta_keep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply a keep file to a dense GRM using `gcta --keep` (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_keep": "Apply a keep file to a dense GRM using `gcta --keep`", "gatk4_shiftfasta": "Create a fasta with the bases shifted by offset", "gcta_addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "gcta_bivariatereml": "Run bivariate REML analysis with a single dense GRM", "bamutil_trimbam": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping"}}, "target": "gcta_keep", "target_idx": 0}
{"id": "mod_emboss_cons_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence weights and a scoring matrix are used to calculate a score for each amino acid residue or nucleotide at each position in the alignment. (tools: emboss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"emboss/cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "alignoth": "Creating alignment plots from bam files", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "gatk4/denoisereadcounts": "Denoises read counts to produce denoised copy ratios"}}, "target": "emboss/cons", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_0", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_picard_sortsam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts BAM/SAM files based on a variety of picard specific criteria (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_sortsam": "Sorts BAM/SAM files based on a variety of picard specific criteria", "bedtools_sort": "Sorts a feature file by chromosome and other criteria.", "mlst": "Run Torsten Seemann's classic MLST on a genome assembly", "csvtk_sort": "Sort  CSV (or TSV) tables", "bedtools_merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the"}}, "target": "picard_sortsam", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/cutandrun --input samplesheet.csv (Assay: CUT&RUN / CUT&TAG chromatin profiling with IgG control)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "mod_anota2seq_anota2seqrun_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq (tools: anota2seq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gedi/indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "muscle": "MUSCLE is a program for creating multiple alignments of amino acid or nucleotide sequences. A range of options", "plastid/psite": "Estimate position of ribosomal P-site within ribosome profiling read alignments as a function of read length", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "yte": "A YAML template engine with Python expressions"}}, "target": "anota2seq/anota2seqrun", "target_idx": 3}
{"id": "core_tool_multiqc_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Aggregate and summarize quality control metrics and analysis logs across FastQC, Cutadapt, and STAR into a single interactive HTML report.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"fastqc": null, "trimmomatic": null, "multiqc": null, "picard": null, "fastp": null}}, "target": "multiqc", "target_idx": 2}
{"id": "resource_baysor_segfree_4", "category": "resource_profiling", "state": {"process": "BAYSOR_SEGFREE", "tool": "baysor/segfree", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_SEGFREE (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_26", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "local_subworkflow_positionsofint_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should POSITIONSOFINT (custom/positionsofint) be built?", "criteria": {"Leave them out": null, "Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 1}
{"id": "mod_longstitch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: \"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - Tigmint cuts the draft assembly at potentially misassembled regions\n  - ntLink is then used to scaffold the corrected assembly\n  - followed by ARKS for further scaffolding (optional)\" (tools: longstitch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strdust": "Tandem repeat genotyper for long reads", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "longstitch": "\"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - ", "savana/run": "Identify and cluster SV breakpoints from long-read alignments.", "happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py"}}, "target": "longstitch", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Tumor-only somatic variant calling without matched normal", "data_format": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bcftools_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge VCF files (tools: merge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/dedup": "Runs the sentieon tool LocusCollector followed by Dedup. LocusCollector collects read information that is used", "bcftools/merge": "Merge VCF files", "gatk4/printreads": "Print reads in the SAM/BAM/CRAM file", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "bcftools/merge", "target_idx": 1}
{"id": "mod_svdb_query_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Query a structural variant database, using a vcf file as query (tools: svdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"baysor_segfree": "Extract neighborhood composition vectors (NVCs) from a dataset.", "svdb_query": "Query a structural variant database, using a vcf file as query", "narfmap_align": "Performs fastq alignment to a reference using NARFMAP", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "caddsv_get": "Download CADD-SV annotation resources or SegmentNT model files."}}, "target": "svdb_query", "target_idx": 1}
{"id": "resource_biobambam_bamsormadup_5", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMSORMADUP", "tool": "biobambam/bamsormadup", "description": "Parallel sorting and duplicate marking"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMSORMADUP (Parallel sorting and duplicate marking) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_0_4", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "NANOPLOT", "library_inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "subworkflow_pkg_bcl_demultiplex_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BCL_DEMULTIPLEX", "modules": ["bcl2fastq", "bclconvert", "multiqcsav"], "description": "Demultiplex Illumina BCL data using bcl-convert or bcl2fastq"}, "question": {"type": "choice", "instructions": "How should BCL_DEMULTIPLEX (bcl2fastq, bclconvert, multiqcsav) be structured in DSL2?", "criteria": {"Local subworkflow BCL_DEMULTIPLEX": null, "Use nf-core subworkflow bcl_demultiplex": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bcl_demultiplex", "target_idx": 1}
{"id": "resource_admixture_2", "category": "resource_profiling", "state": {"process": "ADMIXTURE", "tool": "admixture", "description": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datasets, where the individuals are unrelated (for example, the individuals in a case-control association study)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADMIXTURE (ADMIXTURE is a program for estimating ancestry in a model-based manner from larg) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_0", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "subworkflow_pkg_dia_proteomics_analysis_0", "category": "subworkflow_packaging", "state": {"subworkflow": "DIA_PROTEOMICS_ANALYSIS", "modules": ["diann", "quantmsutils/dianncfg", "quantmsutils/mzmlstatistics", "quantmsutils/diann2mztab"], "description": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,"}, "question": {"type": "choice", "instructions": "How should DIA_PROTEOMICS_ANALYSIS (diann, quantmsutils/dianncfg, quantmsutils/mzmlstatistics, quantmsutils/diann2mztab) be structured in DSL2?", "criteria": {"Use nf-core subworkflow dia_proteomics_analysis": null, "Leave them out": null, "Local subworkflow DIA_PROTEOMICS_ANALYSIS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow dia_proteomics_analysis", "target_idx": 0}
{"id": "mod_bedops_gtf2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert gtf format to bed format (tools: gtf2bed)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "metabat2_jgisummarizebamcontigdepths": "Depth computation per contig step of metabat2", "bedops_gtf2bed": "Convert gtf format to bed format", "yara_mapper": "Align reads to a reference genome using YARA", "agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file"}}, "target": "bedops_gtf2bed", "target_idx": 2}
{"id": "resource_bedgovcf_1", "category": "resource_profiling", "state": {"process": "BEDGOVCF", "tool": "bedgovcf", "description": "Convert a BED file to a VCF file according to a YAML config"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDGOVCF (Convert a BED file to a VCF file according to a YAML config) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Tumor-only somatic variant calling without matched normal", "data_format": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_2_0", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_echtvar_encode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make (encode) a new echtvar file from decomposed vcf (tools: echtvar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/installannotations": "Install the AnnotSV annotations", "bcftools/annotate": "Add or remove annotations.", "seqtk/rename": "Rename sequence names in FASTQ or FASTA files.", "atlas/call": "generate VCF file from a BAM file using various calling methods", "echtvar/encode": "Make (encode) a new echtvar file from decomposed vcf"}}, "target": "echtvar/encode", "target_idx": 4}
{"id": "samplesheet_arch_ont_demux_barcodes_4_0", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Nanopore sequencing run with sample to barcode assignment and flowcell type?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "local_subworkflow_daisribosome_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should DAISRIBOSOME (dais) be built?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow daisribosome": null, "Leave them out": null, "Local subworkflow DAISRIBOSOME": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 3}
{"id": "mod_cnvnator_cnvnator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads. (tools: cnvnator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy_extractchannel": "Extract a single channel image from multiplexed tissue images using stainwarpy", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "cnvnator_convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "cnvnator_cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "cnvkit_reference": "Compile a coverage reference from the given files (normal samples)."}}, "target": "cnvnator_cnvnator", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_dna_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DNA", "modules": ["bowtie2/align", "bwa/mem", "bwamem2/mem", "dragmap/align", "snapaligner/align", "strobealign"], "description": "Align fastq files to a reference genome"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DNA (bowtie2/align, bwa/mem, bwamem2/mem, dragmap/align, snapaligner/align, strobealign) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_ALIGN_DNA": null, "Use nf-core subworkflow fastq_align_dna": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_dna", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wes_pe_2_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_ragtag_patch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Homology-based assembly patching: Make continuous joins and fill gaps in 'target.fa' using sequences from 'query.fa' (tools: ragtag)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abyss/abysspe": null, "ragtag/patch": null, "cnvkit/antitarget": null, "abricate/summary": null, "htodemux": null}}, "target": "ragtag/patch", "target_idx": 1}
{"id": "field_constraint_bam_2_13", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "resource_amulety_antiberty_5", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTY", "tool": "amulety/antiberty", "description": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTY (A module to create antiberty embeddings of antibody (BCR) amino acid sequences u) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_phyloflash_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illumina (meta)genomic dataset. (tools: phyloflash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "phyloflash": "phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illum", "proteinortho": "Proteinortho is a tool to detect orthologous genes within different species.", "localcdsearch_annotate": "A command-line tool for local protein domain annotation using NCBI's Conserved Domain Database (CDD)", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken."}}, "target": "phyloflash", "target_idx": 1}
{"id": "field_constraint_strandedness_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null, "type: boolean": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_37", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_agat_spkeeplongestisoform_3", "category": "resource_profiling", "state": {"process": "AGAT_SPKEEPLONGESTISOFORM", "tool": "agat/spkeeplongestisoform", "description": "Filters GFF records to keep only the longest isoform per gene"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPKEEPLONGESTISOFORM (Filters GFF records to keep only the longest isoform per gene) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_46", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_crabs_insilicopcr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CRABS extracts the amplicon region of the primer set by conducting an in silico PCR. (tools: crabs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_indexgvcf": "NVIDIA Clara Parabricks GPU-accelerated gvcf indexing tool.", "artic_aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "picard_markduplicates": "Locate and tag duplicate reads in a BAM file", "crabs_insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR.", "quantmsutils_mzmlstatistics": "Generate statistics from mzML files using quantms-utils"}}, "target": "crabs_insilicopcr", "target_idx": 3}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_0_2", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "mod_limma_differential_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: runs a differential expression analysis with Limma (tools: limma)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr/propd": null, "scanpy/pca": null, "limma/differential": null, "dotseq/dotseq": null, "picard/collecthsmetrics": null}}, "target": "limma/differential", "target_idx": 2}
{"id": "resource_bbmap_align_4", "category": "resource_profiling", "state": {"process": "BBMAP_ALIGN", "tool": "bbmap/align", "description": "Align short or PacBio reads to a reference genome using BBMap"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_ALIGN (Align short or PacBio reads to a reference genome using BBMap) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_mykrobe_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: AMR predictions for supported species (tools: mykrobe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"spaceranger_mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "pygenprop_info": "Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assign", "mykrobe_predict": "AMR predictions for supported species"}}, "target": "mykrobe_predict", "target_idx": 4}
{"id": "mod_ldak_thinpredictors_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinned predictor list for weighted kinship workflows (tools: ldak6)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"somalier_ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "ldak_thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "bcftools_convert": "Converts certain output formats to VCF", "sentieon_coveragemetrics": "Accelerated implementation of the GATK DepthOfCoverage tool.", "somalier_relate": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/"}}, "target": "ldak_thinpredictors", "target_idx": 1}
{"id": "mod_isoseq3_tag_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract UMI and cell barcodes (tools: isoseq3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq_cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences", "purecn_normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as", "souporcell": "souporcell is a method for clustering mixed-genotype scRNAseq experiments by individual.", "isoseq_refine": "Remove polyA tail and artificial concatemers", "isoseq3_tag": "Extract UMI and cell barcodes"}}, "target": "isoseq3_tag", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_1_27", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_extract_relate_somalier_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_EXTRACT_RELATE_SOMALIER", "modules": ["htslib/bgziptabix", "somalier/extract", "somalier/relate"], "description": "Perform somalier extraction and relate stats on input VCFs"}, "question": {"type": "choice", "instructions": "How should VCF_EXTRACT_RELATE_SOMALIER (htslib/bgziptabix, somalier/extract, somalier/relate) be structured in DSL2?", "criteria": {"Local subworkflow VCF_EXTRACT_RELATE_SOMALIER": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_extract_relate_somalier": null}}, "target": "Use nf-core subworkflow vcf_extract_relate_somalier", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_0_1", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,rrna_fasta": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_4", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_busco_plot_0", "category": "resource_profiling", "state": {"process": "BUSCO_PLOT", "tool": "busco/plot", "description": "BUSCO summary plot generation using the built-in 'busco --plot' command"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PLOT (BUSCO summary plot generation using the built-in 'busco --plot' command) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_alleleexpression_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/alleleexpression", "description": "Alleleexpression is a nf-core pipeline for allele-specific expression (ASE) analysis using STAR-WASP for alignment, UMI-tools for deduplication, and phaser for haplotype phasing and ASE detection.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/alleleexpression?", "criteria": {"sample,vcf,tbi": null, "id,raw_file": null, "sample,fastq_1,fastq_2,vcf": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,vcf", "target_idx": 2}
{"id": "mod_rundbcan_database_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: command from run_dbcan to prepare the database for dbCAN annotation. (tools: run_dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "rundbcan_cazymeannotation": "CAZyme annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (", "mudskipper_index": "Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM fi", "endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen", "rundbcan_database": "command from run_dbcan to prepare the database for dbCAN annotation."}}, "target": "rundbcan_database", "target_idx": 4}
{"id": "resource_agat_convertgff2bed_1", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTGFF2BED", "tool": "agat/convertgff2bed", "description": "Takes a GFF3 file and converts to a bed12 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTGFF2BED (Takes a GFF3 file and converts to a bed12 file) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_15", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_pairtools_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple pairs/pairsam files (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_merge": "Merge VCF files", "stitch": "STITCH is an R program for reference panel free, read aware, low coverage sequencing genotype imputation. STIT", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "pairtools_merge": "Merge multiple pairs/pairsam files", "rgi_cardannotation": "Preprocess the CARD database for RGI to predict antibiotic resistance from protein or nucleotide data"}}, "target": "pairtools_merge", "target_idx": 3}
{"id": "samplesheet_arch_scrna_10x_v3_1_3", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,bam": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "pipe_all101_funcprofiler_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Read-based functional profiling of microbiome sequencing data. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createtaxdb": null, "funcprofiler": null, "proteinfamilies": null, "hadge": null, "eager": null, "drugresponseeval": null, "mcmicro": null, "longraredisease": null, "crisprseq": null, "nascent": null}}, "target": "funcprofiler", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_21", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_1_5", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "template": "nf-core/eager"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,bam": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_irescue_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quantification of transposable elements expression in scRNA-seq (tools: irescue)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"irescue": null, "kallistobustools/count": null, "juicertools/pre": null, "cellbender/merge": null, "ribotish/predict": null}}, "target": "irescue", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bedtools_closest_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_CLOSEST", "tool": "bedtools/closest", "description": "For each feature in A, finds the closest feature (upstream or downstream) in B."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_CLOSEST (For each feature in A, finds the closest feature (upstream or downstream) in B.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_diamond_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculate clusters of highly similar sequences (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/cluster": null, "comebin/runcomebin": null, "bismark/align": null, "foldmason/msa2lddtreport": null, "diamond/cluster": null}}, "target": "diamond/cluster", "target_idx": 4}
{"id": "samplesheet_arch_methylseq_bisulfite_3_0", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "data_format": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_riboseq_profiling_5_4", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/riboseq, determine the input samplesheet column structure for: Ribosome profiling (Ribo-seq) footprint sequencing.", "criteria": {"sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,cdna_fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_1", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_celesta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Unsupervised machine learning for cell type identification in multiplexed imaging using protein expression and cell neighborhood information without ground truth (tools: celesta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"celesta": "Unsupervised machine learning for cell type identification in multiplexed imaging using protein expression and", "vcf2cytosure": "Convert VCF with structural variations to CytoSure format", "backsub": "Pixel-by-pixel channel subtraction tool for multiplexed immunofluorescence data.", "angsd/soapsnpcalibration": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments.", "imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op"}}, "target": "celesta", "target_idx": 0}
{"id": "mod_seqtk_comp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes sequence statistics from FASTQ or FASTA files (tools: seqtk_comp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqtk/mergepe": "Interleave pair-end reads from FastQ files", "seqtk/comp": "Computes sequence statistics from FASTQ or FASTA files", "seqtk/rename": "Rename sequence names in FASTQ or FASTA files.", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "methurator/gtestimator": "Run estimator for DNA methylation sequencing saturation."}}, "target": "seqtk/comp", "target_idx": 1}
{"id": "pipe_all101_methylseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for bisulfite-sequencing analysis? Specific context: Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair. Topics: bisulfite-sequencing, dna-methylation, em-seq, epigenome, epigenomics, methyl-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": "Read-based functional profiling of microbiome sequencing data", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi"}}, "target": "methylseq", "target_idx": 9}
{"id": "qc_adapt_singlecell_multiqc_0_29", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_deepbgc_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning. (tools: deepbgc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "ferrohgvs/normalize": "Normalize HGVS variant descriptions to canonical form with ferro", "deepbgc/download": "Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning.", "bakta/baktadbdownload": "Downloads BAKTA database from Zenodo"}}, "target": "deepbgc/download", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/taxprofiler --input samplesheet.csv (Assay: Multi-taxonomic profiling of complex metagenomic shotgun reads)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/taxprofiler, determine the input samplesheet column structure for: Multi-taxonomic profiling of complex metagenomic shotgun reads.", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_genephylomodeler_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/genephylomodeler. Description: A bioinformatics pipeline that fits evolutionary models and detects natural selection from multiple sequence alignments.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/genephylomodeler.", "criteria": {"id,path": null, "gene_name,alignment,tree,suite,tool": null, "sample_id,bam,vcf,library_id,lane": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "gene_name,alignment,tree,suite,tool", "target_idx": 1}
{"id": "mod_dupblaster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline in the alignment pipe (aligner | dupblaster | sort) rather than as a standalone step (tools: dupblaster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_addmostseverepli": "Annotate a VEP annotated VCF with the most severe pLi field", "picard_markduplicates": "Locate and tag duplicate reads in a BAM file", "parabricks_fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "quilt_quilt": "QUILT is an R and C++ program for rapid genotype imputation from low-coverage sequence using a large reference", "dupblaster": "Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline "}}, "target": "dupblaster", "target_idx": 4}
{"id": "core_tool_kraken2_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Exact k-mer matching taxonomic classifier mapping metagenomic reads to bacterial and viral reference genomes with lowest common ancestor algorithm.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"diamond": null, "motus": null, "kraken2": null, "centrifuge": null, "metaphlan": null}}, "target": "kraken2", "target_idx": 2}
{"id": "field_constraint_status_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "mod_gatk4_intervallisttools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits the interval list file into unique, equally-sized interval files and place it under a directory (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedgovcf": null, "elprep_fastatoelfasta": null, "preseq_lcextrap": null, "agat_convertbed2gff": null, "gatk4_intervallisttools": null}}, "target": "gatk4_intervallisttools", "target_idx": 4}
{"id": "samplesheet_arch_scrna_multiome_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: 10x Multiome single-cell joint RNA and ATAC chromatin)", "question": {"type": "choice", "instructions": "Which columns are standard for 10x Multiome single-cell joint RNA and ATAC chromatin input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "pipe_all101_rnastructurome_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for dms analysis? Specific context: a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data. Topics: dms, map, rna-structure, rnacentral, rnaframework, rt-stop. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel"}}, "target": "rnastructurome", "target_idx": 2}
{"id": "field_constraint_sex_0_5", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/diaproteomics) for Data-Independent Acquisition (DIA) quantitative mass spectrometry. Input files: Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/diaproteomics, determine the input samplesheet column structure for: Data-Independent Acquisition (DIA) quantitative mass spectrometry.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null, "sample,mzml": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "samplesheet_arch_proteomics_dia_0_2", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,peptides_tsv": null, "sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null, "sample,mzml": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "schema_std_provenancereport_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/provenancereport", "assay": "provenancereport pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/provenancereport (A simple provenance reporting pipeline)?", "criteria": {"sample,fastq_1,fastq_2,bam,cram": null, "id,path": null, "seeds,network,perturbed_networks": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "id,path", "target_idx": 1}
{"id": "pipe_all101_atacseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze ATAC-seq peak-calling and QC analysis pipeline. Topics: atac-seq, chromatin-accessibiity. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": null, "cutandrun": null, "pangenome": null, "atacseq": null, "methylseq": null}}, "target": "atacseq", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_bam_8_2", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"patient,sample,bam": null, "sample,vcf": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "resource_angsd_docounts_1", "category": "resource_profiling", "state": {"process": "ANGSD_DOCOUNTS", "tool": "angsd/docounts", "description": "Calculates base frequency statistics across reference positions from BAM."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOCOUNTS (Calculates base frequency statistics across reference positions from BAM.) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_sarek_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for annotation analysis? Specific context: Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing. Topics: annotation, cancer, gatk4, genomics, germline, pre-processing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we"}}, "target": "sarek", "target_idx": 2}
{"id": "mod_gprofiler2_gost_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: runs a functional enrichment analysis with gprofiler2 (tools: gprofiler2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"phantompeakqualtools": "\"This package computes informative enrichment and quality measures\nfor ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq ", "bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "gprofiler2/gost": "runs a functional enrichment analysis with gprofiler2", "gsea/gsea": "run the Broad Gene Set Enrichment tool in GSEA mode", "homer/findpeaks": "Find peaks with HOMER suite"}}, "target": "gprofiler2/gost", "target_idx": 2}
{"id": "field_constraint_bai_0_0", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "schema_std_multiplesequencealign_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/multiplesequencealign", "assay": "multiplesequencealign pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/multiplesequencealign (A pipeline to run and systematically evaluate Multiple Seque)?", "criteria": {"id,fasta,reference,optional_data,template": null, "id,fasta,sequence": null, "sample,bam,pbi,fail,repeat_id": null, "sample,fastq_1,fastq_2,replicate,control": null}}, "target": "id,fasta,reference,optional_data,template", "target_idx": 0}
{"id": "resource_bcftools_csq_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CSQ", "tool": "bcftools/csq", "description": "bcftools Haplotype-aware consequence caller"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CSQ (bcftools Haplotype-aware consequence caller) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_4_1", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted CRAM alignments with companion CRAI indexes?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cram": null, "sample,vcf": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wes_pe_1_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_opt_flip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse complementing them (tools: opt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylph/query": "Sylph query command for querying genome databases against reads/metagenomes", "metabuli/build": "Builds a database for classification with metabuli from FASTA files and a taxonomy", "opt/flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple", "opt_flip_track_stat": "Off-target probe detection", "xeniumranger/relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts."}}, "target": "opt/flip", "target_idx": 2}
{"id": "mod_bwamem2_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA-mem2 index for reference genome (tools: bwamem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"subread/featurecounts": "Count reads that map to genomic features", "graphmap2/index": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "bwamem2/index": "Create BWA-mem2 index for reference genome", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "biscuit/index": "Indexes a reference genome for use with Biscuit"}}, "target": "bwamem2/index", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_align_bwaaln_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWAALN", "modules": ["bwa/aln", "bwa/sampe", "bwa/samse", "samtools/index"], "description": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWAALN (bwa/aln, bwa/sampe, bwa/samse, samtools/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_ALIGN_BWAALN": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_bwaaln": null}}, "target": "Use nf-core subworkflow fastq_align_bwaaln", "target_idx": 3}
{"id": "subworkflow_pkg_bam_impute_quilt_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_QUILT", "modules": ["gawk", "quilt/quilt", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using QUILT software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_QUILT (gawk, quilt/quilt, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_impute_quilt": null, "Local subworkflow BAM_IMPUTE_QUILT": null}}, "target": "Use nf-core subworkflow bam_impute_quilt", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_45", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_jvarkit_sam2tsv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert sam files to tsv files (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"survivor/stats": "Report multiple stats over a VCF file", "jvarkit/sam2tsv": "Convert sam files to tsv files", "bwa/sampe": "Convert paired-end bwa SA coordinate files to SAM format", "sniffles": "structural-variant calling with sniffles", "bioawk": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats."}}, "target": "jvarkit/sam2tsv", "target_idx": 1}
{"id": "mod_panaroo_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast and scalable tool for bacterial pangenome analysis (tools: panaroo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"panaroo_run": null, "agat_convertspgxf2gxf": null, "agat_spaddintrons": null, "mitorsaw_haplotype": null, "aardvark_compare": null}}, "target": "panaroo_run", "target_idx": 0}
{"id": "mod_fgumi_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract unique molecular indices (UMIs) from FASTQ files and write an unaligned BAM file. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/extract": "Extract unique molecular indices (UMIs) from FASTQ files and write an unaligned BAM file.", "fgbio/filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "fasta_classify_catpack": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack).", "pcangsd/inbreeding": "Estimate per-sample inbreeding coefficients from genotype likelihoods"}}, "target": "fgumi/extract", "target_idx": 0}
{"id": "mod_purecn_coverage_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageInMode should be set to 'link'. (tools: purecn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purecn/normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as", "purecn/run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "ldak/kvikstep1": "Run LDAK-KVIK step 1 to fit the genome-wide model and emit the minimal prediction artifact tuple consumed by l", "sentieon/rsempreparereference": "Prepare a reference genome for RSEM", "purecn/coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI"}}, "target": "purecn/coverage", "target_idx": 4}
{"id": "noul_subworkflow_structural_blocks_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_vsearch_sort_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength). (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch/usearchglobal": "Compare target sequences to fasta-formatted query sequences using global pairwise alignment.", "hamronization/deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "vsearch/sort": "Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).", "vsearch/dereplicate": "Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same l", "mapdamage2": "Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads ge"}}, "target": "vsearch/sort", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for POSITIONSOFINT (custom/positionsofint).", "criteria": {"Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null, "Leave them out": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 0}
{"id": "resource_bcftools_query_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_QUERY", "tool": "bcftools/query", "description": "Extracts fields from VCF or BCF files and outputs them in user-defined format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_QUERY (Extracts fields from VCF or BCF files and outputs them in user-defined format.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_blobtk_snail_5", "category": "resource_profiling", "state": {"process": "BLOBTK_SNAIL", "tool": "blobtk/snail", "description": "Creates blobtk snail plots."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_SNAIL (Creates blobtk snail plots.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_20", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_classify_catpack_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CLASSIFY_CATPACK", "modules": ["catpack/addnames", "catpack/bins", "catpack/contigs", "catpack/download", "catpack/prepare", "catpack/summarise", "untar"], "description": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack)."}, "question": {"type": "choice", "instructions": "How should FASTA_CLASSIFY_CATPACK (catpack/addnames, catpack/bins, catpack/contigs, catpack/download, catpack/prepare, catpack/summarise, untar) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_CLASSIFY_CATPACK": null, "Leave them out": null, "Use nf-core subworkflow fasta_classify_catpack": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_classify_catpack", "target_idx": 2}
{"id": "noul_publishdir_directive_usage_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_amulety_balmpaired_2", "category": "resource_profiling", "state": {"process": "AMULETY_BALMPAIRED", "tool": "amulety/balmpaired", "description": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_BALMPAIRED (A module to create BALM paired embeddings of antibody (BCR) amino acid sequences) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_vg_construct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Constructs a graph from a reference and variant calls or a multiple sequence alignment file (tools: vg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"magus/align": "Multiple Sequence Alignment using Graph Clustering", "shinyngs/staticdifferential": "Make plots for interpretation of differential abundance statistics", "panacus/histgrowth": "Calculates a coverage histogram from a GFA file and constructs a growth table from this as either a TSV or HTM", "vg/construct": "Constructs a graph from a reference and variant calls or a multiple sequence alignment file", "llamacpppython/run": "Python wrapper for running locally-hosted LLM with llama.cpp"}}, "target": "vg/construct", "target_idx": 3}
{"id": "intent_debug_error_11", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "debug_error": null, "build_pipeline": null}}, "target": "debug_error", "target_idx": 2}
{"id": "mod_picard_sortsam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sorts BAM/SAM files based on a variety of picard specific criteria (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "picard/markduplicates": "Locate and tag duplicate reads in a BAM file", "picard/sortsam": "Sorts BAM/SAM files based on a variety of picard specific criteria", "bam_rseqc": "Subworkflow to run multiple commands in the RSeqC package", "clame": "binning of metagenomic sequences"}}, "target": "picard/sortsam", "target_idx": 2}
{"id": "field_constraint_fastq_2_3_2", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_31", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_ctatsplicing_startocancerintrons_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detection and annotation of aberrant splicing isoforms in cancer transcriptomes (tools: ctatsplicing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing_startocancerintrons": null, "vcf2zarr_explode": null, "perbase": null, "hisat2_extractsplicesites": null, "rmats_prep": null}}, "target": "ctatsplicing_startocancerintrons", "target_idx": 0}
{"id": "field_constraint_status_1_0", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_2", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_3_1", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "template": "nf-core/hic"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hi-C chromosome conformation capture mapping with entry step FASTQC.", "criteria": {"sample,matrix,contacts": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bedtools_complement_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COMPLEMENT", "tool": "bedtools/complement", "description": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COMPLEMENT (Returns all intervals in a genome that are not covered by at least one interval ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_busco_generateplot_3", "category": "resource_profiling", "state": {"process": "BUSCO_GENERATEPLOT", "tool": "busco/generateplot", "description": "BUSCO plot generation tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_GENERATEPLOT (BUSCO plot generation tool) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_align_dedup_bwamem_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BWAMEM", "modules": ["parabricks/fq2bam", "samtools/index", "picard/addorreplacereadgroups", "picard/markduplicates", "bam_sort_stats_samtools", "fastq_align_bwa"], "description": "Performs alignment of DNA or TAPS-treated reads using bwamem or parabricks/fq2bam, sort and deduplicate"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BWAMEM (parabricks/fq2bam, samtools/index, picard/addorreplacereadgroups, picard/markduplicates, bam_sort_stats_samtools, fastq_align_bwa) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_DEDUP_BWAMEM": null, "Use nf-core subworkflow fastq_align_dedup_bwamem": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwamem", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_1_4", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "intent_debug_error_10", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "mod_fasta_classify_catpack_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack). (tools: fasta_classify_catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_classify_catpack": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack).", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "goleft/indexcov": "Quickly estimate coverage from a whole-genome bam or cram index. A bam index has 16KB resolution so that's wha", "vembrane/filter": "Filter VCF files with vembrane"}}, "target": "fasta_classify_catpack", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_18", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_cram_indexed_2_5", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,cram": null, "sample,vcf": null, "sample,cram,crai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "mod_mash_sketch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates vastly reduced representations of sequences using MinHash (tools: mash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mash_sketch": null, "mashmap": null, "ichorcna_createpon": null, "ivar_consensus": null, "emboss_revseq": null}}, "target": "mash_sketch", "target_idx": 0}
{"id": "mod_vsearch_fastqfilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs quality filtering and / or conversion of a FASTQ file to FASTA format. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/dnamodelapply": null, "vsearch/cluster": null, "vsearch/fastqfilter": null, "vsearch/sintax": null, "catpack/summarise": null}}, "target": "vsearch/fastqfilter", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_trim_fastp_fastqc_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TRIM_FASTP_FASTQC", "modules": ["fastqc", "fastp"], "description": "Read QC, fastp trimming and read qc"}, "question": {"type": "choice", "instructions": "How should FASTQ_TRIM_FASTP_FASTQC (fastqc, fastp) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_trim_fastp_fastqc": null, "Local subworkflow FASTQ_TRIM_FASTP_FASTQC": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_trim_fastp_fastqc", "target_idx": 0}
{"id": "mod_seqkit_sana_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sanitize broken single line FASTQ files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"grimer": null, "seqkit/sana": null, "ariba/getref": null, "adapterremovalfixprefix": null, "gem2/gemindexer": null}}, "target": "seqkit/sana", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_3_2", "category": "samplesheet_schema", "state": {"technology": "3D Chromatin Structure", "workflow_entry": "FASTQC", "library_inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hi-C chromosome conformation capture mapping with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "local_subworkflow_preparereports_1_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should this step (custom/preparereports, multiqc) be packaged: Custom aggregation and MultiQC reporting?", "criteria": {"Use nf-core subworkflow preparereports": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPAREREPORTS": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 3}
{"id": "mod_aria2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CLI Download utility (tools: aria2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast/updateblastdb": "Downloads a BLAST database from NCBI", "catpack/download": "Downloads the required files for either Nr or GTDB for building into a CAT database", "fastq_align_dedup_bismark": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort", "hificnv": "Copy number variant calling from PacBio HiFi reads", "aria2": "CLI Download utility"}}, "target": "aria2", "target_idx": 4}
{"id": "field_constraint_status_0_1", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"pattern: ^[A-Z]+$": null, "format: file-path": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_46", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_gatk4_variantfiltration_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter variants (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_variantfiltration": "Filter variants", "csvtk_join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "biscuit_bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "seqcluster_collapse": "Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file.", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in"}}, "target": "gatk4_variantfiltration", "target_idx": 0}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/dualrnaseq --input samplesheet.csv (Assay: Dual RNA-seq simultaneous host and pathogen transcriptomics)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Dual RNA-seq simultaneous host and pathogen transcriptomics with entry step FASTQC.", "criteria": {"sample,host_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "mod_mageck_mle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: maximum-likelihood analysis of gene essentialities computation (tools: mageck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mageck_mle": "maximum-likelihood analysis of gene essentialities computation", "ngsbits_bedcoverage": "Annotates a BED file with the average coverage of the regions from one or several BAM/CRAM file(s).", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "meryl_histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs"}}, "target": "mageck_mle", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_4_4", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "FASTQC", "library_inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end tiled viral amplicon FASTQs per clinical swab sample?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_fgbio_callduplexconsensusreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same double-stranded source molecule. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "fgbio/callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "custom/tabulartogseachip": "Make a GSEA class file (.chip) from tabular inputs", "svtk/rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format.", "fgumi/duplex": "Calls duplex consensus sequences from reads generated from the same double-stranded\nsource molecule. This is a"}}, "target": "fgbio/callduplexconsensusreads", "target_idx": 1}
{"id": "mod_gridss_somaticfilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/somaticfilter": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "gridss/call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment", "bwamem2/mem": "Performs fastq alignment to a fasta reference using BWA", "gridss/extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files."}}, "target": "gridss/somaticfilter", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_33", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_core10_eager_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Ancient DNA (aDNA) analysis pipeline for damage pattern estimation and paleogenomic mapping.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "eager", "target_idx": 6}
{"id": "mod_pbmarkdup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes one or multiple sequencing chips of an amplified library as HiFi reads and marks or removes\nduplicates. (tools: pbmarkdup)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit_head": null, "atlas_pmd": null, "ascat": null, "pbmarkdup": null, "vrhyme_linkbins": null}}, "target": "pbmarkdup", "target_idx": 3}
{"id": "samplesheet_arch_germline_lane_split_5_4", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Multi-lane Illumina sequencing run of clinical samples.", "criteria": {"lane,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_decontaminate_deacon_hostile_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DECONTAMINATE_DEACON_HOSTILE", "modules": ["hostile/fetch", "hostile/clean", "deacon/index", "deacon/filter", "fastq_fetch_clean_hostile", "fastq_index_filter_deacon"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon or Hostile"}, "question": {"type": "choice", "instructions": "How should FASTQ_DECONTAMINATE_DEACON_HOSTILE (hostile/fetch, hostile/clean, deacon/index, deacon/filter, fastq_fetch_clean_hostile, fastq_index_filter_deacon) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_DECONTAMINATE_DEACON_HOSTILE": null, "Use nf-core subworkflow fastq_decontaminate_deacon_hostile": null}}, "target": "Use nf-core subworkflow fastq_decontaminate_deacon_hostile", "target_idx": 3}
{"id": "mod_sylphtax_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple taxonomic profiles from sylphtaxt/taxprof into a tsv table (tools: sylphtax)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pridepy_fetchsdrf": null, "sylphtax_merge": null, "sylph_sketchgenomes": null, "agrvate": null, "sylph_sketchsamples": null}}, "target": "sylphtax_merge", "target_idx": 1}
{"id": "samplesheet_arch_spatial_visium_4_4", "category": "samplesheet_schema", "state": {"technology": "Spatial Transcriptomics", "workflow_entry": "FASTQC", "library_inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates?", "criteria": {"sample,fastq_1,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "mod_gget_gget_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic databases. gget consists of a collection of separate but interoperable modules, each designed to facilitate one type of database querying in a single line of code. (tools: gget)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_align": null, "gget_gget": null, "macse_refinealignment": null, "fasta_clean_fcs": null, "bowtie_build": null}}, "target": "gget_gget", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_6_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC", "inputs": "FastQ reads per sample", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_isoseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/isoseq. Description: Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences and produce a bed annotation. .", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/isoseq.", "criteria": {"sample,fastq_1,fastq_2,pool,hash_index": null, "sample,fastq_1": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,seq_data,pbi,start_from": null}}, "target": "sample,seq_data,pbi,start_from", "target_idx": 3}
{"id": "resource_amulety_antiberta2_4", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTA2", "tool": "amulety/antiberta2", "description": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTA2 (A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences ) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bcftools_pluginimputeinfo_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINIMPUTEINFO", "tool": "bcftools/pluginimputeinfo", "description": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINIMPUTEINFO (Adds imputation information metrics to the INFO field based on selected FORMAT t) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_bam_taps_conversion_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis (tools: bam_taps_conversion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_postmask": "Post-alignment masking", "rastair_call": "Assess positive C->T conversion as a readout for methylation on a genome-wide basis", "rastair_methylkit": "Parses rastair call output and converts it into a MethylKit-compatible format.", "bam_taps_conversion": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis", "emmtyper": "EMM typing of Streptococcus pyogenes assemblies"}}, "target": "bam_taps_conversion", "target_idx": 3}
{"id": "mod_proovframe_map_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: frame-shift correction for long read (meta)genomics - maps proteins to reads (tools: proovframe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proovframe_fix": "frame-shift correction for long read (meta)genomics - fix frameshifts in reads", "bamclipper": "This module is used to clip primer sequences from your alignments.", "proovframe_map": "frame-shift correction for long read (meta)genomics - maps proteins to reads", "cnvnator_cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "primerprospector_analyzeprimers": "Score PCR primers for binding to target sequences"}}, "target": "proovframe_map", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_26", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_bismark_coverage2cytosine_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Relates methylation calls back to genomic cytosine contexts. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/methylationextractor": null, "bismark/coverage2cytosine": null, "isoseq/refine": null, "bismark/genomepreparation": null, "eklipse": null}}, "target": "bismark/coverage2cytosine", "target_idx": 1}
{"id": "mod_bcftools_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index VCF tools (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv_annotsv": null, "bcftools_call": null, "agat_spaddintrons": null, "bcftools_index": null, "krakentools_combinekreports": null}}, "target": "bcftools_index", "target_idx": 3}
{"id": "mod_bam_dedup_stats_samtools_umicollapse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: umicollapse, index BAM file and run samtools stats, flagstat and idxstats (tools: bam_dedup_stats_samtools_umicollapse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "fastq_align_bwa": "Align reads to a reference genome using bwa then sort with samtools", "fcs_fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi", "bam_dedup_stats_samtools_umicollapse": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats"}}, "target": "bam_dedup_stats_samtools_umicollapse", "target_idx": 4}
{"id": "mod_mapad_map_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Map short-reads to an indexed reference genome (tools: mapad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"damageprofiler": "A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage", "gunc/mergecheckm": "Merging of CheckM and GUNC results in one summary table", "endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen", "mapad/map": "Map short-reads to an indexed reference genome", "chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files."}}, "target": "mapad/map", "target_idx": 3}
{"id": "pipe_all101_references_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze nf-core/references is a bioinformatics pipeline that build references, for multiple use cases. Topics: genome, references, reproducibility. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]"}}, "target": "references", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_0_2", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_expected_cells_0_6", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_13", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_ensemblvep_filtervep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter variants based on Ensembl Variant Effect Predictor (VEP) annotations. (tools: ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/installannotations": null, "atlasgeneannotationmanipulation/gtf2featureannotation": null, "elprep/merge": null, "kraken2/buildstandard": null, "ensemblvep/filtervep": null}}, "target": "ensemblvep/filtervep", "target_idx": 4}
{"id": "resource_biobambam_bammarkduplicates2_5", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMARKDUPLICATES2", "tool": "biobambam/bammarkduplicates2", "description": "Locate and tag duplicate reads in a BAM file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMARKDUPLICATES2 (Locate and tag duplicate reads in a BAM file) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_smartseq_plate_based_0_4", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"plate,sample,bam": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,well,fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_bam_applybqsr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-gather across genomic intervals: when\nmore than one interval file is supplied per sample, the interval-level\noutputs are merged back together with samtools merge. When no intervals\nare supplied (num_intervals: 0), ApplyBQSR is run once on the whole\ninput and no merge step is performed. (tools: bam_applybqsr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_splitmerge": "split single end read groups by length and merge paired end reads", "sentieon_bwaindex": "Create BWA index for reference genome", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "bam_applybqsr": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using\nGATK4 ApplyBQSR. Supports scatter-ga", "glimpse_sample": "Generates haplotype calls by sampling haplotype estimates"}}, "target": "bam_applybqsr", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_2_31", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_openms_psmfeatureextractor_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes extra features for each input PSM for use with Percolator rescoring. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepmased_features": null, "openms_psmfeatureextractor": null, "shinyngs_validatefomcomponents": null, "adapterremovalfixprefix": null, "nail_search": null}}, "target": "openms_psmfeatureextractor", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_21", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_eager_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "description": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/eager?", "criteria": {"sample,fastq_1,fastq_2,library_id,lane": null, "sample,bundle,image": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample_id,bam,vcf,library_id,lane": null}}, "target": "sample_id,bam,vcf,library_id,lane", "target_idx": 3}
{"id": "mod_custom_bed12codonpositions_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviour emits one row per codon (the\n5' nucleotide); --step / --width / --frame control the stride, span\nand offset on the spliced mRNA. Useful for codon-level work on\nspliced features (e.g. ribo-seq P-site counts per codon, frame /\nperiodicity QC, novel-ORF tiling). (tools: bed12codonpositions)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_bed12codonpositions": null, "foldseek_createdb": null, "custom_orfnormalise": null, "ctatsplicing_startocancerintrons": null, "fastqscan": null}}, "target": "custom_bed12codonpositions", "target_idx": 0}
{"id": "mod_snakemake_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Snakemake workflow management system is a tool to create reproducible and scalable data analyses. This module runs a simple Snakemake pipeline based on input snakefile. Expect many limitations.\" (tools: snakemake)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"semibin_singleeasybin": null, "cpc2": null, "abritamr_run": null, "snakemake": null, "bedtools_coverage": null}}, "target": "snakemake", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_4_1", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Short or long reads with run accession and library instrument platform?", "criteria": {"sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_faire_seq_chromatin_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: FAIRE-seq / DNAse-seq open chromatin profiling)", "question": {"type": "choice", "instructions": "Which columns are standard for FAIRE-seq / DNAse-seq open chromatin profiling input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_finaletoolkit_adjustwps_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adjusts raw Windowed Protection Score (WPS) by applying a median filter\nand Savitsky-Golay filter. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": null, "finaletoolkit_adjustwps": null, "stare": null, "affy_justrma": null, "agat_spfilterfeaturefromkilllist": null}}, "target": "finaletoolkit_adjustwps", "target_idx": 1}
{"id": "core_tool_bwa_mem_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Fast short-read DNA sequence alignment against reference genome creating sorted SAM/BAM alignments for variant calling.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"salmon": "Pseudo-aligner", "bowtie2": "Short read aligner", "bwa_mem": "Burrows-Wheeler Aligner for short-read DNA mapping", "star": "RNA-seq aligner", "minimap2": "Long/short read aligner"}}, "target": "bwa_mem", "target_idx": 2}
{"id": "mod_fastq_align_bowtie2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bowtie2 then sort with samtools (tools: fastq_align_bowtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "pairtools/merge": "Merge multiple pairs/pairsam files", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "sourmash/gather": "Search a metagenome sourmash signature against one or many reference databases and return the minimum set of g", "fastq_align_bowtie2": "Align reads to a reference genome using bowtie2 then sort with samtools"}}, "target": "fastq_align_bowtie2", "target_idx": 4}
{"id": "resource_blobtk_create_4", "category": "resource_profiling", "state": {"process": "BLOBTK_CREATE", "tool": "blobtk/create", "description": "Creates a minimal blobdir."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_CREATE (Creates a minimal blobdir.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_bam_1_8", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_38", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "schema_std_datasync_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/datasync", "description": "nf-core/datasync is a system operation pipeline that provides several workflows for handling system operation / automation tasks", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/datasync?", "criteria": {"sample,input,output_path,checksum_md5,checksum_sha": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "vcf,fasta,genome,site,source": null, "fastq_1,fastq_2,group,replicate,control": null}}, "target": "sample,input,output_path,checksum_md5,checksum_sha", "target_idx": 0}
{"id": "mod_fastqe_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data. (tools: fastqe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"drep/dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome", "fastqe": "fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data.", "longphase/phase": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "busco/plot": "BUSCO summary plot generation using the built-in 'busco --plot' command"}}, "target": "fastqe", "target_idx": 1}
{"id": "mod_bam_taps_conversion_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis (tools: bam_taps_conversion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_annotate_snpeff": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file", "rastair/mbias": "Assess C->T conversion as a readout for methylation on a per-read-position basis.", "bam_taps_conversion": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis", "rastair/mbiasparser": "Parses Rastair mbias output to assess the ideal cutoff for read trimming and reports the values.", "bamtools/stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "bam_taps_conversion", "target_idx": 2}
{"id": "mod_scanpy_scrublet_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect doublets in single-cell RNA-seq data using Scrublet via Scanpy (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "anndata/barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "cache_download_ensemblvep_snpeff": "downlad annotation cache for snpeff and ensemblvep", "scanpy/scrublet": "Detect doublets in single-cell RNA-seq data using Scrublet via Scanpy", "kaiju/mkfmi": "Make Kaiju FMI-index file from a protein FASTA file"}}, "target": "scanpy/scrublet", "target_idx": 3}
{"id": "resource_autocycler_cluster_4", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_CLUSTER", "tool": "autocycler/cluster", "description": "Cluster replicons in compressed assemblies with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_CLUSTER (Cluster replicons in compressed assemblies with Autocycler.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bwa_aln_4", "category": "resource_profiling", "state": {"process": "BWA_ALN", "tool": "bwa/aln", "description": "Find SA coordinates of the input reads for bwa short-read mapping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_ALN (Find SA coordinates of the input reads for bwa short-read mapping) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_high", "target_idx": 0}
{"id": "mod_doubletdetection_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Doublet detection in single-cell RNA-seq data (tools: doubletdetection)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender_removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "ribotish_predict": "Quality control of riboseq bam data", "anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file", "pints_caller": "Main caller script for peak calling", "doubletdetection": "Doublet detection in single-cell RNA-seq data"}}, "target": "doubletdetection", "target_idx": 4}
{"id": "resource_blast_makeblastdb_0", "category": "resource_profiling", "state": {"process": "BLAST_MAKEBLASTDB", "tool": "blast/makeblastdb", "description": "Builds a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_MAKEBLASTDB (Builds a BLAST database) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_subworkflow_structural_blocks_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_deepvariant_rundeepvariant_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "catpack_contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).", "atlas_call": "generate VCF file from a BAM file using various calling methods", "deepvariant_rundeepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat"}}, "target": "deepvariant_rundeepvariant", "target_idx": 4}
{"id": "samplesheet_arch_germline_lane_split_3_1", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multi-lane Illumina sequencing run of clinical samples with entry step FASTQC.", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_nanocomp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare multiple runs of long read sequencing data and alignments (tools: nanocomp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_idmerger": "Merges several idXML files into one idXML file.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ascat": "copy number profiles of tumour cells.", "somalier_ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "nanocomp": "Compare multiple runs of long read sequencing data and alignments"}}, "target": "nanocomp", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_1_1", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_iqtree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a Newick format phylogeny from a multiple sequence alignment using the maximum likelihood algorithm. Capable of bacterial genome size alignments. (tools: iqtree)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasttree": null, "epang_split": null, "iqtree": null, "gcta_grmcutoff": null, "fairy_sketch": null}}, "target": "iqtree", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_1", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_biscuit_vcf2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file. (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/vcf2bed": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file.", "biscuit/mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "upd": "Simple software to call UPD regions from germline exome/wgs trios."}}, "target": "biscuit/vcf2bed", "target_idx": 0}
{"id": "pipe_all101_rnafusion_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze RNA-seq analysis pipeline for detection of gene-fusions. Topics: fusion, fusion-genes, gene-fusion, rna, rna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"dualrnaseq": null, "rnafusion": null, "proteogenomicsdb": null, "pixelator": null, "cutandrun": null, "airrflow": null, "funcprofiler": null, "mhcquant": null}}, "target": "rnafusion", "target_idx": 1}
{"id": "mod_mmseqs_createdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create an MMseqs database from an existing FASTA/Q file (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "last_split": "Find split or spliced alignments in a MAF file", "mmseqs_easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2", "fastdup": "FastDup is a tool designed to locate and tag duplicate reads in a coordinate-sorted SAM or BAM file, using the", "mmseqs_createtaxdb": "Adds taxonomy information to an existing MMseqs2 database"}}, "target": "mmseqs_createdb", "target_idx": 0}
{"id": "resource_artic_minion_4", "category": "resource_profiling", "state": {"process": "ARTIC_MINION", "tool": "artic/minion", "description": "Run the alignment/variant-call/consensus logic of the artic pipeline"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_MINION (Run the alignment/variant-call/consensus logic of the artic pipeline) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_fastq_1_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "mod_taxonkit_list_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate taxonomic subtrees based on taxonids (tools: taxonkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_buildcustom": null, "taxonkit_list": null, "survivor_stats": null, "emmtyper": null, "ganon_report": null}}, "target": "taxonkit_list", "target_idx": 1}
{"id": "mod_gunc_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detection of Chimerism and Contamination in Prokaryotic Genomes (tools: gunc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "gunc_downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "gunc_run": "Detection of Chimerism and Contamination in Prokaryotic Genomes", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq", "datavzrd": "Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables."}}, "target": "gunc_run", "target_idx": 2}
{"id": "mod_mmseqs_makepaddedseqdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create an MMseqs padded database from an existing MMseqs database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_makepaddedseqdb": "Create an MMseqs padded database from an existing MMseqs database", "wisecondorx_predict": "Find copy number aberrations", "mmseqs_cluster": "Cluster sequences using MMSeqs2 cluster.", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever "}}, "target": "mmseqs_makepaddedseqdb", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_21", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_shapeit5_ligate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chunks of phased common variants. (tools: shapeit5)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "memote/report": "Generate HTML quality report snapshot for genome-scale metabolic models", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "shapeit5/ligate": "Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chu", "bam_vcf_impute_glimpse2": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow\ntakes VCF files, phased ref"}}, "target": "shapeit5/ligate", "target_idx": 3}
{"id": "resource_alignoth_3", "category": "resource_profiling", "state": {"process": "ALIGNOTH", "tool": "alignoth", "description": "Creating alignment plots from bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALIGNOTH (Creating alignment plots from bam files) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_icountmini_peaks_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs iCount peaks on a BED file of crosslinks (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_filter_bcftools_ensemblvep": null, "icountmini/metagene": null, "icountmini/peaks": null, "peka": null, "samtools/markdup": null}}, "target": "icountmini/peaks", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_8_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "mod_liftoff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses Liftoff to accurately map annotations in GFF or GTF between assemblies of the same,\nor closely-related species (tools: liftoff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"liftoff": "Uses Liftoff to accurately map annotations in GFF or GTF between assemblies of the same,\nor closely-related sp", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "fastqc": "Run FastQC on sequenced reads", "bedtools_shift": "Shifts each feature by specific number of bases", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file"}}, "target": "liftoff", "target_idx": 0}
{"id": "mod_umicollapse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read. (tools: umicollapse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "angsd_soapsnpcalibration": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments.", "rtgtools_bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas", "humid": "HUMID is a tool to quickly and easily remove duplicate reads from FASTQ files, with or without UMIs.", "umicollapse": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read."}}, "target": "umicollapse", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wgs_pe_0_3", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bacphlip_0", "category": "resource_profiling", "state": {"process": "BACPHLIP", "tool": "bacphlip", "description": "A bacteriophage lifestyle prediction tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BACPHLIP (A bacteriophage lifestyle prediction tool) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_retry_errorstrategy_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bcftools_pluginfilltags_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFILLTAGS", "tool": "bcftools/pluginfilltags", "description": "Compute and fill various INFO tags"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFILLTAGS (Compute and fill various INFO tags) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bedtools_jaccard_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_JACCARD", "tool": "bedtools/jaccard", "description": "Calculate Jaccard statistic b/w two feature files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_JACCARD (Calculate Jaccard statistic b/w two feature files.) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_1_22", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_alignoth_1", "category": "resource_profiling", "state": {"process": "ALIGNOTH", "tool": "alignoth", "description": "Creating alignment plots from bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALIGNOTH (Creating alignment plots from bam files) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_autocycler_resolve_1", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_RESOLVE", "tool": "autocycler/resolve", "description": "Resolve trimmed assembly graphs into final contigs within Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_RESOLVE (Resolve trimmed assembly graphs into final contigs within Autocycler.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_sentieon_readwriter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality Score Recalibration to a file. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT", "biobambam/bammerge": "Merge a list of sorted bam files", "sentieon/readwriter": "Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality S", "apbs": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Bol", "bedtools/map": "Allows one to screen for overlaps between two sets of genomic features."}}, "target": "sentieon/readwriter", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_7", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bbmap_bbnorm_5", "category": "resource_profiling", "state": {"process": "BBMAP_BBNORM", "tool": "bbmap/bbnorm", "description": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result in a flat coverage distribution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBNORM (BBNorm is designed to normalize coverage by down-sampling reads over high-depth ) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "local_subworkflow_daisribosome_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should this step (dais) be packaged: Custom ribosomal frameshift translation analysis?", "criteria": {"Use nf-core subworkflow daisribosome": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow DAISRIBOSOME": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 3}
{"id": "resource_autocycler_subsample_2", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_SUBSAMPLE", "tool": "autocycler/subsample", "description": "Downsample long-read sequencing data to the requested coverage using Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_SUBSAMPLE (Downsample long-read sequencing data to the requested coverage using Autocycler.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_gatk4_determinegermlinecontigploidy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determines the baseline contig ploidy for germline samples given counts data (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions.", "gapseq_findtransport": "Predict transporters from genomic data using gapseq", "gatk4_determinegermlinecontigploidy": "Determines the baseline contig ploidy for germline samples given counts data", "gedi_indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "ascat": "copy number profiles of tumour cells."}}, "target": "gatk4_determinegermlinecontigploidy", "target_idx": 2}
{"id": "noul_channel_factory_inside_process_body_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "subworkflow_pkg_bam_dedup_stats_samtools_umitools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS", "modules": ["umitools/dedup", "samtools/index", "samtools/view", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS (umitools/dedup, samtools/index, samtools/view, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS": null, "Leave them out": null, "Use nf-core subworkflow bam_dedup_stats_samtools_umitools": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umitools", "target_idx": 3}
{"id": "mod_magus_guidetree_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multiple Sequence Alignment using Graph Clustering (tools: magus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clustalo/align": "Align sequences using Clustal Omega", "emboss/cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "parabricks/haplotypecaller": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating GATK haplotypecaller.", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "magus/guidetree": "Multiple Sequence Alignment using Graph Clustering"}}, "target": "magus/guidetree", "target_idx": 4}
{"id": "field_constraint_expected_cells_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "mod_t1k_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: t1k)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hlala_preparegraph": null, "vcf2db": null, "cmseq_polymut": null, "liftoff": null, "t1k_run": null}}, "target": "t1k_run", "target_idx": 4}
{"id": "field_constraint_bai_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.crai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_8_2", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null, "sample,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "noul_channel_collect_operator_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_sample_1_2", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"format: file-path": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_metaphlan_makedb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build MetaPhlAn database for taxonomic profiling. (tools: metaphlan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_taxonomic_profile_metaphlan": null, "cnvkit/coverage": null, "bbmap/index": null, "bam_rseqc": null, "metaphlan/makedb": null}}, "target": "metaphlan/makedb", "target_idx": 4}
{"id": "schema_std_rnastructurome_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnastructurome", "description": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnastructurome?", "criteria": {"sample,sample_id,fastq_1,fastq_2,method": null, "sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "sample,sample_id,fastq_1,fastq_2,method", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_5_3", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/chipseq, determine the input samplesheet column structure for: ChIP-seq with IP and input control design.", "criteria": {"sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic tumor-normal calling from pre-aligned BAM files. Input files: Coordinate-sorted BAMs with index for tumor and normal samples.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,vcf": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_2_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_gatk4_svannotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds predicted functional consequence, gene overlap, and noncoding element overlap annotations to SV VCF from GATK-SV pipeline. Input files are an SV VCF, a GTF file containing primary or canonical transcripts, and a BED file containing noncoding elements. Output file is an annotated SV VCF. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"circexplorer2/annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse", "kaiju/kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "gatk4/svannotate": "Adds predicted functional consequence, gene overlap, and noncoding element overlap annotations to SV VCF from ", "echtvar/anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "s4pred/runmodel": "Prediction of a protein's secondary structure from its amino acid sequence"}}, "target": "gatk4/svannotate", "target_idx": 2}
{"id": "core_tool_picard_markduplicates_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Identify and flag PCR and optical duplicate reads in coordinate-sorted BAM files based on 5-prime mapping coordinates.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"gatk_markduplicates": null, "samtools": null, "picard_markduplicates": null, "fastp": null, "sambamba": null}}, "target": "picard_markduplicates", "target_idx": 2}
{"id": "mod_baysor_segfree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract neighborhood composition vectors (NVCs) from a dataset. (tools: baysor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"baysor_segfree": "Extract neighborhood composition vectors (NVCs) from a dataset.", "mmseqs_createtsv": "Create a tsv file from a query and a target database as well as the result database", "goatools_findenrichment": "Find enriched GO terms in a list of genes", "bam_qc_rnaseq": "Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC ", "scanpy_filter": "Filter cells and genes in single-cell RNA-seq data using Scanpy"}}, "target": "baysor_segfree", "target_idx": 0}
{"id": "mod_bcl2fastq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Illumina BCL files (tools: bcl2fastq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fqtk": "Demultiplex fastq files", "bcl2fastq": "Demultiplex Illumina BCL files", "pairtools/merge": "Merge multiple pairs/pairsam files", "fastq_fastqc_umitools_trimgalore": "Read QC, UMI extraction and trimming", "bclconvert": "Demultiplex Illumina BCL files"}}, "target": "bcl2fastq", "target_idx": 1}
{"id": "field_constraint_sample_1_14", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"type: integer": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "noul_exit_code_137_cause_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_0_3", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "intent_ask_question_13", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "debug_error": null, "prepare_data": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_27", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_spatyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computational method for finding spa types. (tools: spatyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_ngscheckmate": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "metaphlan3_metaphlan3": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "spatyper": "Computational method for finding spa types."}}, "target": "spatyper", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_1_40", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_fastq_align_bwa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using bwa then sort with samtools (tools: fastq_align_bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_bwa": "Align reads to a reference genome using bwa then sort with samtools", "gatk4_mergemutectstats": "Merges mutect2 stats generated on different intervals/regions", "taxpasta_merge": "Standardise and merge two or more taxonomic profiles into a single table", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "fastq_align_bwa", "target_idx": 0}
{"id": "mod_vsearch_sintax_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification using the sintax algorithm. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch/fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format.", "vsearch/sintax": "Taxonomic classification using the sintax algorithm.", "vsearch/usearchglobal": "Compare target sequences to fasta-formatted query sequences using global pairwise alignment.", "verifybamid/verifybamid2": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "fasta_gtf_bam_rpbp": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). R"}}, "target": "vsearch/sintax", "target_idx": 1}
{"id": "mod_bcftools_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters VCF files (tools: filter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gprofiler2_gost": "runs a functional enrichment analysis with gprofiler2", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools_filter": "Filters VCF files", "deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat"}}, "target": "bcftools_filter", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq with strandedness", "data_format": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_minia_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Minia is a short-read assembler based on a de Bruijn graph (tools: minia)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa/samse": null, "circularmapper/realignsamfile": null, "mashtree": null, "gcta/calculateldscores": null, "minia": null}}, "target": "minia", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_tn_6_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "BWA_MEM", "library_inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic cancer variant calling with tumor-normal pairs input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_picard_liftovervcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lifts over a VCF file from one reference build to another. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "atlas_call": "generate VCF file from a BAM file using various calling methods", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "picard_liftovervcf": "Lifts over a VCF file from one reference build to another.", "gatk4_preprocessintervals": "Prepares bins for coverage collection."}}, "target": "picard_liftovervcf", "target_idx": 3}
{"id": "mod_pygenprop_info_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assignments, step assignments, InterProScan matches, and protein sequences. (tools: pygenprop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"instrain/profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "pygenprop/info": "Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assign", "gcta/addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "interproscan": "Produces protein annotations and predictions from an amino acids FASTA file", "mifaser": "Functional annotation of metagenomic reads by assigning enzyme commission (EC) numbers"}}, "target": "pygenprop/info", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/eager) for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment. Input files: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status.", "question": {"type": "choice", "instructions": "Which columns are standard for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bamtools_stats_5", "category": "resource_profiling", "state": {"process": "BAMTOOLS_STATS", "tool": "bamtools/stats", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_STATS (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_eager_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for adna analysis? Specific context: A fully reproducible and state-of-the-art ancient DNA analysis pipeline. Topics: adna, ancient-dna-analysis, ancientdna, genome, metagenomics, pathogen-genomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "metapep": "From metagenomes to epitopes and beyond", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 "}}, "target": "eager", "target_idx": 3}
{"id": "mod_bcftools_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters VCF files (tools: filter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/concat": "Concatenate VCF files", "multiqc": "Aggregate results from bioinformatics analyses across many samples into a single report", "bcftools/filter": "Filters VCF files", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools/isec": "Apply set operations to VCF files"}}, "target": "bcftools/filter", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_bedtools_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split BED files into several smaller BED files (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a", "bedtools/split": "Split BED files into several smaller BED files", "hiphase": "Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across ", "bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "bedtools/bamtobed": "Converts a bam file to a bed12 file."}}, "target": "bedtools/split", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/dualrnaseq", "assay_type": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "data_format": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Dual RNA-seq simultaneous host and pathogen transcriptomics with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,host_fasta": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "pipe_all101_seqsubmit_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for seqsubmit. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "seqsubmit": "nf-core pipeline for data submission to ENA", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "seqsubmit", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_7_0", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "data_format": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "mod_ngsbits_bedcoverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates a BED file with the average coverage of the regions from one or several BAM/CRAM file(s). (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "homer_maketagdirectory": "Create a tag directory with the HOMER suite", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "ngsbits_bedcoverage": "Annotates a BED file with the average coverage of the regions from one or several BAM/CRAM file(s).", "paftools_sam2paf": "A program to convert bam into paf."}}, "target": "ngsbits_bedcoverage", "target_idx": 3}
{"id": "samplesheet_arch_pediatric_trio_somatic_4_1", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_rhocall_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Markup VCF file using rho-calls. (tools: rhocall)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging/macsima2mc": "Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO.", "ngsbits/rohhunter": "RohHunter is a tool for run of homozygosity (ROH) detection based on a variant list in VCF format.", "rhocall/annotate": "Markup VCF file using rho-calls.", "bcftools/rohviz": "Visualise the output of bcftools roh", "faqcs": "Perform adapter and quality trimming on sequencing reads with reporting"}}, "target": "rhocall/annotate", "target_idx": 2}
{"id": "resource_agat_spkeeplongestisoform_5", "category": "resource_profiling", "state": {"process": "AGAT_SPKEEPLONGESTISOFORM", "tool": "agat/spkeeplongestisoform", "description": "Filters GFF records to keep only the longest isoform per gene"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPKEEPLONGESTISOFORM (Filters GFF records to keep only the longest isoform per gene) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_biscuit_biscuitblaster_5", "category": "resource_profiling", "state": {"process": "BISCUIT_BISCUITBLASTER", "tool": "biscuit/biscuitblaster", "description": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BISCUITBLASTER (A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM f) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_sample_1_8", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"format: file-path": null, "enum: [0, 1]": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "core_tool_kallisto_bustools_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Ultra-fast pseudoalignment and barcode/UMI processing for single-cell RNA-seq generating bustools count matrices.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"cellranger": null, "salmon": null, "kallisto_bustools": null, "starsolo": null, "alevin": null}}, "target": "kallisto_bustools", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_39", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_aria2_4", "category": "resource_profiling", "state": {"process": "ARIA2", "tool": "aria2", "description": "CLI Download utility"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIA2 (CLI Download utility) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_biscuit_mergecg_3", "category": "resource_profiling", "state": {"process": "BISCUIT_MERGECG", "tool": "biscuit/mergecg", "description": "Merges methylation information for opposite-strand C's in a CpG context"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_MERGECG (Merges methylation information for opposite-strand C's in a CpG context) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Standard Paired-end Whole Genome Sequencing (WGS))", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_fairy_coverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a MetaBAT2-compatible TSV with per-contig\nmean depth and variance columns. (tools: fairy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "differential_functional_enrichment": "Run functional analysis on differential abundance analysis output", "autocycler_trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "fairy_coverage": "Computes coverage depth statistics for assembled contigs from one or more\nfairy sketch files, producing a Meta", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}}, "target": "fairy_coverage", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_index_filter_deacon_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_INDEX_FILTER_DEACON", "modules": ["deacon/index", "deacon/filter"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon"}, "question": {"type": "choice", "instructions": "How should FASTQ_INDEX_FILTER_DEACON (deacon/index, deacon/filter) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_INDEX_FILTER_DEACON": null, "Leave them out": null, "Use nf-core subworkflow fastq_index_filter_deacon": null}}, "target": "Use nf-core subworkflow fastq_index_filter_deacon", "target_idx": 3}
{"id": "schema_std_lsmquant_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/lsmquant", "description": "A pipeline for processing and analysis of light-sheet microscopy images.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/lsmquant?", "criteria": {"sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,vcf": null, "vcf,fasta,genome,site,source": null, "sample,fastq_1,strandedness": null}}, "target": "sample_id,img_directory,parameter_file", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_sentieon_haplotyper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs Sentieon's haplotyper for germline variant calling. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit_mds": "Comnpute the Motif Diversity Score using normalized Shannon entropy\n(Jiang et al., 2020).", "sentieon_applyvarcal": "Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the sec", "krakentools_kreport2krona": "Takes a Kraken report file and prints out a krona-compatible TEXT file", "sentieon_haplotyper": "Runs Sentieon's haplotyper for germline variant calling.", "sentieon_bwaindex": "Create BWA index for reference genome"}}, "target": "sentieon_haplotyper", "target_idx": 3}
{"id": "schema_std_tfactivity_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tfactivity", "assay": "tfactivity pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/tfactivity (Bioinformatics pipeline that makes use of expression and ope)?", "criteria": {"patient,sample,fastq_1,fastq_2,bam": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,condition,assay,peak_file,footprinting": null, "sample,group,path,ref,method": null}}, "target": "sample,condition,assay,peak_file,footprinting", "target_idx": 2}
{"id": "resource_autocycler_cluster_1", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_CLUSTER", "tool": "autocycler/cluster", "description": "Cluster replicons in compressed assemblies with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_CLUSTER (Cluster replicons in compressed assemblies with Autocycler.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "assay_type": "Ribosome profiling (Ribo-seq) footprint sequencing", "data_format": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ribosome profiling (Ribo-seq) footprint sequencing input samplesheet?", "criteria": {"sample,cdna_fasta": null, "sample,bam": null, "sample,fastq_1,strandedness": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "mod_pyclonevi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele frequencies and copy number data of single or multiple samples. (tools: pyclonevi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq", "bio2zarr_vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster.", "cnvpytor_callcnvs": "Command line tool for calling CNVs in whole genome sequencing data", "fastq_align_hisat2": "Align reads to a reference genome using hisat2 then sort with samtools", "ichorcna_createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti"}}, "target": "pyclonevi", "target_idx": 0}
{"id": "subworkflow_pkg_bam_stats_samtools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STATS_SAMTOOLS", "modules": ["samtools/stats", "samtools/idxstats", "samtools/flagstat"], "description": "Produces comprehensive statistics from SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_STATS_SAMTOOLS (samtools/stats, samtools/idxstats, samtools/flagstat) be structured in DSL2?", "criteria": {"Local subworkflow BAM_STATS_SAMTOOLS": null, "Leave them out": null, "Use nf-core subworkflow bam_stats_samtools": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_stats_samtools", "target_idx": 2}
{"id": "intent_build_pipeline_15", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "ask_question": null, "prepare_data": null}}, "target": "build_pipeline", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_6_4", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Xenium in situ subcellular spatial RNA transcriptomics input samplesheet?", "criteria": {"sample,bam": null, "sample,image": null, "sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_6_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns are standard for Parse Biosciences Split-seq combinatorial barcoding input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,well,plate": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_27", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_multiple_script_sections_invalid_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_35", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_atlasgeneannotationmanipulation_gtf2featureannotation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate tables of feature metadata from GTF files (tools: atlasgeneannotationmanipulation)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/sort": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate,\nqueryname, and template-coor", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "snpdists": "Pairwise SNP distance matrix from a FASTA sequence alignment", "agat/convertspgxf2gxf": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file", "atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files"}}, "target": "atlasgeneannotationmanipulation/gtf2featureannotation", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_15", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_conifer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate confidence scores from Kraken2 output (tools: conifer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep3_classify": null, "mobsuite_recon": null, "conifer": null, "mosdepth": null, "centrifuge_centrifuge": null}}, "target": "conifer", "target_idx": 2}
{"id": "mod_artic_minion_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run the alignment/variant-call/consensus logic of the artic pipeline (tools: artic)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gffcompare": null, "artic/guppyplex": null, "artic/aligntrim": null, "annotsv/installannotations": null, "artic/minion": null}}, "target": "artic/minion", "target_idx": 4}
{"id": "mod_chewbbaca_allelecall_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine the allelic profiles of a genome using a pre-defined schema (tools: chewbbaca)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "chewbbaca_createschema": "Create a schema to determine the allelic profiles of a genome", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "samtools_collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma", "chewbbaca_allelecall": "Determine the allelic profiles of a genome using a pre-defined schema"}}, "target": "chewbbaca_allelecall", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_8_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay_type": "PacBio HiFi unaligned BAM variant calling", "data_format": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_4_0", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates?", "criteria": {"sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_41", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_bigscape_bigscape_1", "category": "resource_profiling", "state": {"process": "BIGSCAPE_BIGSCAPE", "tool": "bigscape/bigscape", "description": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSCAPE_BIGSCAPE (BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clust) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bismark_deduplicate_3", "category": "resource_profiling", "state": {"process": "BISMARK_DEDUPLICATE", "tool": "bismark/deduplicate", "description": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_DEDUPLICATE (Removes alignments to the same position in the genome\nfrom the Bismark mapping o) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_26", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_bismark_summary_3", "category": "resource_profiling", "state": {"process": "BISMARK_SUMMARY", "tool": "bismark/summary", "description": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_SUMMARY (Uses Bismark report files of several samples in a run folder to generate a graph) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_ctatsplicing_prepgenomelib_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reference preparation for CTAT-splicing (tools: ctatsplicing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/bbduk": "Adapter and quality trimming of sequencing reads", "sistr": "Serovar prediction of salmonella assemblies", "leafcutter/clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter", "hisat2/extractsplicesites": "Extracts splicing sites from a gtf files", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing"}}, "target": "ctatsplicing/prepgenomelib", "target_idx": 4}
{"id": "mod_cellrangeratac_mkfastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to create fastqs needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkfastq command. (tools: cellranger-atac)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunc_downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "interproscan": "Produces protein annotations and predictions from an amino acids FASTA file", "bowtie_align": "Align reads to a reference genome using bowtie", "cellrangeratac_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkfastq com", "bowtie_build": "Create bowtie index for reference genome"}}, "target": "cellrangeratac_mkfastq", "target_idx": 3}
{"id": "mod_plink_gwas_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate GWAS association studies (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "suppa_psiperevent": "Calculate PSI values for alternative splicing events using SUPPA", "hifitrimmer_processblast": "Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrima", "regenie_runl0": "Run one REGENIE step 1 level-0 job from a split master file", "plink_gwas": "Generate GWAS association studies"}}, "target": "plink_gwas", "target_idx": 4}
{"id": "samplesheet_arch_smartseq_plate_based_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "data_format": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,well,fastq": null, "sample,matrix": null, "plate,sample,bam": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_ampliseq_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/ampliseq. Description: Amplicon sequencing analysis workflow using DADA2 and QIIME2.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/ampliseq.", "criteria": {"sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,alleles,mhc_class,filename": null, "sample_id,name,description,path,path_2": null, "sample,input,output_path,checksum_md5,checksum_sha": null}}, "target": "sample,fastq_1,fastq_2,sampleID,forwardReads", "target_idx": 0}
{"id": "resource_authentict_deam2cont_5", "category": "resource_profiling", "state": {"process": "AUTHENTICT_DEAM2CONT", "tool": "authentict/deam2cont", "description": "Use deamination patterns to estimate contamination in single-stranded libraries"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTHENTICT_DEAM2CONT (Use deamination patterns to estimate contamination in single-stranded libraries) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_fastq_1_3_5", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "resource_biscuit_epiread_5", "category": "resource_profiling", "state": {"process": "BISCUIT_EPIREAD", "tool": "biscuit/epiread", "description": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_EPIREAD (Summarizes read-level methylation (and optionally SNV) information from a\nBiscui) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_blast_blastdbcmd_3", "category": "resource_profiling", "state": {"process": "BLAST_BLASTDBCMD", "tool": "blast/blastdbcmd", "description": "Retrieve entries from a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTDBCMD (Retrieve entries from a BLAST database) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_macs2_callpeak_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments (tools: macs2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wisecondorx_newref": "Create a new reference using healthy reference samples", "alignoth": "Creating alignment plots from bam files", "macs2_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed"}}, "target": "macs2_callpeak", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_40", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_all101_readsimulator_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for readsimulator. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]"}}, "target": "readsimulator", "target_idx": 5}
{"id": "qc_adapt_pacbio_hifi_1_15", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_blast_blastp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "elprep_filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "blast_blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "tiff_segmentation_vpt": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool"}}, "target": "blast_blastp", "target_idx": 2}
{"id": "intent_build_pipeline_13", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "build_pipeline": null, "prepare_data": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_24", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_hmmer_jackhmmer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: iterative searches to detect distant homologs by refining an HMM profile from hits (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldmason_easymsa": "Aligns protein structures using foldmason", "hhsuite_hhsearch": "Sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "deepcell_mesmer": "Deepcell/mesmer segmentation for whole-cell", "hmmer_jackhmmer": "iterative searches to detect distant homologs by refining an HMM profile from hits", "hhsuite_hhblits": "Fast and sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)"}}, "target": "hmmer_jackhmmer", "target_idx": 3}
{"id": "mod_fibertoolsrs_addnucleosomes_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Add nucleosomes positions and MSP position to ONT BAM files (tools: fibertoolsrs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pear": "PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger.", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "bismark/report": "Collects bismark alignment reports", "fibertoolsrs/addnucleosomes": "Add nucleosomes positions and MSP position to ONT BAM files", "fgbio/sortbam": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate, queryname, random, and rando"}}, "target": "fibertoolsrs/addnucleosomes", "target_idx": 3}
{"id": "mod_plink2_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters plink bfiles or pfiles with filters such as maf or var (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/filter": "Filters plink bfiles or pfiles with filters such as maf or var", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "plink2/remove": "Remove samples from a plink2 dataset", "plink2/extract": "Subset plink pfiles with a text file of variant identifiers", "galah": "Cluster genome FASTA files by average nucleotide identity"}}, "target": "plink2/filter", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_msisensor_msi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate microsattelite instability (MSI) using paired tumor-normal sequencing data (tools: msisensor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro/msisomatic": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "msisensor/msi": "Evaluate microsattelite instability (MSI) using paired tumor-normal sequencing data", "msisensor2/msi": "msisensor2 detection of MSI regions.", "snapaligner/index": "Create a SNAP index for reference genome", "meryl/count": "A genomic k-mer counter (and sequence utility) with nice features."}}, "target": "msisensor/msi", "target_idx": 1}
{"id": "resource_antismash_antismashlitedownloaddatabases_3", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES", "tool": "antismash/antismashlitedownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHLITEDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_proteinfamilies_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for metagenomics analysis? Specific context: Generation and updating of protein families. Topics: metagenomics, protein-families. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]"}}, "target": "proteinfamilies", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_17", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_last_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find split or spliced alignments in a MAF file (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last/dotplot": "Makes a dotplot (Oxford Grid) of pair-wise sequence alignments", "last/split": "Find split or spliced alignments in a MAF file", "rundbcan/database": "command from run_dbcan to prepare the database for dbCAN annotation.", "controlfreec/freec2bed": "Plot Freec output", "last/mafswap": "Reorder alignments in a MAF file"}}, "target": "last/split", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_5", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bcftools_pluginimputeinfo_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINIMPUTEINFO", "tool": "bcftools/pluginimputeinfo", "description": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINIMPUTEINFO (Adds imputation information metrics to the INFO field based on selected FORMAT t) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_4_2", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "mod_rattle_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reference-free reconstruction and quantification of transcriptomes from long-read sequencing (tools: rattle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rattle_cluster": "Reference-free reconstruction and quantification of transcriptomes from long-read sequencing", "snippy_core": "Core-SNP alignment from Snippy outputs", "clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "gatk4_germlinecnvcaller": "Calls copy-number variants in germline samples given their counts and the output of DetermineGermlineContigPlo", "cdhit_cdhit": "Cluster protein sequences using sequence similarity"}}, "target": "rattle_cluster", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pre-aligned BAM variant calling pipeline. Input files: Aligned BAM files.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_index_methylseq_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_METHYLSEQ", "modules": ["untar", "gunzip", "bismark/genomepreparation", "bwameth/index", "bwa/index", "samtools/faidx"], "description": "Generate index files from reference fasta for bismark, bwameth and bwamem aligners"}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_METHYLSEQ (untar, gunzip, bismark/genomepreparation, bwameth/index, bwa/index, samtools/faidx) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_INDEX_METHYLSEQ": null, "Use nf-core subworkflow fasta_index_methylseq": null}}, "target": "Use nf-core subworkflow fasta_index_methylseq", "target_idx": 3}
{"id": "resource_busco_generateplot_2", "category": "resource_profiling", "state": {"process": "BUSCO_GENERATEPLOT", "tool": "busco/generateplot", "description": "BUSCO plot generation tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_GENERATEPLOT (BUSCO plot generation tool) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_biohansel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use k-mers to rapidly subtype S. enterica genomes (tools: biohansel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunc/mergecheckm": null, "gunc/run": null, "saltshaker/classify": null, "biohansel": null, "rundbcan/easysubstrate": null}}, "target": "biohansel", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_biscuit_pileup_3", "category": "resource_profiling", "state": {"process": "BISCUIT_PILEUP", "tool": "biscuit/pileup", "description": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_PILEUP (Computes cytosine methylation and callable SNV mutations, optionally in referenc) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_rastair_mbiasparser_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parses Rastair mbias output to assess the ideal cutoff for read trimming and reports the values. (tools: rastair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/report": "Collects bismark alignment reports", "mm2plus/index": "Provides fasta index required by mm2plus alignment.", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "samtools/cramsize": "List CRAM Content-ID and Data-Series sizes", "rastair/mbiasparser": "Parses Rastair mbias output to assess the ideal cutoff for read trimming and reports the values."}}, "target": "rastair/mbiasparser", "target_idx": 4}
{"id": "resource_bedtools_split_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SPLIT", "tool": "bedtools/split", "description": "Split BED files into several smaller BED files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SPLIT (Split BED files into several smaller BED files) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_stacks_refmap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available. (tools: stacks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack_summarise": "Summarises results from CAT/BAT/RAT classification steps", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "stacks_refmap": "ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available.", "scds": "Module to use scds for doublet scoring"}}, "target": "stacks_refmap", "target_idx": 3}
{"id": "field_constraint_status_0_7", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "core_tool_minimap2_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Long-read mapping of Oxford Nanopore and PacBio HiFi sequencing reads against human and microbial reference assemblies.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"star": null, "minimap2": null, "bwa_mem": null, "subread": null, "bowtie2": null}}, "target": "minimap2", "target_idx": 1}
{"id": "mod_kaiju_mkfmi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make Kaiju FMI-index file from a protein FASTA file (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge_centrifuge": "Classifies metagenomic sequence data", "ucsc_bedgraphtobigwig": "Convert a bedGraph file to bigWig format.", "kaiju_mkfmi": "Make Kaiju FMI-index file from a protein FASTA file", "seqtk_seq": "Common transformation operations on FASTA or FASTQ files.", "conifer": "Calculate confidence scores from Kraken2 output"}}, "target": "kaiju_mkfmi", "target_idx": 2}
{"id": "resource_abra2_1", "category": "resource_profiling", "state": {"process": "ABRA2", "tool": "abra2", "description": "Assembly Based ReAligner for next-generation sequencing data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRA2 (Assembly Based ReAligner for next-generation sequencing data) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_workflow_completion_lifecycle_hook_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_named_output_channel_access_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "schema_std_rnasplice_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnasplice", "description": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnasplice?", "criteria": {"sample,seq_data,pbi,start_from": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,tools,file,index": null, "sample,fastq_1,fastq_2,bam,seq_type": null}}, "target": "sample,fastq_1,fastq_2,strandedness,condition", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_1_5", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "intent_build_pipeline_0", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "noul_named_process_output_emits_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "local_subworkflow_irma_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should IRMA (irma) be built?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow IRMA": null, "Use nf-core subworkflow irma": null}}, "target": "Local subworkflow IRMA", "target_idx": 2}
{"id": "samplesheet_arch_rare_disease_trio_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/raredisease) for Trio exome/genome sequencing (Proband, Mother, Father). Input files: Paired-end FASTQs with pedigree relationships and affected status.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_4_3", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "template": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads for immunoprecipitation and input chromatin?", "criteria": {"sample,antibody,control": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_5", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_spatial_xenium_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Xenium in situ subcellular spatial RNA transcriptomics)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Xenium in situ subcellular spatial RNA transcriptomics.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "mod_bamreadcount_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads. (tools: bamreadcount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamreadcount": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencin", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "snpsift_annmem": "Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-opt", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods."}}, "target": "bamreadcount", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_1_38", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_mcmicro_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for bioformats analysis? Specific context: An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data.. Topics: bioformats, image-analysis, image-processing, microscopy, multiplexed-imaging, ome-tiff. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "mcmicro", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_6_4", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Fungal ITS1/ITS2 marker gene amplicon surveillance input samplesheet?", "criteria": {"sample,primer_its1,primer_its2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,unite_fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_agat_spaddintrons_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Add intron features to gtf/gff file without intron features. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spstatistics": "Provides different type of statistics in text format from a GFF/GTF annotation file", "cellranger/multi": "Module to use Cell Ranger's pipelines to analyze sequencing data produced from various Chromium technologies, ", "agat/spaddintrons": "Add intron features to gtf/gff file without intron features.", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "gstama/collapse": "Collapse redundant transcript models in Iso-Seq data."}}, "target": "agat/spaddintrons", "target_idx": 2}
{"id": "pipe_all101_slamseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: SLAMSeq processing and analysis pipeline. Topics: differential-expression, quantseq, slamseq, transcriptomics. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]"}}, "target": "slamseq", "target_idx": 5}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/pacvar --input samplesheet.csv (Assay: PacBio HiFi unaligned BAM variant calling)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for PacBio HiFi unaligned BAM variant calling with entry step PBMM2_ALIGN.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_43", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_fastqscreen_fastqscreen_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to multiple reference genomes using fastq-screen (tools: fastqscreen)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscreen/fastqscreen": "Align reads to multiple reference genomes using fastq-screen", "seqfu/derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "gatk4/variantfiltration": "Filter variants"}}, "target": "fastqscreen/fastqscreen", "target_idx": 0}
{"id": "mod_fqtk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex fastq files (tools: fqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "fqtk": "Demultiplex fastq files", "qcat": "Demultiplexer for Nanopore samples", "gridss/preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and ", "trimal": "trimAl is a tool for the automated removal of spurious sequences or poorly aligned regions from a multiple seq"}}, "target": "fqtk", "target_idx": 1}
{"id": "resource_aardvark_compare_5", "category": "resource_profiling", "state": {"process": "AARDVARK_COMPARE", "tool": "aardvark/compare", "description": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_COMPARE (A tool to evaluate variant calling performance by comparing a query VCF against ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "local_subworkflow_positionsofint_1_5", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should this step (custom/positionsofint) be packaged: Position of interest depth extraction?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow positionsofint": null, "Local subworkflow POSITIONSOFINT": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 3}
{"id": "mod_dedup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments). (tools: dedup)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "hamronization/deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "pairtools/dedup": "Find and remove PCR/optical duplicates", "pasty": "Serogroup Pseudomonas aeruginosa assemblies"}}, "target": "dedup", "target_idx": 2}
{"id": "local_subworkflow_prepilluminareads_1_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "How should this step (trimmomatic) be packaged: Single-step adapter trimming for Illumina reads?", "criteria": {"Local subworkflow PREPILLUMINAREADS": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow prepilluminareads": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for 10x Multiome single-cell joint RNA and ATAC chromatin. Input files: Paired FASTQs for both GEX and ATAC modalities per nucleus.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,bam": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "field_constraint_fastq_1_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "resource_ampcombi2_parsetables_4", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_PARSETABLES", "tool": "ampcombi2/parsetables", "description": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_PARSETABLES (A submodule that parses and standardizes the results from various antimicrobial ) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_holodeck_methylate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a methylation-annotated VCF from a reference genome with holodeck (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"holodeck/eval": null, "holodeck/methylate": null, "hmmer/hmmemit": null, "fastq_shortreads_preprocess_qc": null, "miranda": null}}, "target": "holodeck/methylate", "target_idx": 1}
{"id": "field_constraint_expected_cells_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "mod_taxonkit_name2taxid_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert taxon names to TaxIds (tools: taxonkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_classify": "Classify FASTQ files against ganon database", "manta_tumoronly": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "taxonkit_name2taxid": "Convert taxon names to TaxIds", "ganon_report": "Generate a ganon report file from the output of ganon classify", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters"}}, "target": "taxonkit_name2taxid", "target_idx": 2}
{"id": "resource_ashlar_3", "category": "resource_profiling", "state": {"process": "ASHLAR", "tool": "ashlar", "description": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASHLAR (Alignment by Simultaneous Harmonization of Layer/Adjacency Registration) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_nascent_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Nascent Transcription Processing Pipeline. Topics: gro-seq, nascent, pro-seq, rna, transcription, tss. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]"}}, "target": "nascent", "target_idx": 3}
{"id": "mod_ampir_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ampir uses a supervised statistical machine learning approach to predict AMPs. (tools: ampir)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampir": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "macrel/contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid", "lima": "lima - The PacBio Barcode Demultiplexer and Primer Remover", "humann3/regroup": "Regrouping genes to other functional categories"}}, "target": "ampir", "target_idx": 0}
{"id": "resource_arriba_visualisation_5", "category": "resource_profiling", "state": {"process": "ARRIBA_VISUALISATION", "tool": "arriba/visualisation", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_VISUALISATION (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_8", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "intent_prepare_data_6", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "prepare_data", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "assay_type": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "data_format": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_fastme_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Distance-based phylogeny with FastME (tools: fastme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_newick_epang_gappa": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in ", "fastme": "Distance-based phylogeny with FastME", "nanolyse": "DNA contaminant removal using NanoLyse", "clustalo/guidetree": "Renders a guidetree in clustalo", "authentict/deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries"}}, "target": "fastme", "target_idx": 1}
{"id": "resource_bcftools_filter_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_FILTER", "tool": "bcftools/filter", "description": "Filters VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_FILTER (Filters VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_trgt_genotype_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tandem repeat genotyping from PacBio HiFi data (tools: trgt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trgt_genotype": "Tandem repeat genotyping from PacBio HiFi data", "trgt_merge": "Merge TRGT VCFs from multiple samples", "unzipfiles": "Unzip ZIP archive files", "hifiadapterfilt_downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "picard_collectalignmentsummarymetrics": "Collect metrics about the alignment summary of a paired-end library."}}, "target": "trgt_genotype", "target_idx": 0}
{"id": "field_constraint_sex_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/dualrnaseq", "assay_type": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "data_format": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,fastq_1": null, "sample,host_fasta": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should POSITIONSOFINT (custom/positionsofint) be built?", "criteria": {"Use nf-core subworkflow positionsofint": null, "Local subworkflow POSITIONSOFINT": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 1}
{"id": "mod_bismark_genomepreparation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "emboss_seqret": "Reads in one or more sequences, converts, filters, or transforms them and writes them out again", "bismark_align": "Performs alignment of BS-Seq reads using bismark", "bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "sentieon_applyvarcal": "Apply a score cutoff to filter variants based on a recalibration table.\nSentieon's Aplyvarcal performs the sec"}}, "target": "bismark_genomepreparation", "target_idx": 0}
{"id": "mod_cooltools_eigscis_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform eigen value decomposition on a cooler matrix to calculate compartment signal by finding the eigenvector that correlates best with the phasing track (tools: cooltools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler_balance": "Run matrix balancing on a cool file", "gatk4_selectvariants": "Select a subset of variants from a VCF file", "mudskipper_bulk": "Convert genomic BAM/SAM files to transcriptomic BAM/RAD files.", "cooltools_eigscis": "Perform eigen value decomposition on a cooler matrix to calculate compartment signal by finding the eigenvecto", "calder2": "Hierarchical Hi-C compartment computation"}}, "target": "cooltools_eigscis", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_31", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_46", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_pcgr_getref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Get reference to run Personal Cancer Genome Reporter (PCGR) (tools: pcgr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastqscan": "FASTQ summary statistics in JSON format", "zip": "Compress file lists to produce ZIP archive files", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "pcgr_getref": "Get reference to run Personal Cancer Genome Reporter (PCGR)", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously"}}, "target": "pcgr_getref", "target_idx": 3}
{"id": "mod_skani_sketch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Storing skani sketches/indices on disk. (tools: skani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lissero": "Serogrouping Listeria monocytogenes assemblies", "picard/scatterintervalsbyns": "Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into inte", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "skani/triangle": "All-to-all ANI computation.", "skani/sketch": "Storing skani sketches/indices on disk."}}, "target": "skani/sketch", "target_idx": 4}
{"id": "noul_workflow_completion_lifecycle_hook_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_22", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_channel_mix_operator_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_0_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "data_format": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multiplexed Oxford Nanopore run with barcode demultiplexing with entry step NANOPLOT.", "criteria": {"sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "mod_gatk4_reblockgvcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Condenses homRef blocks in a single-sample GVCF (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/analyzecovariates": null, "rtn/tni": null, "gatk4/annotateintervals": null, "fastq_shortreads_preprocess_qc": null, "gatk4/reblockgvcf": null}}, "target": "gatk4/reblockgvcf", "target_idx": 4}
{"id": "samplesheet_arch_faire_seq_chromatin_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for FAIRE-seq / DNAse-seq open chromatin profiling. Input files: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_bedtools_map_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Allows one to screen for overlaps between two sets of genomic features. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_map": "Allows one to screen for overlaps between two sets of genomic features.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "crabs_insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR.", "fasttree": "Produces a Newick format phylogeny from a multiple sequence alignment. Capable of bacterial genome size alignm"}}, "target": "bedtools_map", "target_idx": 0}
{"id": "resource_bioformats2raw_5", "category": "resource_profiling", "state": {"process": "BIOFORMATS2RAW", "tool": "bioformats2raw", "description": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOFORMATS2RAW (Java application to convert image file formats, including .mrxs, to an intermedi) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_cellranger_vdj_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Immune Profiling. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellranger_vdj": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Immune Profil", "mcstaging_phenoimager2mc": "Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per c", "deeptools_bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig ", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}}, "target": "cellranger_vdj", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/eager) for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment. Input files: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bcftools_sort_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SORT", "tool": "bcftools/sort", "description": "Sorts VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SORT (Sorts VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_medium", "target_idx": 1}
{"id": "mod_hamronization_rgi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize RGI outputs using the hAMRonization specification. (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"helitronscanner/scan": "HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes", "hamronization/deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "htseq/count": "count how many reads map to each feature", "hamronization/rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification.", "hamronization/amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification."}}, "target": "hamronization/rgi", "target_idx": 3}
{"id": "mod_agat_spmergeannotations_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated names and fixes other oddities met in those files. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bases2fastq": "Demultiplex Element Biosciences bases files", "angsd/dosaf": "Estimate site allele frequencies from BAM files.", "alignoth": "Creating alignment plots from bam files", "treerecs": "Treerecs is an open-source (species- and gene-) tree reconciliation software distributed under the GNU AGPL li", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "agat/spmergeannotations", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_1_39", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_biobambam_bammerge_1", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMERGE", "tool": "biobambam/bammerge", "description": "Merge a list of sorted bam files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMERGE (Merge a list of sorted bam files) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_ribocode_gtfupdate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Update GTF annotation file for RiboCode compatibility (tools: ribocode)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode_prepare": null, "ribocode_gtfupdate": null, "custom_orfmerge": null, "ribotish_predict": null, "smncopynumbercaller": null}}, "target": "ribocode_gtfupdate", "target_idx": 1}
{"id": "intent_prepare_data_11", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "ask_question": null, "prepare_data": null}}, "target": "prepare_data", "target_idx": 3}
{"id": "field_constraint_fastq_1_2_10", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_1' validated?", "criteria": {"type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "resource_annotsv_annotsv_4", "category": "resource_profiling", "state": {"process": "ANNOTSV_ANNOTSV", "tool": "annotsv/annotsv", "description": "Annotation and Ranking of Structural Variation"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_ANNOTSV (Annotation and Ranking of Structural Variation) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_46", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_4_0", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_37", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Standard Paired-end Whole Genome Sequencing (WGS). Input files: Raw paired-end Illumina WGS FASTQs.", "question": {"type": "choice", "instructions": "Which columns are standard for Standard Paired-end Whole Genome Sequencing (WGS) input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_0_1", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Tumor-only somatic variant calling without matched normal?", "criteria": {"patient,normal,tumor": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_longraredisease_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for nanopore analysis? Specific context: Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders. Topics: nanopore, pacbio. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]"}}, "target": "longraredisease", "target_idx": 9}
{"id": "samplesheet_arch_vcf_annotation_pipeline_6_4", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns are standard for Downstream functional annotation of pre-called VCF files input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf,tbi": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "mod_blast_blastn_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a BLAST DNA database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": null, "gatk4_filtervarianttranches": null, "any2fasta": null, "blast_blastn": null, "basicpy": null}}, "target": "blast_blastn", "target_idx": 3}
{"id": "mod_hapibd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The hap-ibd program detects identity-by-descent (IBD) segments and homozygosity-by-descent (HBD) segments in phased genotype data. The hap-ibd program can analyze data sets with hundreds of thousands of samples. (tools: hapibd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krona/ktimportkrona": "Collect multiple krona reports into a single html file", "pretextsnapshot": "A module to generate images from Pretext contact maps.", "dshbio/filterbed": "Filter features in gzipped BED format", "snippy/run": "Rapid haploid variant calling", "hapibd": "The hap-ibd program detects identity-by-descent (IBD) segments and homozygosity-by-descent (HBD) segments in p"}}, "target": "hapibd", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_22", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_bio2zarr_vcfpartition_1", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCFPARTITION", "tool": "bio2zarr/vcfpartition", "description": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCFPARTITION (Outputs a set of region strings that partition indexed VCF/BCF files for paralle) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_rnadnavar_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for RNA and DNA integrated analysis for somatic mutation detection. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"chipseq": null, "nanostring": null, "rnadnavar": null, "createtaxdb": null, "references": null, "differentialabundance": null, "riboseq": null, "createpanelrefs": null}}, "target": "rnadnavar", "target_idx": 2}
{"id": "intent_debug_error_2", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "debug_error", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay_type": "PacBio HiFi unaligned BAM variant calling", "data_format": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "resource_bcftools_sort_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SORT", "tool": "bcftools/sort", "description": "Sorts VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SORT (Sorts VCF files) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_medium", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_4_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "mod_lima_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: lima - The PacBio Barcode Demultiplexer and Primer Remover (tools: lima)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gstama/collapse": "Collapse redundant transcript models in Iso-Seq data.", "isoseq3/tag": "Extract UMI and cell barcodes", "picard/cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "lima": "lima - The PacBio Barcode Demultiplexer and Primer Remover", "icountmini/summary": "Report proportion of cross-link events/sites on each region type."}}, "target": "lima", "target_idx": 3}
{"id": "resource_angsd_docounts_0", "category": "resource_profiling", "state": {"process": "ANGSD_DOCOUNTS", "tool": "angsd/docounts", "description": "Calculates base frequency statistics across reference positions from BAM."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOCOUNTS (Calculates base frequency statistics across reference positions from BAM.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bioformats2raw_2", "category": "resource_profiling", "state": {"process": "BIOFORMATS2RAW", "tool": "bioformats2raw", "description": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOFORMATS2RAW (Java application to convert image file formats, including .mrxs, to an intermedi) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_4", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_3_1", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "mod_clonalframeml_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict recomination events in bacterial genomes (tools: clonalframeml)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "clonalframeml": "Predict recomination events in bacterial genomes", "ilastik/pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "foldmason/msa2lddtreport": "Renders a visualization report using foldmason"}}, "target": "clonalframeml", "target_idx": 2}
{"id": "pipe_all101_mcmicro_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for bioformats. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin"}}, "target": "mcmicro", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_1_4", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_lofreq_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to call low frequency variants from alignments (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krona_ktupdatetaxonomy": null, "bcftools_consensus": null, "agat_spstatistics": null, "aardvark_merge": null, "lofreq_call": null}}, "target": "lofreq_call", "target_idx": 4}
{"id": "subworkflow_pkg_bam_taps_conversion_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TAPS_CONVERSION", "modules": ["rastair/mbias", "rastair/call", "rastair/methylkit", "rastair/mbiasparser"], "description": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis"}, "question": {"type": "choice", "instructions": "How should BAM_TAPS_CONVERSION (rastair/mbias, rastair/call, rastair/methylkit, rastair/mbiasparser) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_taps_conversion": null, "Local subworkflow BAM_TAPS_CONVERSION": null}}, "target": "Use nf-core subworkflow bam_taps_conversion", "target_idx": 2}
{"id": "mod_fastdup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FastDup is a tool designed to locate and tag duplicate reads in a coordinate-sorted SAM or BAM file, using the same core algorithm as Picard MarkDuplicates. (tools: fastdup)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"purgedups_splitfa": "Split fasta file by 'N's to aid in self alignment for duplicate purging", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "fastdup": "FastDup is a tool designed to locate and tag duplicate reads in a coordinate-sorted SAM or BAM file, using the", "octopusv_plotcircos": "Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file.", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "fastdup", "target_idx": 2}
{"id": "mod_canu_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. (tools: canu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ale": null, "canu": null, "agat/spflagshortintrons": null, "abra2": null, "rmarkdownnotebook": null}}, "target": "canu", "target_idx": 1}
{"id": "resource_baysor_segfree_3", "category": "resource_profiling", "state": {"process": "BAYSOR_SEGFREE", "tool": "baysor/segfree", "description": "Extract neighborhood composition vectors (NVCs) from a dataset."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAYSOR_SEGFREE (Extract neighborhood composition vectors (NVCs) from a dataset.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_svtk_vcf2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts VCFs containing structural variants to BED format (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/call": "generate VCF file from a BAM file using various calling methods", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "fasta_index_dna": "Generate aligner index for a reference genome.\nPlease note, this workflow requires input CHANNELS. Input value", "bam_dedup_umi": "BAM deduplication with UMI processing for both genome and transcriptome alignments", "svtk/vcf2bed": "Converts VCFs containing structural variants to BED format"}}, "target": "svtk/vcf2bed", "target_idx": 4}
{"id": "samplesheet_arch_faire_seq_chromatin_4_3", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_gt_gff3validator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GenomeTools gt-gff3validator utility to strictly validate a GFF3 file (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt_gff3validator": "GenomeTools gt-gff3validator utility to strictly validate a GFF3 file", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "samtools_bedcov": "reports coverage over regions in a supplied BED file", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "octopusv_correct": "Standardize a caller VCF into OctopuSV SVCF format."}}, "target": "gt_gff3validator", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_48", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Standard Paired-end Whole Genome Sequencing (WGS). Input files: Raw paired-end Illumina WGS FASTQs.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Standard Paired-end Whole Genome Sequencing (WGS) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_bandage_image_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render an assembly graph in GFA 1.0 format to PNG and SVG image formats (tools: bandage)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm/lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA", "bandage/image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats", "odgi/draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "cutesv": "structural-variant calling with cutesv"}}, "target": "bandage/image", "target_idx": 2}
{"id": "schema_std_viralrecon_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "description": "Assembly and intrahost/low-frequency variant calling for viral samples", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/viralrecon?", "criteria": {"sample,fastq_1,fastq_2,barcode": null, "sample_id,mapped,index,file_type": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,fastq_1,fastq_2,replicate,antibody": null}}, "target": "sample,fastq_1,fastq_2,barcode", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_47", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_deacon_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create deacon index for reference genome (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/depth": "Computes the depth at each position or region.", "deacon/index": "Create deacon index for reference genome", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "bowtie/build": "Create bowtie index for reference genome", "sylph/sketchgenomes": "Sylph profile command for taxonoming profiling of genomes"}}, "target": "deacon/index", "target_idx": 1}
{"id": "mod_amulety_antiberta2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety/antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety.", "amulety/antiberty": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety.", "amulety/translate": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast.", "wisecondorx/gender": "Returns the gender of a .npz resulting from convert, based on a Gaussian mixture model trained during the newr", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization."}}, "target": "amulety/antiberta2", "target_idx": 0}
{"id": "mod_kmcp_compute_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate k-mers (sketches) from FASTA/Q sequences (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kmcp_compute": "Generate k-mers (sketches) from FASTA/Q sequences", "sentieon_bwaindex": "Create BWA index for reference genome", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "flash": "Perform merging of mate paired-end sequencing reads"}}, "target": "kmcp_compute", "target_idx": 0}
{"id": "pipe_all101_chipseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for chip. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]"}}, "target": "chipseq", "target_idx": 6}
{"id": "qc_adapt_singlecell_multiqc_0_10", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_plastid_psite_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate position of ribosomal P-site within ribosome profiling read alignments as a function of read length (tools: plastid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms_peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)", "samtools_fixmate": "Samtools fixmate is a tool that can fill in information (insert size, cigar, mapq) about paired end reads onto", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "plastid_psite": "Estimate position of ribosomal P-site within ribosome profiling read alignments as a function of read length", "alignoth": "Creating alignment plots from bam files"}}, "target": "plastid_psite", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/chipseq --input samplesheet.csv (Assay: ChIP-seq with IP and input control design)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1,fastq_2": null, "sample,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 0}
{"id": "field_constraint_sample_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"format: file-path": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_tximeta_tximport_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Import transcript-level abundances and estimated counts for gene-level\nanalysis packages (tools: tximeta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "tximeta_tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages", "vcf2maf": "vcf2maf", "gatk4_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "summarizedexperiment_summarizedexperiment": "SummarizedExperiment container"}}, "target": "tximeta_tximport", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_19", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_1_3", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,cpg,methylation": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/metatdenovo) for Environmental community metatranscriptomics de novo assembly. Input files: Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null, "sample,bam": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 1}
{"id": "mod_sourcepredict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classifies and predicts the origin of metagenomic samples (tools: sourcepredict)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trinity": "Assembles a de novo transcriptome from RNAseq reads", "sourcepredict": "Classifies and predicts the origin of metagenomic samples", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "miniprot_index": "Provides fasta index required by miniprot alignment.", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD"}}, "target": "sourcepredict", "target_idx": 1}
{"id": "mod_cat_fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are automatically gzip-compressed during concatenation. (tools: cat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_gvcftyper": "Perform joint genotyping on one or more samples pre-called with Sentieon's Haplotyper.", "angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "cat_fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs", "find_concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size"}}, "target": "cat_fastq", "target_idx": 2}
{"id": "mod_windowmasker_ustat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program to take a counts file and creates a file of genomic co-ordinates to be masked. (tools: windowmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"windowmasker/ustat": "A program to take a counts file and creates a file of genomic co-ordinates to be masked.", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "controlfreec/makegraph": "Plot Freec output", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "regenie/runl0": "Run one REGENIE step 1 level-0 job from a split master file"}}, "target": "windowmasker/ustat", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Trio exome/genome sequencing (Proband, Mother, Father))", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Trio exome/genome sequencing (Proband, Mother, Father).", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_12", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_busco_phylogenomics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct species phylogenies using BUSCO proteins (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco/phylogenomics": null, "ashlar": null, "stadeniolib/scramble": null, "nanomonsv/get": null, "bwa/mem": null}}, "target": "busco/phylogenomics", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_24", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_bedtools_complement_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COMPLEMENT", "tool": "bedtools/complement", "description": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COMPLEMENT (Returns all intervals in a genome that are not covered by at least one interval ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_singlecell_parse_splitseq_3_2", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Parse Biosciences Split-seq combinatorial barcoding with entry step FASTQC.", "criteria": {"sample,well,plate": null, "sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_rnaseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay": "rnaseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnaseq (RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or)?", "criteria": {"sample_id,subject_id,species,pcr_target_locus,tissue": null, "sample_id,idat_red,idat_green,group": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample,fastq_1,fastq_2,strandedness,seq_platform", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_5_3", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Multiplexed Oxford Nanopore run with barcode demultiplexing.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,barcode": null, "sample,bam": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: FAIRE-seq / DNAse-seq open chromatin profiling)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_biscuit_qc_5", "category": "resource_profiling", "state": {"process": "BISCUIT_QC", "tool": "biscuit/qc", "description": "Perform basic quality control on a BAM file generated with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_QC (Perform basic quality control on a BAM file generated with Biscuit) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_15", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_busco_generateplot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BUSCO plot generation tool (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "deeptools/plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "star/starsolo": "Create a counts matrix for single-cell data using STARSolo, handling cell barcodes and UMI information.", "busco/generateplot": "BUSCO plot generation tool"}}, "target": "busco/generateplot", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_2_24", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_thermorawfileparser_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parses a Thermo RAW file containing mass spectra to an open file format (tools: thermorawfileparser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"thermorawfileparser": null, "bedtools/coverage": null, "openmsthirdparty/cometadapter": null, "quantmsutils/mzmlstatistics": null, "quartonotebook": null}}, "target": "thermorawfileparser", "target_idx": 0}
{"id": "samplesheet_arch_proteomics_dia_0_1", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,fasta": null, "sample,mzml": null, "sample,raw_file,condition": null, "sample,peptides_tsv": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "resource_bbmap_index_2", "category": "resource_profiling", "state": {"process": "BBMAP_INDEX", "tool": "bbmap/index", "description": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_INDEX (Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_samtools_markdup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mark duplicate alignments in a coordinate sorted file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_markdup": "mark duplicate alignments in a coordinate sorted file", "fastq_find_mirna_mirdeep2": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, proc", "ascat": "copy number profiles of tumour cells.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "hifitrimmer_processblast": "Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrima"}}, "target": "samtools_markdup", "target_idx": 0}
{"id": "field_constraint_expected_cells_0_1", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_bakta_bakta_0", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTA", "tool": "bakta/bakta", "description": "Annotation of bacterial genomes (isolates, MAGs) and plasmids"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTA (Annotation of bacterial genomes (isolates, MAGs) and plasmids) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_1", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_bamtools_convert_3", "category": "resource_profiling", "state": {"process": "BAMTOOLS_CONVERT", "tool": "bamtools/convert", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_CONVERT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_annosine_2", "category": "resource_profiling", "state": {"process": "ANNOSINE", "tool": "annosine", "description": "Accelerating de novo SINE annotation in plant and animal genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOSINE (Accelerating de novo SINE annotation in plant and animal genomes) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_lsa_cosine_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates the cosine similarity matrix between samples based on a gene expression matrix. (tools: lsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lsa_cosine": "Calculates the cosine similarity matrix between samples based on a gene expression matrix.", "autocycler_cluster": "Cluster replicons in compressed assemblies with Autocycler.", "vamb_bin": "Variational autoencoder for metagenomic binning", "comebin_runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "rclone_copy": "Copy files or directories between local and/or remote storage using Rclone"}}, "target": "lsa_cosine", "target_idx": 0}
{"id": "field_constraint_fastq_2_1_2", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "field_constraint_phenotype_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [normal, tumor]": null, "type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_2_4", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bedtools_groupby_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GROUPBY", "tool": "bedtools/groupby", "description": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another column."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GROUPBY (Groups features in a BED file by given column(s) and computes summary statistics) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_shinyngs_validatefomcomponents_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: validate consistency of feature and sample annotations with matrices and contrasts (tools: shinyngs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/pca": "Perform PCA analysis using PLINK", "affy/justrma": "Read CEL files into an ExpressionSet and generate a matrix", "htodemux": "Demultiplex samples based on data from cell hashing.", "geoquery/getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)", "shinyngs/validatefomcomponents": "validate consistency of feature and sample annotations with matrices and contrasts"}}, "target": "shinyngs/validatefomcomponents", "target_idx": 4}
{"id": "pipe_all101_crisprseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`).. Topics: crispr, crispr-analysis, crispr-cas, ngs. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner"}}, "target": "crisprseq", "target_idx": 2}
{"id": "samplesheet_arch_methylseq_bisulfite_4_1", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_taxprofiler_shotgun_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "assay_type": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "data_format": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Short or long reads with run accession and library instrument platform?", "criteria": {"sample,kraken_db": null, "sample,bam": null, "sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_module_metadata_propagation_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_ask_question_6", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_7_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fasta": null, "sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_2_26", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_purecn_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run PureCN workflow to normalize, segment and determine purity and ploidy (tools: purecn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA", "plink/missing": "Compute sample-based and variant-based missing genotype rates and write a new PLINK binary fileset", "purecn/run": "Run PureCN workflow to normalize, segment and determine purity and ploidy", "purecn/coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI", "purecn/intervalfile": "Generate on and off-target intervals for PureCN from a list of targets"}}, "target": "purecn/run", "target_idx": 2}
{"id": "mod_miniasm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A very fast OLC-based de novo assembler for noisy long reads (tools: miniasm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"unzip": "Unzip ZIP archive files", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "miniasm": "A very fast OLC-based de novo assembler for noisy long reads", "ale": "ALE: assembly likelihood estimator.", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}}, "target": "miniasm", "target_idx": 2}
{"id": "noul_module_metadata_propagation_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_16", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "field_constraint_phenotype_1_8", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [normal, tumor]": null, "format: file-path": null, "type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "resource_bio2zarr_vcf2zarrconvert_1", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARRCONVERT", "tool": "bio2zarr/vcf2zarrconvert", "description": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARRCONVERT (Convert VCF data to the VCF Zarr specification reliably, in parallel or distribu) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_khmer_trimlowabund_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes low abundance k-mers from FASTA/FASTQ files (tools: khmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "jvarkit_sam2tsv": "Convert sam files to tsv files", "busco_generateplot": "BUSCO plot generation tool", "khmer_trimlowabund": "Removes low abundance k-mers from FASTA/FASTQ files", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt"}}, "target": "khmer_trimlowabund", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_5_4", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: Fungal ITS1/ITS2 marker gene amplicon surveillance.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_jupyternotebook_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill. (tools: jupytext)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill.", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization.", "shinyngs/validatefomcomponents": "validate consistency of feature and sample annotations with matrices and contrasts", "quarto/prerender": "Pre-render a Quarto document to markdown, including parametrization", "authentict/deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries"}}, "target": "jupyternotebook", "target_idx": 0}
{"id": "noul_invalid_process_communication_via_globals_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_rpbp_selectperiodicoffsets_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produced upstream. For each\nread length, the offset with the highest periodicity Bayes-factor mean\nis selected - this is the offset that, when added to a read's 5' end,\nis estimated to land closest to the ribosomal P-site (the codon being\ndecoded). Downstream, these offsets are used to convert raw read\n5'-end coordinates into P-site positions when counting reads against\ncandidate ORFs.\n\nEmits one row per read length (length, best offset, supporting Bayes\nfactor statistics). The next step\n(`rpbp/getperiodiclengthsoffsets`) filters this table to the high-quality\npairs that pass user-specified count / signal thresholds before\nP-site counting in `rpbp/extractorfprofiles`. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp_getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "methbat_profile": "Runs methbat profile command to create methylation profiles for regions of interest from CpG metrics.", "rpbp_selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "samtools_collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma"}}, "target": "rpbp_selectperiodicoffsets", "target_idx": 2}
{"id": "mod_dssp_mkdssp_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates secondary structure assignments from PDB files using mkdssp (DSSP).\nDSSP is a standard tool for assigning secondary structure to amino acids in protein structures. (tools: dssp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caalm_caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES", "blast_blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "snapaligner_align": "Performs fastq alignment to a fasta reference using SNAP", "nacho_normalize": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "dssp_mkdssp": "Calculates secondary structure assignments from PDB files using mkdssp (DSSP).\nDSSP is a standard tool for ass"}}, "target": "dssp_mkdssp", "target_idx": 4}
{"id": "mod_gapseq_findtransport_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict transporters from genomic data using gapseq (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"graphmap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "gapseq_findtransport": "Predict transporters from genomic data using gapseq", "clame": "binning of metagenomic sequences", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "alignoth": "Creating alignment plots from bam files"}}, "target": "gapseq_findtransport", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_23", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_icountmini_summary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Report proportion of cross-link events/sites on each region type. (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplocheck": null, "tcoffee_consensus": null, "icountmini_segment": null, "icountmini_summary": null, "icountmini_metagene": null}}, "target": "icountmini_summary", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_4_3", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Combinatorial split-pool barcoded FASTQs with subpool annotations?", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_bedtools_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "bedtools_merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "agat_spstatistics": "Provides different type of statistics in text format from a GFF/GTF annotation file", "treerecs": "Treerecs is an open-source (species- and gene-) tree reconciliation software distributed under the GNU AGPL li"}}, "target": "bedtools_merge", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/hic) for Hi-C chromosome conformation capture mapping. Input files: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Hi-C chromosome conformation capture mapping?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry))", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "pipe_all101_phyloplace_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.. Topics: evolution, evolutionary-tree, phylogenetic-placement, phylogenetics, sequence-classification, taxonomy-assignment. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "metapep": "From metagenomes to epitopes and beyond", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]"}}, "target": "phyloplace", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_5_3", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/smrnaseq, determine the input samplesheet column structure for: Small RNA / miRNA sequencing.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,mirna_id": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_sequencetools_pileupcaller_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PileupCaller is a tool to create genotype calls from bam files using read-sampling methods (tools: sequencetools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellsnp_modea": "Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A ", "freebayes": "A haplotype-based variant detector", "kmcp_merge": "Merge search results from multiple databases.", "sequencetools_pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "gcta_remlldms": "Run REML-LDMS heritability estimation with an MGRM manifest"}}, "target": "sequencetools_pileupcaller", "target_idx": 3}
{"id": "mod_fasta_explore_search_plot_tidk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats\nalong a sliding window for each sequence in the input fasta file. Results are presented in\nTSV and SVG formats. The user can specify an a priori sequence for identification.\nPossible a posteriori sequences are also explored and the most frequent sequence is\nused for identification similar to the a priori sequence. seqkit/seq and seqkit/sort modules are\nalso included to filter out small sequences and sort sequences by length. (tools: fasta_explore_search_plot_tidk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yahs": "Performs assembly scaffolding using YaHS", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "fasta_explore_search_plot_tidk": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats\nalong a sliding win", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "savana/run": "Identify and cluster SV breakpoints from long-read alignments."}}, "target": "fasta_explore_search_plot_tidk", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_9", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_cnvpytor_view_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: view function to generate vcfs (tools: cnvpytor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"angsd_soapsnpcalibration": null, "abyss_abysspe": null, "cnvkit_target": null, "canvas_germline": null, "cnvpytor_view": null}}, "target": "cnvpytor_view", "target_idx": 4}
{"id": "mod_pear_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger. (tools: pear)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"merquryfk_katgc": null, "bedtools_merge": null, "pear": null, "fastq_align_hisat2": null, "bcftools_merge": null}}, "target": "pear", "target_idx": 2}
{"id": "subworkflow_pkg_bam_ngscheckmate_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_NGSCHECKMATE", "modules": ["bcftools/mpileup", "ngscheckmate/ncm"], "description": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set of SNPs."}, "question": {"type": "choice", "instructions": "How should BAM_NGSCHECKMATE (bcftools/mpileup, ngscheckmate/ncm) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_NGSCHECKMATE": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_ngscheckmate": null}}, "target": "Use nf-core subworkflow bam_ngscheckmate", "target_idx": 3}
{"id": "schema_std_pixelator_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pixelator", "assay": "pixelator pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/pixelator (Pipeline to generate Proximity Network Assay data with Pixel)?", "criteria": {"sample,fastq,cell_count": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,pool,hash_index": null}}, "target": "sample,fastq_1,fastq_2,pool,hash_index", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_index_filter_deacon_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_INDEX_FILTER_DEACON", "modules": ["deacon/index", "deacon/filter"], "description": "Decontaminate FastQ files by filtering reads that match a reference genome using Deacon"}, "question": {"type": "choice", "instructions": "How should FASTQ_INDEX_FILTER_DEACON (deacon/index, deacon/filter) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_INDEX_FILTER_DEACON": null, "Use nf-core subworkflow fastq_index_filter_deacon": null}}, "target": "Use nf-core subworkflow fastq_index_filter_deacon", "target_idx": 3}
{"id": "mod_nextclade_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation) (tools: nextclade)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ferrohgvs_normalize": "Normalize HGVS variant descriptions to canonical form with ferro", "proovframe_fix": "frame-shift correction for long read (meta)genomics - fix frameshifts in reads", "deepbgc_download": "Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning.", "nextclade_run": "SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation)", "nextclade_datasetget": "Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ impleme"}}, "target": "nextclade_run", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_30", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_vt_normalize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: normalizes variants in a VCF file (tools: vt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt_normalize": "normalizes variants in a VCF file", "deeptools_bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "gatk4_preprocessintervals": "Prepares bins for coverage collection.", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "vcf_filter_bcftools_ensemblvep": "Filter VCF file with bcftools and filter_vep"}}, "target": "vt_normalize", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_6_0", "category": "samplesheet_schema", "state": {"technology": "Variant Annotation", "workflow_entry": "ENSEMBLVEP", "library_inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns are standard for Downstream functional annotation of pre-called VCF files input samplesheet?", "criteria": {"sample,vcf,tbi": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_2_5", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,bed": null, "sample,bam,bai": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_0_1", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC", "inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bismark_deduplicate_1", "category": "resource_profiling", "state": {"process": "BISMARK_DEDUPLICATE", "tool": "bismark/deduplicate", "description": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_DEDUPLICATE (Removes alignments to the same position in the genome\nfrom the Bismark mapping o) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_antismash_antismashdownloaddatabases_4", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHDOWNLOADDATABASES", "tool": "antismash/antismashdownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_merquryfk_hapmaker_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables (tools: merquryfk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"meryl/count": "A genomic k-mer counter (and sequence utility) with nice features.", "merquryfk/katgc": "A reimplemenation of KatGC to work with FastK databases", "merquryfk/hapmaker": "Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables", "abundance_differential_filter": "A subworkflow for filtering differential abundance results", "strelka/somatic": "Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small coh"}}, "target": "merquryfk/hapmaker", "target_idx": 2}
{"id": "field_constraint_strandedness_1_13", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null, "pattern: ^[0-9]+$": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "mod_gatk4_mergevcfs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges several vcf files (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem2/mem": "Performs fastq alignment to a fasta reference using BWA", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "gatk4/mergevcfs": "Merges several vcf files", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "genomescope2": "Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical "}}, "target": "gatk4/mergevcfs", "target_idx": 2}
{"id": "mod_deseq2_differential_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: runs a differential expression analysis with DESeq2 (tools: deseq2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shinyngs/staticdifferential": "Make plots for interpretation of differential abundance statistics", "picard/collectvariantcallingmetrics": "Collects per-sample and aggregate (spanning all samples) metrics from the provided VCF file", "ngscheckmate/ncm": "Determining whether sequencing data comes from the same individual by using SNP matching. Designed for humans ", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "deseq2/differential": "runs a differential expression analysis with DESeq2"}}, "target": "deseq2/differential", "target_idx": 4}
{"id": "resource_bcftools_convert_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONVERT", "tool": "bcftools/convert", "description": "Converts certain output formats to VCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONVERT (Converts certain output formats to VCF) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_staramr_search_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Scans genome contigs against the ResFinder, PlasmidFinder, and PointFinder databases. (tools: staramr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt/decompose": null, "hamronization/amrfinderplus": null, "argnorm": null, "fastani": null, "staramr/search": null}}, "target": "staramr/search", "target_idx": 4}
{"id": "mod_deacon_indexunion_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine multiple deacon indexes (A ∪ B ...) (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"instrain_profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "deacon_indexunion": "Combine multiple deacon indexes (A ∪ B ...)", "pairix": "a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates", "bcftools_index": "Index VCF tools", "bowtie_build": "Create bowtie index for reference genome"}}, "target": "deacon_indexunion", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_36", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_cooler_makebins_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate fixed-width genomic bins (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler/cload": "Create a cooler from genomic pairs and bins", "cooler/makebins": "Generate fixed-width genomic bins", "seqkit/translate": "Translate DNA/RNA to protein sequence", "biscuit/pileup": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call so", "cooler/balance": "Run matrix balancing on a cool file"}}, "target": "cooler/makebins", "target_idx": 1}
{"id": "mod_gawk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: If you are like many computer users, you would frequently like to make changes in various text files\nwherever certain patterns appear, or extract data from parts of certain lines while discarding the rest.\nThe job is easy with awk, especially the GNU implementation gawk. (tools: gawk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastp": "Perform adapter/quality trimming on sequencing reads", "gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever ", "minimac4_compressref": "Compression of a reference panel for genotype imputation to `.msav` format", "seqkit_tab2fx": "Convert tabular format (first two/three columns) to FASTA/Q format.", "seqkit_fx2tab": "Convert FASTA/Q to tabular format, and provide various information, like sequence length, GC content/GC skew."}}, "target": "gawk", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_5_5", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "template": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: ATAC-seq chromatin accessibility with biological replicates.", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "mod_gatk4_modelsegments_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts copy number ratios (and optonally allelic counts) to copy number segments (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4/modelsegments": "Converts copy number ratios (and optonally allelic counts) to copy number segments", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "gatk4/modelsegments", "target_idx": 3}
{"id": "core_tool_samtools_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Coordinate-sorting, indexing, and statistics generation for genome-aligned BAM binary alignment files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bamtools": null, "picard": null, "sambamba": null, "bedtools": null, "samtools": null}}, "target": "samtools", "target_idx": 4}
{"id": "field_constraint_bam_1_6", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "field_constraint_fastq_2_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "schema_std_spatialaxe_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/spatialaxe. Description: A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/spatialaxe.", "criteria": {"patient,sample,fastq_1,fastq_2,bam": null, "sample,id,data_path,fastq_dir,cytaimage": null, "sample,bundle,image": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "sample,bundle,image", "target_idx": 2}
{"id": "subworkflow_pkg_bam_split_by_region_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SPLIT_BY_REGION", "modules": ["samtools/view", "samtools/index"], "description": "Split the reads in the input bam by specified genomic region."}, "question": {"type": "choice", "instructions": "How should BAM_SPLIT_BY_REGION (samtools/view, samtools/index) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_SPLIT_BY_REGION": null, "Use nf-core subworkflow bam_split_by_region": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_split_by_region", "target_idx": 2}
{"id": "mod_star_starsolo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a counts matrix for single-cell data using STARSolo, handling cell barcodes and UMI information. (tools: starsolo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi": null, "star_starsolo": null, "bbmap_align": null, "snippy_run": null, "xeniumranger_resegment": null}}, "target": "star_starsolo", "target_idx": 1}
{"id": "mod_tcoffee_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using T_COFFEE (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "metaphlan_makedb": "Build MetaPhlAn database for taxonomic profiling.", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "tcoffee_align": "Aligns sequences using T_COFFEE", "antismash_antismashlite": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "tcoffee_align", "target_idx": 3}
{"id": "pipe_all101_methylong_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for dna-methylation. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, "}}, "target": "methylong", "target_idx": 5}
{"id": "samplesheet_arch_ont_metagenome_single_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Long-read Oxford Nanopore environmental metagenomic sequencing", "data_format": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Oxford Nanopore environmental metagenomic sequencing input samplesheet?", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_tar_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compress directories into tarballs with various compression options (tools: tar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"archive_extract": "Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip", "catpack/reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "tar": "Compress directories into tarballs with various compression options", "untarfiles": "Extract files.", "mmseqs/easycluster": "Cluster sequences using MMSeqs2 easy cluster."}}, "target": "tar", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_1_34", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/metatdenovo --input samplesheet.csv (Assay: Environmental community metatranscriptomics de novo assembly)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "samplesheet_arch_bulk_small_rna_0_3", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "template": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_peddy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manipulation, validation and exploration of pedigrees (tools: peddy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"somalier/relate": null, "vembrane/table": null, "rtgtools/pedfilter": null, "plink2/het": null, "peddy": null}}, "target": "peddy", "target_idx": 4}
{"id": "mod_find_concatenate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size (tools: find)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk/concat": "Concatenate two or more CSV (or TSV) tables into a single table", "foldmason/createdb": "Creates a database for Foldmason.", "find/concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size", "deepvariant/vcfstatsreport": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "qsv/cat": "Concatenate two or more CSV (or TSV) tables into a single table"}}, "target": "find/concatenate", "target_idx": 2}
{"id": "resource_bbmap_index_5", "category": "resource_profiling", "state": {"process": "BBMAP_INDEX", "tool": "bbmap/index", "description": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_INDEX (Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_riboseq_profiling_5_3", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/riboseq, determine the input samplesheet column structure for: Ribosome profiling (Ribo-seq) footprint sequencing.", "criteria": {"sample,bam": null, "sample,cdna_fasta": null, "sample,vcf": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral amplicon sequencing with primers", "data_format": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_index_dna_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_DNA", "modules": ["bowtie2/build", "bwa/index", "bwamem2/index", "dragmap/hashtable", "snapaligner/index"], "description": "Generate aligner index for a reference genome."}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_DNA (bowtie2/build, bwa/index, bwamem2/index, dragmap/hashtable, snapaligner/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTA_INDEX_DNA": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_index_dna": null}}, "target": "Use nf-core subworkflow fasta_index_dna", "target_idx": 3}
{"id": "resource_agat_spaddintrons_5", "category": "resource_profiling", "state": {"process": "AGAT_SPADDINTRONS", "tool": "agat/spaddintrons", "description": "Add intron features to gtf/gff file without intron features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPADDINTRONS (Add intron features to gtf/gff file without intron features.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_cram_indexed_1_3", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,cram": null, "sample,cram,crai": null}}, "target": "sample,cram,crai", "target_idx": 3}
{"id": "resource_biscuit_pileup_2", "category": "resource_profiling", "state": {"process": "BISCUIT_PILEUP", "tool": "biscuit/pileup", "description": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_PILEUP (Computes cytosine methylation and callable SNV mutations, optionally in referenc) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_38", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "field_constraint_fastq_2_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "mod_md5sum_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create MD5 (128-bit) checksums (tools: md5sum)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt_decompose": "decomposes multiallelic variants into biallelic in a VCF file.", "cnaqc": "Quality control of copy number data from bulk WGS assays", "shasum": "Print SHA256 (256-bit) checksums.", "md5sum": "Create MD5 (128-bit) checksums", "rclone_checksum": "Check files in a destination path against a checksum SUM file"}}, "target": "md5sum", "target_idx": 3}
{"id": "mod_tbprofiler_profile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to detect resistance and lineages of M. tuberculosis genomes (tools: tbprofiler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tbprofiler/profile": "A tool to detect resistance and lineages of M. tuberculosis genomes", "ariba/run": "Query input FASTQs against Ariba formatted databases", "ectyper": "In silico prediction of E. coli serotype", "svtk/rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format.", "kallistobustools/ref": "index creation for kb count quantification of single-cell data."}}, "target": "tbprofiler/profile", "target_idx": 0}
{"id": "mod_ea-utils_gtf2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a GTF/GFF annotation file to BED12 format (tools: gtf2bed)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ea-utils_gtf2bed": "Convert a GTF/GFF annotation file to BED12 format", "bwa_index": "Create BWA index for reference genome", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat_spaddintrons": "Add intron features to gtf/gff file without intron features.", "kled": "An ultra-fast and sensitive structural variant detection tool for long-read sequencing data."}}, "target": "ea-utils_gtf2bed", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2", "modules": ["kraken2/add", "kraken2/build"], "description": "KRAKEN2 build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2 (kraken2/add, kraken2/build) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fasta_build_add_kraken2": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTA_BUILD_ADD_KRAKEN2": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2", "target_idx": 0}
{"id": "mod_macsyfinder_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download MacSyFinder models using msf_data (tools: macsyfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "shapeit5_ligate": "Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chu", "alignoth": "Creating alignment plots from bam files", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA.", "macsyfinder_download": "Download MacSyFinder models using msf_data"}}, "target": "macsyfinder_download", "target_idx": 4}
{"id": "pipe_all101_proteogenomicsdb_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis.. Topics: cosmic, gnomad, protein-databases, proteogenomics, proteomics, pypgatk. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]"}}, "target": "proteogenomicsdb", "target_idx": 3}
{"id": "samplesheet_arch_vcf_annotation_pipeline_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Downstream functional annotation of pre-called VCF files", "data_format": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,bam,bai": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "mod_gatk4_sitedepthtobaf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: EXPERIMENTAL TOOL! Convert SiteDepth to BafEvidence (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "affy_justrma": "Read CEL files into an ExpressionSet and generate a matrix", "gridss_annotate": "Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmaske", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4_sitedepthtobaf": "EXPERIMENTAL TOOL! Convert SiteDepth to BafEvidence"}}, "target": "gatk4_sitedepthtobaf", "target_idx": 4}
{"id": "samplesheet_arch_bulk_wes_pe_6_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Whole Exome Sequencing (WES) target capture input samplesheet?", "criteria": {"sample,bed": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bcftools_view_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF (tools: view)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/merge": null, "krakenuniq/preloadedkrakenuniq": null, "bcftools/consensus": null, "haplogrep3/classify": null, "bcftools/view": null}}, "target": "bcftools/view", "target_idx": 4}
{"id": "subworkflow_pkg_archive_extract_3", "category": "subworkflow_packaging", "state": {"subworkflow": "ARCHIVE_EXTRACT", "modules": ["gunzip", "untar", "unzip"], "description": "Extract archive(s) from any format"}, "question": {"type": "choice", "instructions": "How should ARCHIVE_EXTRACT (gunzip, untar, unzip) be structured in DSL2?", "criteria": {"Use nf-core subworkflow archive_extract": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow ARCHIVE_EXTRACT": null}}, "target": "Use nf-core subworkflow archive_extract", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_33", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_12", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_undeclared_process_file_inputs_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_modular_subworkflow_composition_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_status_1_5", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_6_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "samplesheet_arch_rare_disease_trio_0_2", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_module_metadata_propagation_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_gens_preparecovandbaf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tools for preparing inputs for visualization in Gens (tools: gens)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gffcompare": "Compare, merge, annotate and estimate accuracy of generated gtf files", "sequali": "Sequence quality metrics for FASTQ and uBAM files.", "gens_preparecovandbaf": "Tools for preparing inputs for visualization in Gens", "sentieon_wgsmetrics": "Collects whole genome quality metrics from a bam file", "varlociraptor_preprocess": "Obtains per-sample observations for the actual calling process with varlociraptor calls"}}, "target": "gens_preparecovandbaf", "target_idx": 2}
{"id": "mod_bedtools_shuffle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a genome file (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": null, "bedtools/shuffle": null, "bamtools/convert": null, "kalign/align": null, "mashtree": null}}, "target": "bedtools/shuffle", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_impute_beagle5_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_BEAGLE5", "modules": ["beagle5/beagle", "bcftools/index", "bcftools/view", "glimpse2/ligate"], "description": "Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_BEAGLE5 (beagle5/beagle, bcftools/index, bcftools/view, glimpse2/ligate) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow vcf_impute_beagle5": null, "Local subworkflow VCF_IMPUTE_BEAGLE5": null}}, "target": "Use nf-core subworkflow vcf_impute_beagle5", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_1_26", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "local_subworkflow_checkirma_2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for CHECKIRMA (custom/checkirma).", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow checkirma": null, "Leave them out": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "resource_abra2_4", "category": "resource_profiling", "state": {"process": "ABRA2", "tool": "abra2", "description": "Assembly Based ReAligner for next-generation sequencing data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRA2 (Assembly Based ReAligner for next-generation sequencing data) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_proteinfold_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Protein 3D structure prediction pipeline. Topics: alphafold2, colabfold, esmfold, protein-fold-prediction, protein-folding, protein-sequences. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pixelator": null, "hicar": null, "hgtseq": null, "proteinfold": null, "demultiplex": null, "chipseq": null, "cutandrun": null, "oncoanalyser": null, "longraredisease": null, "seqsubmit": null}}, "target": "proteinfold", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "schema_std_tumourevo_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tumourevo", "description": "Analysis pipeline to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/tumourevo?", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "id,fasta,query": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "patient,vcf,tbi,dataset,tumour_sample", "target_idx": 0}
{"id": "pipe_all101_clipseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling options.. Topics: clip, clip-seq, peak-calling, rna-rbp-interactions. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis"}}, "target": "clipseq", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_0_13", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_fastq_align_dedup_bwameth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate (tools: fastq_align_dedup_bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "fastq_align_dedup_bwameth": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate", "bwameth_index": "Performs indexing of c2t converted reference genome", "hpsuissero": "Serotype prediction of Haemophilus parasuis assemblies", "plink_gwas": "Generate GWAS association studies"}}, "target": "fastq_align_dedup_bwameth", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wes_pe_5_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Paired-end Whole Exome Sequencing (WES) target capture.", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_27", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_arcane_filter_4", "category": "resource_profiling", "state": {"process": "ARCANE_FILTER", "tool": "arcane/filter", "description": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARCANE_FILTER (Filter GTF annotations and genome sequence for alignment-free single-cell RNA-se) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_expansionhunterdenovo_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge STR profiles into a multi-sample STR profile (tools: expansionhunterdenovo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo/merge": "Merge STR profiles into a multi-sample STR profile", "shinyngs/validatefomcomponents": "validate consistency of feature and sample annotations with matrices and contrasts", "krona/ktimportkrona": "Collect multiple krona reports into a single html file", "biobambam/bammerge": "Merge a list of sorted bam files", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "expansionhunterdenovo/merge", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_40", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_annotsv_annotsv_0", "category": "resource_profiling", "state": {"process": "ANNOTSV_ANNOTSV", "tool": "annotsv/annotsv", "description": "Annotation and Ranking of Structural Variation"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_ANNOTSV (Annotation and Ranking of Structural Variation) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_kmermaid_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: k-mer similarity analysis pipeline. Topics: k-mer, kmer, kmer-counting, kmer-frequency-count. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": null, "longraredisease": null, "nanoseq": null, "hadge": null, "stableexpression": null, "viralrecon": null, "mnaseseq": null, "variantbenchmarking": null}}, "target": "kmermaid", "target_idx": 0}
{"id": "field_constraint_bai_1_7", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "noul_container_environment_specification_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_blast_blastn_4", "category": "resource_profiling", "state": {"process": "BLAST_BLASTN", "tool": "blast/blastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_channel_factory_inside_process_body_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (custom/mira-nf) for Custom MIRA-NF Influenza / SC2 pipeline. Input files: Paired-end surveillance FASTQs from respiratory pathogen panels.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Custom MIRA-NF Influenza / SC2 pipeline with entry step INPUT_CHECK.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_1_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "mod_ampcombi2_parsetables_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A submodule that parses and standardizes the results from various antimicrobial peptide identification tools. (tools: ampcombi2/parsetables)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastawindows": "Quickly compute statistics over a fasta file in windows.", "amplify/predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "ampcombi2/parsetables", "target_idx": 3}
{"id": "samplesheet_arch_metagenome_mag_grouped_0_2", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_bedgovcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a BED file to a VCF file according to a YAML config (tools: bedgovcf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/mergesamfiles": null, "agat/convertgff2bed": null, "bedops/convert2bed": null, "fasta_hmmsearch_rank_fastas": null, "bedgovcf": null}}, "target": "bedgovcf", "target_idx": 4}
{"id": "samplesheet_arch_rare_disease_trio_4_2", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs with pedigree relationships and affected status?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_stainwarpy_extractchannel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract a single channel image from multiplexed tissue images using stainwarpy (tools: stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "pharokka/pharokka": "Functional annotation of phages", "tif_registration_stainwarpy": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy", "stainwarpy/extractchannel": "Extract a single channel image from multiplexed tissue images using stainwarpy", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration"}}, "target": "stainwarpy/extractchannel", "target_idx": 3}
{"id": "mod_gt_ltrharvest_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts LTR retrotransposons using GenomeTools gt-ltrharvest utility (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": null, "alignoth": null, "agat_sqstatbasic": null, "gt_ltrharvest": null, "paftools_sam2paf": null}}, "target": "gt_ltrharvest", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_23", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_amulety_balmpaired_4", "category": "resource_profiling", "state": {"process": "AMULETY_BALMPAIRED", "tool": "amulety/balmpaired", "description": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_BALMPAIRED (A module to create BALM paired embeddings of antibody (BCR) amino acid sequences) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedgovcf_2", "category": "resource_profiling", "state": {"process": "BEDGOVCF", "tool": "bedgovcf", "description": "Convert a BED file to a VCF file according to a YAML config"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDGOVCF (Convert a BED file to a VCF file according to a YAML config) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_references_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for genome. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]"}}, "target": "references", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_shortreads_preprocess_qc_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SHORTREADS_PREPROCESS_QC", "modules": ["fastq_qc_stats", "fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp", "fastq_preprocess_seqkit", "fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup", "umitools/extract", "fastq_removeadapters_merge", "trimmomatic", "cutadapt", "trimgalore", "bbmap/bbduk", "leehom", "fastp", "adapterremoval", "cat/fastq", "fastq_complexity_filter", "prinseqplusplus", "bbmap/clumpify", "fastq_decontaminate_deacon_hostile", "fastq_index_filter_deacon", "fastq_fetch_clean_hostile", "hostile/fetch", "hostile/clean", "bowtie2/build", "deacon/filter", "deacon/index"], "description": "Quality check and preprocessing subworkflow of Illumina short reads"}, "question": {"type": "choice", "instructions": "How should FASTQ_SHORTREADS_PREPROCESS_QC (fastq_qc_stats, fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp, fastq_preprocess_seqkit, fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup, umitools/extract, fastq_removeadapters_merge, trimmomatic, cutadapt, trimgalore, bbmap/bbduk, leehom, fastp, adapterremoval, cat/fastq, fastq_complexity_filter, prinseqplusplus, bbmap/clumpify, fastq_decontaminate_deacon_hostile, fastq_index_filter_deacon, fastq_fetch_clean_hostile, hostile/fetch, hostile/clean, bowtie2/build, deacon/filter, deacon/index) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_SHORTREADS_PREPROCESS_QC": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_shortreads_preprocess_qc": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_shortreads_preprocess_qc", "target_idx": 2}
{"id": "mod_bbmap_bbnorm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result in a flat coverage distribution. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt/normalize": null, "bam_methyldackel": null, "deeptools/bamcompare": null, "cobs/classicconstruct": null, "bbmap/bbnorm": null}}, "target": "bbmap/bbnorm", "target_idx": 4}
{"id": "samplesheet_arch_germline_lane_split_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Multi-lane Illumina sequencing run of clinical samples", "data_format": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_10", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_gem2_gem2bedmappability_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a mappability file to bedgraph format (tools: gem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"miniprot/align": null, "gem3/gem3indexer": null, "genmap/index": null, "gem2/gem2bedmappability": null, "pairtools/restrict": null}}, "target": "gem2/gem2bedmappability", "target_idx": 3}
{"id": "mod_custom_orfmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `custom/orfnormalise` upstream and\n(typically) `bedtools/getfasta` + `seqkit/translate` downstream to obtain\nthe AA FASTA.\n\nRows sharing an identical exon structure are grouped first and clustered as a\nsingle proxy chosen by class specificity, then the members are restored. Class\nselects the strategy, so without this an ORF that two callers class differently\nwould be split across strategies and could never merge.\n\nProxies are then partitioned by clustering strategy. The harmonised `orf_class`\nwritten by `custom/orfnormalise` selects the strategy but is never part of a\ngrouping key, because callers disagree on class for the same ORF (Ribo-TISH\nreports `5'UTR` for both uORFs and CDS-overlapping uORFs) and keying on it\nwould emit one catalogue row per disagreeing caller:\n\n  - canonical_cds:        grouped by (transcript_id, strand), then\n                          reciprocal-overlap clustered within the\n                          transcript so a short truncated variant is\n                          not folded into the full-length CDS.\n  - uORF, uoORF, dORF,    collapse by (transcript_id, strand, start,\n    doORF, intORF, other: end). A single transcript can host multiple\n                          distinct uORFs / dORFs / internal ORFs, so\n                          keying on the outer span keeps them in\n                          separate clusters while still merging\n                          cross-caller calls that agree on coordinates.\n  - novel_u:              greedy reciprocal-overlap clustering on summed\n                          exon-block intersection at `--reciprocal-overlap`\n                          (default 0.8). Catches fuzzy cross-caller\n                          matches and exact-coordinate collapses in\n                          one pass. Order-dependent at the boundary:\n                          a chain A-B-C where A-B and B-C overlap at\n                          ~0.85 but A-C only at ~0.75 may cluster as\n                          {A,B,C} or {A,B}+{C} depending on iteration\n                          order. Rare in practice at 0.8.\n\nCross-caller consensus is recorded in two column families on the\ncatalogue TSV:\n\n  - `called_by_<caller>`: 0/1 indicator per supported caller\n                          (ribotish, ribocode, ribotricer, rpbp, price).\n  - `score_<caller>`:     best score from that caller within the cluster.\n                          Score direction is per-caller (p-values are\n                          minimised; Bayes factors / phase scores are\n                          maximised).\n\nCross-sample recurrence is recorded in two further columns:\n\n  - `n_samples`:          number of distinct samples contributing to the\n                          cluster (a cohort recurrence metric).\n  - `samples`:            sorted, comma-separated list of those sample ids.\n\nEmits a small MultiQC custom-content TSV (per-class counts) for\ninclusion in downstream MultiQC reports.\n\nAlongside the full catalogue, emits a consensus view (`*.consensus.*`)\nfiltered to ORFs supported by at least `--min-callers` distinct callers\nand recurring in at least `--min-samples` samples (both default 1, i.e.\nno filtering, so the consensus view equals the full catalogue). Raising\neither threshold yields a higher-confidence catalogue without altering\nthe full one. (tools: orfmerge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/orfmerge": null, "mykrobe/predict": null, "dotseq/dotseq": null, "portello": null, "gedi/indexgenome": null}}, "target": "custom/orfmerge", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: Fungal ITS1/ITS2 marker gene amplicon surveillance)", "question": {"type": "choice", "instructions": "Which columns are standard for Fungal ITS1/ITS2 marker gene amplicon surveillance input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_hic_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for chromosome-conformation-capture. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "hic", "target_idx": 7}
{"id": "samplesheet_arch_bulk_small_rna_4_2", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end 50bp miRNA reads with 3-prime adapter?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,mirna_id": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "pipe_all101_proteogenomicsdb_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for cosmic. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u"}}, "target": "proteogenomicsdb", "target_idx": 3}
{"id": "resource_bedtools_split_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SPLIT", "tool": "bedtools/split", "description": "Split BED files into several smaller BED files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SPLIT (Split BED files into several smaller BED files) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_crabs_insilicopcr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CRABS extracts the amplicon region of the primer set by conducting an in silico PCR. (tools: crabs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/markduplicates": "Locate and tag duplicate reads in a BAM file", "artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "plink2/score": "Apply a scoring system to each sample in a plink 2 fileset", "yahs": "Performs assembly scaffolding using YaHS", "crabs/insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR."}}, "target": "crabs/insilicopcr", "target_idx": 4}
{"id": "schema_std_genomeqc_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeqc", "description": "Compare the quality of multiple genomes, along with their annotations.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/genomeqc?", "criteria": {"sample,fastq_1,fastq_2,strandedness,seq_platform": null, "id,raw_file": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null}}, "target": "fasta,assembly,ncbi,gff,fastq", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral amplicon sequencing with primers. Input files: Paired-end tiled viral amplicon FASTQs per clinical swab sample.", "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_kmermaid_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for k-mer. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]"}}, "target": "kmermaid", "target_idx": 3}
{"id": "resource_biscuit_mergecg_5", "category": "resource_profiling", "state": {"process": "BISCUIT_MERGECG", "tool": "biscuit/mergecg", "description": "Merges methylation information for opposite-strand C's in a CpG context"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_MERGECG (Merges methylation information for opposite-strand C's in a CpG context) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_47", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_0_39", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "schema_std_genephylomodeler_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genephylomodeler", "description": "A bioinformatics pipeline that fits evolutionary models and detects natural selection from multiple sequence alignments", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/genephylomodeler?", "criteria": {"gene_name,alignment,tree,suite,tool": null, "sample,fastq_1,fastq_2,genome": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "gene_name,alignment,tree,suite,tool", "target_idx": 0}
{"id": "mod_eagle2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform phasing of genotyped data with or without a reference panel (tools: eagle2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eagle2": "Perform phasing of genotyped data with or without a reference panel", "plink2/score": "Apply a scoring system to each sample in a plink 2 fileset", "shapeit5/phasecommon": "Tool to phase common sites, typically SNP array data, or the first step of WES/WGS data.", "mykrobe/predict": "AMR predictions for supported species", "beagle5/beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers."}}, "target": "eagle2", "target_idx": 0}
{"id": "resource_autocycler_resolve_3", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_RESOLVE", "tool": "autocycler/resolve", "description": "Resolve trimmed assembly graphs into final contigs within Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_RESOLVE (Resolve trimmed assembly graphs into final contigs within Autocycler.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_expansionhunterdenovo_profile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute genome-wide STR profile (tools: expansionhunterdenovo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"expansionhunterdenovo_merge": "Merge STR profiles into a multi-sample STR profile", "expansionhunterdenovo_profile": "Compute genome-wide STR profile", "regtools_junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.", "hmmer_hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile", "plink_exclude": "Exclude variant identifiers from plink bfiles"}}, "target": "expansionhunterdenovo_profile", "target_idx": 1}
{"id": "resource_bbmap_align_5", "category": "resource_profiling", "state": {"process": "BBMAP_ALIGN", "tool": "bbmap/align", "description": "Align short or PacBio reads to a reference genome using BBMap"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_ALIGN (Align short or PacBio reads to a reference genome using BBMap) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_1_5", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "template": "nf-core/rnafusion"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "mod_htodemux_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex samples based on data from cell hashing. (tools: htodemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "htodemux": "Demultiplex samples based on data from cell hashing.", "diann/insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "hasheddrops": "Generating cell hashing calls from a matrix of count data.", "ldak/thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne"}}, "target": "htodemux", "target_idx": 1}
{"id": "noul_channel_join_operator_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_cramino_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality assessment of long-read bam files using cramino. (tools: cramino)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem3_gem3indexer": "Create a GEM index from a FASTA file", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "hmmer_hmmrank": "R script that scores output from multiple runs of hmmer/hmmsearch", "cramino": "Quality assessment of long-read bam files using cramino."}}, "target": "cramino", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_se_4_0", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end FASTQ reads per library?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "schema_std_longraredisease_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/longraredisease", "description": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/longraredisease?", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "family_id,sample,file_path,hpo_terms,sex": null, "sample,bundle,image": null, "vcf,fasta,genome,site,source": null}}, "target": "family_id,sample,file_path,hpo_terms,sex", "target_idx": 1}
{"id": "mod_fasta_index_bismark_bwameth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate index files from reference fasta for bismark and bwameth (tools: fasta_index_bismark_bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools_prepareforrsem": "Make the output from umi_tools dedup or group compatible with RSEM", "bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "bbmap_bbnorm": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result i", "fasta_index_bismark_bwameth": "Generate index files from reference fasta for bismark and bwameth", "bismark_align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "fasta_index_bismark_bwameth", "target_idx": 3}
{"id": "local_subworkflow_daisribosome_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should this step (dais) be packaged: Custom ribosomal frameshift translation analysis?", "criteria": {"Local subworkflow DAISRIBOSOME": null, "Use nf-core subworkflow daisribosome": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 0}
{"id": "mod_cpc2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Coding Potential Calculator 2 (tools: cpc2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genomad_endtoend": "Identify mobile genetic elements present in genomic assemblies", "genrich": "Peak-calling for ChIP-seq and ATAC-seq enrichment experiments", "cpc2": "Coding Potential Calculator 2", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "cpc2", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_4_1", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Combinatorial split-pool barcoded FASTQs with subpool annotations?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,well,plate": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_bam_markduplicates_samtools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_SAMTOOLS", "modules": ["samtools/collate", "samtools/fixmate", "samtools/sort", "samtools/markdup"], "description": "Samtools markduplicate SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_SAMTOOLS (samtools/collate, samtools/fixmate, samtools/sort, samtools/markdup) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow bam_markduplicates_samtools": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_MARKDUPLICATES_SAMTOOLS": null}}, "target": "Use nf-core subworkflow bam_markduplicates_samtools", "target_idx": 1}
{"id": "mod_stare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Framework that scores enhancer–gene interactions using the Activity-By-Contact model and derives transcription factor affinities on gene level (tools: stare)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "stare": "Framework that scores enhancer–gene interactions using the Activity-By-Contact model and derives transcription", "alignoth": "Creating alignment plots from bam files", "gatk4/variantstotable": "Extract fields from a VCF file to a tab-delimited table", "hasheddrops": "Generating cell hashing calls from a matrix of count data."}}, "target": "stare", "target_idx": 1}
{"id": "mod_tidk_explore_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: `tidk explore` attempts to find the simple telomeric repeat unit in the genome provided.\nIt will report this repeat in its canonical form (e.g. TTAGG -> AACCT). (tools: tidk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/align": null, "vcf_filter_bcftools_ensemblvep": null, "tidk/explore": null, "agat/spflagshortintrons": null, "agat/spextractsequences": null}}, "target": "tidk/explore", "target_idx": 2}
{"id": "mod_shovill_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble bacterial isolate genomes from Illumina paired-end reads (tools: shovill)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate_run": null, "minibwa_map": null, "abricate_summary": null, "gtdbtk_gtdbtoncbimajorityvote": null, "shovill": null}}, "target": "shovill", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_align_bwaaln_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BWAALN", "modules": ["bwa/aln", "bwa/sampe", "bwa/samse", "samtools/index"], "description": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed BAM files"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BWAALN (bwa/aln, bwa/sampe, bwa/samse, samtools/index) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_align_bwaaln": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_BWAALN": null}}, "target": "Use nf-core subworkflow fastq_align_bwaaln", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_34", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bracken_combinebrackenoutputs_3", "category": "resource_profiling", "state": {"process": "BRACKEN_COMBINEBRACKENOUTPUTS", "tool": "bracken/combinebrackenoutputs", "description": "Combine output of metagenomic samples analyzed by bracken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_COMBINEBRACKENOUTPUTS (Combine output of metagenomic samples analyzed by bracken.) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_beagle5_beagle_3", "category": "resource_profiling", "state": {"process": "BEAGLE5_BEAGLE", "tool": "beagle5/beagle", "description": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEAGLE5_BEAGLE (Beagle v5.5 is a software package for phasing genotypes and for imputing ungenot) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_amulety_antiberta2_0", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTA2", "tool": "amulety/antiberta2", "description": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTA2 (A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_19", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq. Input files: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq.", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_localcdsearch_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A command-line tool for downloading databases for local protein domain annotation using NCBI's Conserved Domain Database (CDD) (tools: localcdsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"localcdsearch_download": "A command-line tool for downloading databases for local protein domain annotation using NCBI's Conserved Domai", "cdhit_cdhit": "Cluster protein sequences using sequence similarity", "bcftools_csq": "bcftools Haplotype-aware consequence caller", "cleanifier_filter": "Fast, lightweight contamination removal from microbiome data (FASTQ) using a probabilistic Cuckoo filter or Cu", "vcf_impute_minimac4": "Subworkflow to impute VCF files using MINIMAC4 software. The subworkflow\ntakes VCF files, phased reference pan"}}, "target": "localcdsearch_download", "target_idx": 0}
{"id": "resource_ampcombi2_complete_1", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_COMPLETE", "tool": "ampcombi2/complete", "description": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_COMPLETE (A submodule that merges all output summary tables from ampcombi/parsetables in o) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_vuegen_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The VueGen nf-core module is designed to automate report generation from outputs produced by other modules, subworkflows, or pipelines. The module integrates the VueGen Python library and customizes it for compatibility with the Nextflow environment. VueGen automates the creation of reports from bioinformatics outputs, supporting formats like PDF, HTML, DOCX, ODT, PPTX, Reveal.js, Jupyter notebooks, and Streamlit web applications. (tools: vuegen)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_index_filter_deacon": null, "foldcomp_compress": null, "rmarkdownnotebook": null, "quartonotebook": null, "vuegen": null}}, "target": "vuegen", "target_idx": 4}
{"id": "mod_odgi_stats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metrics describing a variation graph and its path relationship. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_qc_rnaseq": null, "gfaffix": null, "odgi/draw": null, "anndata/getsize": null, "odgi/stats": null}}, "target": "odgi/stats", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_1_34", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_33", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_16", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_49", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_25", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_23", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_se_4_4", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end FASTQ reads per library?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_bwamem3_mem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align fastq reads to a fasta reference using bwa-mem3 (tools: bwamem3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem3/mem": null, "ariba/getref": null, "picard/fixmateinformation": null, "bwa/mem": null, "bwafastalign/mem": null}}, "target": "bwamem3/mem", "target_idx": 0}
{"id": "subworkflow_pkg_deepvariant_3", "category": "subworkflow_packaging", "state": {"subworkflow": "DEEPVARIANT", "modules": ["deepvariant/makeexamples", "deepvariant/callvariants", "deepvariant/postprocessvariants"], "description": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data"}, "question": {"type": "choice", "instructions": "How should DEEPVARIANT (deepvariant/makeexamples, deepvariant/callvariants, deepvariant/postprocessvariants) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow deepvariant": null, "Local subworkflow DEEPVARIANT": null}}, "target": "Use nf-core subworkflow deepvariant", "target_idx": 2}
{"id": "mod_clustalo_guidetree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Renders a guidetree in clustalo (tools: clustalo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "clustalo_guidetree": "Renders a guidetree in clustalo", "cellranger_vdj": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Immune Profil", "famsa_guidetree": "Renders a guidetree in famsa", "mafft_guidetree": "Guide tree rendering using MAFFT"}}, "target": "clustalo_guidetree", "target_idx": 1}
{"id": "pipe_all101_fastqrepair_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, and settles reads that became disordered. Topics: corruption, data-cleaning, data-recovery, fastq, fastq-corrupted, fastq-format. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis"}}, "target": "fastqrepair", "target_idx": 1}
{"id": "resource_amps_4", "category": "resource_profiling", "state": {"process": "AMPS", "tool": "amps", "description": "Post-processing script of the MaltExtract component of the HOPS package"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPS (Post-processing script of the MaltExtract component of the HOPS package) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_rgi_main_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict antibiotic resistance from protein or nucleotide data (tools: rgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_preprocess_seqkit": null, "amulety/translate": null, "antismash/antismash": null, "rgi/main": null, "amrfinderplus/run": null}}, "target": "rgi/main", "target_idx": 3}
{"id": "resource_bcftools_csq_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CSQ", "tool": "bcftools/csq", "description": "bcftools Haplotype-aware consequence caller"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CSQ (bcftools Haplotype-aware consequence caller) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_repeatmasker_repeatmasker_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Screening DNA sequences for interspersed repeats and low complexity DNA sequences (tools: repeatmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trgt_plot": "Visualize tandem repeats genotyped by TRGT", "agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "repeatmasker_repeatmasker": "Screening DNA sequences for interspersed repeats and low complexity DNA sequences", "abacas": "Contiguate draft genome assembly", "jvarkit_vcf2table": "Convert VCF to a user friendly table"}}, "target": "repeatmasker_repeatmasker", "target_idx": 2}
{"id": "pipe_all101_oncoanalyser_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A comprehensive cancer DNA/RNA analysis and reporting pipeline. Topics: cancer, clinical, ctdna, dna, exome, longitudinal. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mcmicro": null, "oncoanalyser": null, "proteogenomicsdb": null, "dualrnaseq": null, "methylseq": null}}, "target": "oncoanalyser", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_44", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_0_2", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_taxprofiler_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data. Topics: classification, illumina, long-reads, metagenomics, microbiome, nanopore. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]"}}, "target": "taxprofiler", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/riboseq --input samplesheet.csv (Assay: Ribosome profiling (Ribo-seq) footprint sequencing)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/riboseq, determine the input samplesheet column structure for: Ribosome profiling (Ribo-seq) footprint sequencing.", "criteria": {"sample,bam": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "resource_bio2zarr_vcfpartition_0", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCFPARTITION", "tool": "bio2zarr/vcfpartition", "description": "Outputs a set of region strings that partition indexed VCF/BCF files for parallel processing."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCFPARTITION (Outputs a set of region strings that partition indexed VCF/BCF files for paralle) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_snpdists_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pairwise SNP distance matrix from a FASTA sequence alignment (tools: snpdists)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpdists": "Pairwise SNP distance matrix from a FASTA sequence alignment", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "shigapass": "ShigaPass is an in silico tool used to predict Shigella serotypes and to differentiate between Shigella, EIEC ", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "eigenstratdatabasetools/eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset."}}, "target": "snpdists", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_48", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bismark_deduplicate_5", "category": "resource_profiling", "state": {"process": "BISMARK_DEDUPLICATE", "tool": "bismark/deduplicate", "description": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_DEDUPLICATE (Removes alignments to the same position in the genome\nfrom the Bismark mapping o) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_2_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "noul_retry_errorstrategy_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_executor_support_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_process_conditional_execution_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_gem2_gemindexer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a GEM index from a FASTA file (tools: gem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem2_gemindexer": "Create a GEM index from a FASTA file", "cooler_cload": "Create a cooler from genomic pairs and bins", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\"."}}, "target": "gem2_gemindexer", "target_idx": 0}
{"id": "schema_std_abotyper_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/abotyper", "assay": "abotyper pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/abotyper (A pipeline for characterising the Human Blood Group and Red )?", "criteria": {"sample,sample_id,fastq_1,fastq_2,method": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_6_0", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "mod_hicexplorer_hicpca_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes PCA eigenvectors for a Hi-C matrix. (tools: hicexplorer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "shinyngs/staticexploratory": "Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots", "rhocall/viz": "Call regions of homozygosity and make tentative UPD calls", "hicexplorer/hicpca": "Computes PCA eigenvectors for a Hi-C matrix.", "kofamscan": "Produces annotation using kofamscan against a Profile database and a KO list"}}, "target": "hicexplorer/hicpca", "target_idx": 3}
{"id": "samplesheet_arch_rare_disease_trio_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Trio exome/genome sequencing (Proband, Mother, Father))", "question": {"type": "choice", "instructions": "Which columns are standard for Trio exome/genome sequencing (Proband, Mother, Father) input samplesheet?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_mirtop_counts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop counts generates a file with the minimal information about each sequence and the count data in columns for each samples. (tools: mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_missing": "Compute sample-based and variant-based missing genotype rates and write a new PLINK binary fileset", "mirtop_counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns ", "miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "picard_collectrnaseqmetrics": "Collect metrics from a RNAseq BAM file", "mirtop_stats": "mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category."}}, "target": "mirtop_counts", "target_idx": 1}
{"id": "schema_std_rnadnavar_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnadnavar", "assay": "rnadnavar pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/rnadnavar (Pipeline for RNA and DNA integrated analysis for somatic mut)?", "criteria": {"gene_name,alignment,tree,suite,tool": null, "sample_id,mapped,index,file_type": null, "sample,tools,file,index": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 3}
{"id": "resource_anota2seq_anota2seqrun_3", "category": "resource_profiling", "state": {"process": "ANOTA2SEQ_ANOTA2SEQRUN", "tool": "anota2seq/anota2seqrun", "description": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANOTA2SEQ_ANOTA2SEQRUN (Generally applicable transcriptome-wide analysis of translational efficiency usi) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_expected_cells_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_contam_seqtk_kraken_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_CONTAM_SEQTK_KRAKEN", "modules": ["kraken2/kraken2", "seqtk/sample"], "description": "Produces a contamination report from FastQ input after subsampling"}, "question": {"type": "choice", "instructions": "How should FASTQ_CONTAM_SEQTK_KRAKEN (kraken2/kraken2, seqtk/sample) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_CONTAM_SEQTK_KRAKEN": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_contam_seqtk_kraken": null}}, "target": "Use nf-core subworkflow fastq_contam_seqtk_kraken", "target_idx": 3}
{"id": "mod_bedtools_complement_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"upp/align": "Aligns protein structures using UPP", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "deepbgc/pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.", "bedtools/complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}}, "target": "bedtools/complement", "target_idx": 4}
{"id": "mod_stringtie_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges the annotation gtf file and the stringtie output gtf files (tools: stringtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bammerge": "Merge a list of sorted bam files", "stringtie_merge": "Merges the annotation gtf file and the stringtie output gtf files", "krona_ktimportkrona": "Collect multiple krona reports into a single html file", "shapeit5_ligate": "Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chu", "concoct_extractfastabins": "Creates a FASTA file for each new cluster assigned by CONCOCT"}}, "target": "stringtie_merge", "target_idx": 1}
{"id": "mod_tabix_tabix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file, or extract regions from a bgzipped VCF file\nusing an optional regions file. (tools: tabix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie/build": "Create bowtie index for reference genome", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "finaletoolkit/wps": "Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription", "tabix/tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,", "bamutil/trimbam": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping"}}, "target": "tabix/tabix", "target_idx": 3}
{"id": "schema_std_hlatyping_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/hlatyping. Description: Precision HLA typing from next-generation sequencing data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/hlatyping.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "sample,fastq_1,fastq_2,replicate,control": null}}, "target": "sample,fastq_1,fastq_2,bam,seq_type", "target_idx": 2}
{"id": "mod_transdecoder_longorf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TransDecoder identifies candidate coding regions within transcript sequences. it is used to build gff file. (tools: transdecoder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "ucsc_bigwigaverageoverbed": "compute average score of bigwig over bed file", "agat_spaddintrons": "Add intron features to gtf/gff file without intron features.", "transdecoder_longorf": "TransDecoder identifies candidate coding regions within transcript sequences. it is used to build gff file.", "angsd_gl": "Calculated genotype likelihoods from BAM files."}}, "target": "transdecoder_longorf", "target_idx": 3}
{"id": "mod_bcftools_pluginfixploidy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes. (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio_splitgff3": "Split features in gzipped GFF3 format", "macs3_callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "bcftools_concat": "Concatenate VCF files", "bcftools_pluginfixploidy": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignmen", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "bcftools_pluginfixploidy", "target_idx": 3}
{"id": "mod_rsem_preparereference_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare a reference genome for RSEM (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rsem/preparereference": "Prepare a reference genome for RSEM", "untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives", "custom/rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices", "genmod/compound": "Score compounds", "sentieon/rsemcalculateexpression": "Calculate expression with RSEM"}}, "target": "rsem/preparereference", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_16", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_atlas_call_3", "category": "resource_profiling", "state": {"process": "ATLAS_CALL", "tool": "atlas/call", "description": "generate VCF file from a BAM file using various calling methods"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_CALL (generate VCF file from a BAM file using various calling methods) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "core_tool_macs2_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Model-based analysis of ChIP-Seq data to identify statistically significant transcription factor binding sites and histone mark enrichment peaks.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"seacr": null, "macs2": null, "genrich": null, "homer": null, "epic2": null}}, "target": "macs2", "target_idx": 1}
{"id": "pipe_all101_methylong_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for dna-methylation analysis? Specific context: Extract methylation calls from long reads (ONT/ PacBio). Topics: dna-methylation, fiber-seq, long-read, ont, pacbio. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. "}}, "target": "methylong", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_2_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_index_dna_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_DNA", "modules": ["bowtie2/build", "bwa/index", "bwamem2/index", "dragmap/hashtable", "snapaligner/index"], "description": "Generate aligner index for a reference genome."}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_DNA (bowtie2/build, bwa/index, bwamem2/index, dragmap/hashtable, snapaligner/index) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_INDEX_DNA": null, "Use nf-core subworkflow fasta_index_dna": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_index_dna", "target_idx": 1}
{"id": "mod_strvctvre_strvctvre_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a structural variant classifier for exonic deletions and duplications (tools: strvctvre)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": null, "optitype": null, "strvctvre/strvctvre": null, "caddsv/run": null, "genotyphi/parse": null}}, "target": "strvctvre/strvctvre", "target_idx": 2}
{"id": "pipe_all101_funcprofiler_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for funcprofiler analysis? Specific context: Read-based functional profiling of microbiome sequencing data. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]"}}, "target": "funcprofiler", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "ATAC-seq chromatin accessibility with biological replicates", "data_format": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bed": null, "sample,bam": null, "sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "pipe_all101_hic_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis of Chromosome Conformation Capture data (Hi-C). Topics: chromosome-conformation-capture, hi-c. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"circdna": null, "eager": null, "demultiplex": null, "hic": null, "viralrecon": null}}, "target": "hic", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_4_3", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "template": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Serial plasma cfDNA and biopsy FASTQs across treatment intervals?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/chipseq", "assay_type": "ChIP-seq with IP and input control design", "data_format": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_1_4", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_cnvpytor_importreaddepth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file. (tools: cnvpytor -rd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasttree": "Produces a Newick format phylogeny from a multiple sequence alignment. Capable of bacterial genome size alignm", "varlociraptor_callvariants": "Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlocira", "cnvpytor_importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file.", "cnvpytor_histogram": "calculates read depth histograms", "canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed"}}, "target": "cnvpytor_importreaddepth", "target_idx": 2}
{"id": "mod_samtools_bedcov_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: reports coverage over regions in a supplied BED file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools_bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig ", "samtools_collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma", "samtools_depth": "Computes the depth at each position or region.", "samtools_bedcov": "reports coverage over regions in a supplied BED file", "angsd_gl": "Calculated genotype likelihoods from BAM files."}}, "target": "samtools_bedcov", "target_idx": 3}
{"id": "core_tool_featurecounts_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Assign and quantify mapped reads to genomic features such as exons, genes, and promoter annotations from sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"stringtie": "Transcript assembly", "salmon": "Transcript quantifier", "htseq": "High-throughput sequencing analysis", "kallisto": "RNA quantification", "featurecounts": "Assign sequence reads to genomic features (genes, exons, promoters)"}}, "target": "featurecounts", "target_idx": 4}
{"id": "samplesheet_arch_faire_seq_chromatin_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "FAIRE-seq / DNAse-seq open chromatin profiling", "data_format": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for FAIRE-seq / DNAse-seq open chromatin profiling input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,bed": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bwa_samse_3", "category": "resource_profiling", "state": {"process": "BWA_SAMSE", "tool": "bwa/samse", "description": "Convert bwa SA coordinate file to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMSE (Convert bwa SA coordinate file to SAM format) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_high", "target_idx": 1}
{"id": "subworkflow_pkg_orftable_fasta_gtf_buildorfcatalogue_3", "category": "subworkflow_packaging", "state": {"subworkflow": "ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE", "modules": ["custom/orfnormalise", "custom/orfmerge", "bedtools/getfasta", "seqkit/translate", "mmseqs/easycluster", "custom/orfcollapse"], "description": "Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller"}, "question": {"type": "choice", "instructions": "How should ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE (custom/orfnormalise, custom/orfmerge, bedtools/getfasta, seqkit/translate, mmseqs/easycluster, custom/orfcollapse) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue": null, "Local subworkflow ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE": null, "Leave them out": null}}, "target": "Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue", "target_idx": 1}
{"id": "mod_rseqc_readduplication_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate read duplication rate (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc/readduplication": null, "skesa": null, "gatk/realignertargetcreator": null, "anota2seq/anota2seqrun": null, "ctatsplicing/startocancerintrons": null}}, "target": "rseqc/readduplication", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_5_3", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: 10x Multiome single-cell joint RNA and ATAC chromatin.", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,bam": null, "sample,matrix": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "mod_scanpy_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter cells and genes in single-cell RNA-seq data using Scanpy (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scanpy/filter": "Filter cells and genes in single-cell RNA-seq data using Scanpy", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "suppa/clusterevents": "Cluster events based on PSI values and significantly differentially spliced events using SUPPA2.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "controlfreec/makegraph": "Plot Freec output"}}, "target": "scanpy/filter", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/cutandrun --input samplesheet.csv (Assay: CUT&RUN / CUT&TAG chromatin profiling with IgG control)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "schema_std_eager_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/eager. Description: A fully reproducible and state-of-the-art ancient DNA analysis pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/eager.", "criteria": {"sample,fastq_1,fastq_2,bam,cram": null, "sample_id,bam,vcf,library_id,lane": null, "sample,bundle,image": null, "gene_name,alignment,tree,suite,tool": null}}, "target": "sample_id,bam,vcf,library_id,lane", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_2", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_all101_viralintegration_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for chimeric-alignment analysis? Specific context: Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach.. Topics: chimeric-alignment, ctat, viral-integration, virus, virusintegrationfinder. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data."}}, "target": "viralintegration", "target_idx": 4}
{"id": "mod_gatk4_baserecalibrator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate recalibration table for Base Quality Score Recalibration (BQSR) (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/baserecalibrator": null, "fairy/coverage": null, "gatk4/gatherbqsrreports": null, "parabricks/applybqsr": null, "hackgap/count": null}}, "target": "gatk4/baserecalibrator", "target_idx": 0}
{"id": "mod_arriba_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data. (tools: arriba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba_download": null, "fusioninspector": null, "ea-utils_gtf2bed": null, "arriba_arriba": null, "gatk4_sitedepthtobaf": null}}, "target": "arriba_download", "target_idx": 0}
{"id": "schema_std_bacass_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "assay": "bacass pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/bacass (Simple bacterial assembly and annotation pipeline)?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam,pbi,fail,repeat_id": null, "sample_id,mapped,index,file_type": null, "ID,R1,R2,LongFastQ,Fast5": null}}, "target": "ID,R1,R2,LongFastQ,Fast5", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_2_0", "category": "samplesheet_schema", "state": {"technology": "Ancient DNA", "workflow_entry": "FASTQC", "library_inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_parabricks_haplotypecaller_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating GATK haplotypecaller. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk/plot": null, "graphtyper/genotype": null, "igvreports": null, "parabricks/haplotypecaller": null, "grabix/check": null}}, "target": "parabricks/haplotypecaller", "target_idx": 3}
{"id": "resource_blobtk_depth_0", "category": "resource_profiling", "state": {"process": "BLOBTK_DEPTH", "tool": "blobtk/depth", "description": "Creates a bed file containing the depth of data at intervals of an aligned bam."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_DEPTH (Creates a bed file containing the depth of data at intervals of an aligned bam.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_hmmcopy_readcounter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: readCounter function from HMMcopy utilities, used to generate read in windows (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples).", "samtools/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "last/postmask": "Post-alignment masking", "hmmcopy/readcounter": "readCounter function from HMMcopy utilities, used to generate read in windows"}}, "target": "hmmcopy/readcounter", "target_idx": 4}
{"id": "resource_bioformats2raw_1", "category": "resource_profiling", "state": {"process": "BIOFORMATS2RAW", "tool": "bioformats2raw", "description": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOFORMATS2RAW (Java application to convert image file formats, including .mrxs, to an intermedi) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "core_tool_mutect2_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Somatic short variant detection (SNVs and small indels) comparing matched tumor and normal sequencing data with Bayesian somatic likelihood filtering.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"varscan2": "Somatic caller", "somaticsniper": "Somatic SNV caller", "mutect2": "Call somatic SNVs and indels via local assembly of haplotypes with tumor/normal comparison", "strelka2": "Fast somatic caller", "vardict": "Variant caller"}}, "target": "mutect2", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_7_1", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_20", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "schema_std_proteinannotator_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/proteinannotator. Description: Generation of sequence-level annotations for amino acid sequences.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/proteinannotator.", "criteria": {"id,fasta": null, "sample,type,level,msfile": null, "sample,fastq_1,fastq_2,batch,condition": null, "sample,id,data_path,fastq_dir,cytaimage": null}}, "target": "id,fasta", "target_idx": 0}
{"id": "mod_bam_markduplicates_samtools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Samtools markduplicate SAM/BAM/CRAM file (tools: bam_markduplicates_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_markduplicates_samtools": "Samtools markduplicate SAM/BAM/CRAM file", "sourmash_pairwise": "Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch.", "gatk4spark_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "pbmarkdup": "Takes one or multiple sequencing chips of an amplified library as HiFi reads and marks or removes\nduplicates."}}, "target": "bam_markduplicates_samtools", "target_idx": 0}
{"id": "noul_process_conditional_execution_0", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `when:` directive in a process controls conditional execution based on workflow parameters.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_nacho_normalize_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter data is a messenger-RNA/micro-RNA (mRNA/miRNA) expression assay and works with fluorescent barcodes.\nEach barcode is assigned a mRNA/miRNA, which can be counted after bonding with its target.\nAs a result each count of a specific barcode represents the presence of its target mRNA/miRNA. (tools: NACHO)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirdeep2_mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs.", "nacho_qc": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "krakentools_combinekreports": "Takes multiple kraken-style reports and combines them into a single report file", "nacho_normalize": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "parabricks_genotypegvcf": "NVIDIA Clara Parabricks GPU-accelerated joint genotyping, replicating GATK GenotypeGVCFs"}}, "target": "nacho_normalize", "target_idx": 3}
{"id": "mod_miniprot_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides fasta index required by miniprot alignment. (tools: miniprot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"soupx": "Estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.\n\nThe filtere", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "miniprot/index": "Provides fasta index required by miniprot alignment.", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "bcftools/index": "Index VCF tools"}}, "target": "miniprot/index", "target_idx": 2}
{"id": "mod_fcs_fcsgx_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excluding the given taxid. (tools: fcs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmtnote_annotate": null, "abyss_abysspe": null, "abricate_summary": null, "fcs_fcsgx": null, "gfatools_stat": null}}, "target": "fcs_fcsgx", "target_idx": 3}
{"id": "resource_autocycler_combine_2", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMBINE", "tool": "autocycler/combine", "description": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMBINE (Merge resolved cluster assemblies into final consensus outputs with Autocycler.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_parabricks_mutectcaller_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated somatic variant calling, replicating GATK Mutect2. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"graphtyper/genotype": "Tools for population-scale genotyping using pangenome graphs.", "parabricks/mutectcaller": "NVIDIA Clara Parabricks GPU-accelerated somatic variant calling, replicating GATK Mutect2.", "ferrohgvs/parse": "Parse and validate HGVS variant descriptions with ferro", "amulety/embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "nextclade/run": "SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation)"}}, "target": "parabricks/mutectcaller", "target_idx": 1}
{"id": "mod_saltshaker_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mtDNA deletion and duplication plotting downstream of mitosalt (tools: saltshaker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"haplogrep3_classify": null, "pirate": null, "saltshaker_plot": null, "mgnifam_generatefamilies": null, "saltshaker_call": null}}, "target": "saltshaker_plot", "target_idx": 2}
{"id": "subworkflow_pkg_vcf_impute_beagle5_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_BEAGLE5", "modules": ["beagle5/beagle", "bcftools/index", "bcftools/view", "glimpse2/ligate"], "description": "Subworkflow to impute VCF files using BEAGLE5 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_BEAGLE5 (beagle5/beagle, bcftools/index, bcftools/view, glimpse2/ligate) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_impute_beagle5": null, "Local subworkflow VCF_IMPUTE_BEAGLE5": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_impute_beagle5", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_4_1", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Xenium output bundle with transcripts CSV, cell polygons, and morphology images?", "criteria": {"sample,vcf": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null, "sample,image": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "noul_default_empty_channel_behavior_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_pairtools_stats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairs statistics (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools_stats": "Calculate pairs statistics", "ltrretriever_lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric ", "plink_ld": "LD analysis in PLINK examines genetic variant associations within populations", "gcta_bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "custom_collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op"}}, "target": "pairtools_stats", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_3", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_arriba_arriba_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data. (tools: arriba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_tnscope": "TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, us", "catpack_contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).", "parabricks_starfusion": "This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. Thi", "arriba_arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "arriba_visualisation": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}}, "target": "arriba_arriba", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_10", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_svim_alignment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Structural variant detection from long-read sequencing alignments using SVIM. (tools: svim)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_splitintervals": "Split intervals into sub-interval files.", "caddsv_run": "Score structural variants with CADD-SV.", "svim_alignment": "Structural variant detection from long-read sequencing alignments using SVIM.", "checkv_downloaddatabase": "Construct the database necessary for checkv's quality assessment", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient "}}, "target": "svim_alignment", "target_idx": 2}
{"id": "resource_bclconvert_3", "category": "resource_profiling", "state": {"process": "BCLCONVERT", "tool": "bclconvert", "description": "Demultiplex Illumina BCL files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCLCONVERT (Demultiplex Illumina BCL files) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_0_0", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping", "pipeline": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,tss_bed": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_19", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_8", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_bamaligncleaner_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: removes unused references from header of sorted BAM/CRAM files. (tools: bamaligncleaner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": "split single end read groups by length and merge paired end reads", "gens/preparecovandbaf": "Tools for preparing inputs for visualization in Gens", "cellranger/multi": "Module to use Cell Ranger's pipelines to analyze sequencing data produced from various Chromium technologies, ", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "bamreadcount": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencin"}}, "target": "bamaligncleaner", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_0_1", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_4_0", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering", "pipeline": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,rrna_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "samplesheet_arch_rare_disease_trio_6_0", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns are standard for Trio exome/genome sequencing (Proband, Mother, Father) input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/atacseq) for ATAC-seq chromatin accessibility with biological replicates. Input files: Paired-end Tn5 transposed FASTQs across conditions and replicates.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: ATAC-seq chromatin accessibility with biological replicates.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,bed": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "field_constraint_bam_1_2", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "mod_rpbp_extractmetageneprofiles_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\". For each read length, the profile\ncounts how many reads of that length have their 5' end at each position\nin a window around every annotated start codon, summed across all\ntranscripts. Looking at the profile across the window reveals whether\nreads of that length show the 3-nucleotide periodicity characteristic\nof translating ribosomes.\n\nThis per-length view matters because different ribosome footprint\nlengths place the ribosomal P-site (the codon being decoded) at\ndifferent offsets from the read's 5' end, so each length needs its\nown offset calibration. Output is consumed by\n`rpbp/estimatemetagenebayesfactors`, which scores each (length, offset)\ncombination for periodicity. (tools: rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trust4": "Run TRUST4 on RNA-seq data", "rpbp_extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "rpbp_estimateorfbayesfactors": "Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian ", "bwameme_mem": "Performs fastq alignment to a fasta reference using BWA-MEME", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\"."}}, "target": "rpbp_extractmetageneprofiles", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_0_3", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_agat_convertbed2gff_0", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTBED2GFF", "tool": "agat/convertbed2gff", "description": "Takes a bed12 file and converts to a GFF3 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTBED2GFF (Takes a bed12 file and converts to a GFF3 file) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_fgumi_correct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgbio/callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag.", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "goat/taxonsearch": "Query metadata for any taxon across the tree of life.", "fgumi/correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi", "fgumi/clip": "Clip overlapping reads in a BAM file with fgumi"}}, "target": "fgumi/correct", "target_idx": 3}
{"id": "mod_fastq_align_dedup_bwameth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate (tools: fastq_align_dedup_bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "plink/extract": "Subset plink bfiles with a text file of variant identifiers", "bwameth/align": "Performs alignment of BS-Seq reads using bwameth", "fastq_align_dedup_bwameth": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate", "bcftools/isec": "Apply set operations to VCF files"}}, "target": "fastq_align_dedup_bwameth", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_5", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_jvarkit_vcffilterjdk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtering VCF with dynamically-compiled java expressions (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"muse_sump": "Computes tier-based cutoffs from a sample-specific error model which is generated by muse/call and reports the", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "jvarkit_vcffilterjdk": "Filtering VCF with dynamically-compiled java expressions", "gcta_bivariatereml": "Run bivariate REML analysis with a single dense GRM"}}, "target": "jvarkit_vcffilterjdk", "target_idx": 3}
{"id": "resource_bwafastalign_mem_4", "category": "resource_profiling", "state": {"process": "BWAFASTALIGN_MEM", "tool": "bwafastalign/mem", "description": "Performs fastq alignment to a fasta reference using BWA-FastAlign."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAFASTALIGN_MEM (Performs fastq alignment to a fasta reference using BWA-FastAlign.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_high", "target_idx": 0}
{"id": "pipe_all101_spatialaxe_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for 10x-genomics analysis? Specific context: A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data. Topics: 10x-genomics, atera, image-processing, spatial, spatial-data-analysis, spatial-transcriptomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "spatialaxe", "target_idx": 2}
{"id": "resource_amulety_embed_1", "category": "resource_profiling", "state": {"process": "AMULETY_EMBED", "tool": "amulety/embed", "description": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_EMBED (A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) ) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_ngsbits_updhunter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: UPD detection from trio variant data. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"upd": "Simple software to call UPD regions from germline exome/wgs trios.", "bwa/index": "Create BWA index for reference genome", "ngsbits/updhunter": "UPD detection from trio variant data.", "bcftools/annotate": "Add or remove annotations.", "slamdunk/map": "Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings."}}, "target": "ngsbits/updhunter", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_24", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_sentieon_qualcal_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate recalibration table and optionally perform base quality recalibration (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_gatherbqsrreports": "Gathers scattered BQSR recalibration reports into a single file", "instrain_profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "fibertoolsrs_addnucleosomes": "Add nucleosomes positions and MSP position to ONT BAM files", "gatk4spark_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "sentieon_qualcal": "Generate recalibration table and optionally perform base quality recalibration"}}, "target": "sentieon_qualcal", "target_idx": 4}
{"id": "resource_bftools_showinf_0", "category": "resource_profiling", "state": {"process": "BFTOOLS_SHOWINF", "tool": "bftools/showinf", "description": "Extract OME xml data from OME-tif"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFTOOLS_SHOWINF (Extract OME xml data from OME-tif) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_prepilluminareads_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPILLUMINAREADS (trimmomatic).", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow prepilluminareads": null, "Local subworkflow PREPILLUMINAREADS": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 3}
{"id": "mod_gatk4_genomicsdbimport_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: merge GVCFs from multiple samples. For use in joint genotyping or somatic panel of normal creation. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/annotateintervals": null, "rundbcan/easysubstrate": null, "gatk4/genomicsdbimport": null, "interproscan": null, "gatk4/baserecalibrator": null}}, "target": "gatk4/genomicsdbimport", "target_idx": 2}
{"id": "mod_chelae_trim_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adapter and quality trimming of short-read FASTQ data using chelae. (tools: chelae)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromap/chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "chopper": "Filter and trim long read data.", "fastq_extract_kraken_krakentools": "Extract classified Kraken2 reads by taxonomic id", "concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage "}}, "target": "chelae/trim", "target_idx": 1}
{"id": "resource_aardvark_merge_3", "category": "resource_profiling", "state": {"process": "AARDVARK_MERGE", "tool": "aardvark/merge", "description": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_MERGE (A tool to evaluate and merge multiple variant calls into a consensus VCF.) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_vcf_impute_minimac4_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_IMPUTE_MINIMAC4", "modules": ["minimac4/compressref", "minimac4/impute", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute VCF files using MINIMAC4 software. The subworkflow"}, "question": {"type": "choice", "instructions": "How should VCF_IMPUTE_MINIMAC4 (minimac4/compressref, minimac4/impute, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Local subworkflow VCF_IMPUTE_MINIMAC4": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow vcf_impute_minimac4": null}}, "target": "Use nf-core subworkflow vcf_impute_minimac4", "target_idx": 3}
{"id": "mod_bbmap_repair_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Re-pairs reads that became disordered or had some mates eliminated. (tools: repair)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "bbmap/repair": "Re-pairs reads that became disordered or had some mates eliminated.", "quartonotebook": "Render a Quarto notebook, including parametrization.", "caalm/downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down"}}, "target": "bbmap/repair", "target_idx": 2}
{"id": "noul_channel_filter_operator_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wes_pe_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Paired-end Whole Exome Sequencing (WES) target capture)", "question": {"type": "choice", "instructions": "Which columns are standard for Paired-end Whole Exome Sequencing (WES) target capture input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_rnaseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.. Topics: rna, rna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"dualrnaseq": null, "viralmetagenome": null, "scrnaseq": null, "molkart": null, "rnaseq": null, "phaseimpute": null, "pacvar": null, "bactmap": null}}, "target": "rnaseq", "target_idx": 4}
{"id": "mod_genmap_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: create index file for genmap (tools: genmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmap/index": null, "biscuit/qc": null, "bismark/genomepreparation": null, "stacks/refmap": null, "openms/peakpickerhires": null}}, "target": "genmap/index", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_5_4", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Tumor-only somatic variant calling without matched normal.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bcftools_annotate_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ANNOTATE", "tool": "bcftools/annotate", "description": "Add or remove annotations."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ANNOTATE (Add or remove annotations.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_faa_seqfu_seqkit_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FAA_SEQFU_SEQKIT", "modules": ["seqfu/stats", "seqkit/seq", "seqkit/rmdup", "seqkit/replace"], "description": "Subworkflow that optionally preprocesses amino acid FASTA sequences"}, "question": {"type": "choice", "instructions": "How should FAA_SEQFU_SEQKIT (seqfu/stats, seqkit/seq, seqkit/rmdup, seqkit/replace) be structured in DSL2?", "criteria": {"Local subworkflow FAA_SEQFU_SEQKIT": null, "Use nf-core subworkflow faa_seqfu_seqkit": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow faa_seqfu_seqkit", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_5_2", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: ATAC-seq chromatin accessibility with biological replicates.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_create_umi_consensus_fgbio_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_CREATE_UMI_CONSENSUS_FGBIO", "modules": ["bwa/index", "bwa/mem", "bwamem2/mem", "bwamem2/index", "fgbio/fastqtobam", "fgbio/groupreadsbyumi", "fgbio/callmolecularconsensusreads", "fgbio/callduplexconsensusreads", "fgbio/filterconsensusreads", "samblaster", "samtools/bam2fq", "samtools/sort", "samtools/index", "samtools/fastq", "fgbio/zipperbams"], "description": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads"}, "question": {"type": "choice", "instructions": "How should FASTQ_CREATE_UMI_CONSENSUS_FGBIO (bwa/index, bwa/mem, bwamem2/mem, bwamem2/index, fgbio/fastqtobam, fgbio/groupreadsbyumi, fgbio/callmolecularconsensusreads, fgbio/callduplexconsensusreads, fgbio/filterconsensusreads, samblaster, samtools/bam2fq, samtools/sort, samtools/index, samtools/fastq, fgbio/zipperbams) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_create_umi_consensus_fgbio": null, "Leave them out": null, "Local subworkflow FASTQ_CREATE_UMI_CONSENSUS_FGBIO": null}}, "target": "Use nf-core subworkflow fastq_create_umi_consensus_fgbio", "target_idx": 1}
{"id": "field_constraint_sex_2_12", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_14", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "schema_std_demultiplex_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/demultiplex", "description": "Demultiplexing pipeline for sequencing data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/demultiplex?", "criteria": {"sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,fastq_2": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null}}, "target": "id,samplesheet,lane,flowcell,per_flowcell_manifest", "target_idx": 2}
{"id": "mod_tcoffee_seqreformat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reformats files with t-coffee (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "tcoffee_seqreformat": "Reformats files with t-coffee", "gecco_convert": "This command helps transforming the output files created by\nGECCO into helpful format, should you want to use "}}, "target": "tcoffee_seqreformat", "target_idx": 3}
{"id": "resource_bedtools_bamtobed_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_BAMTOBED", "tool": "bedtools/bamtobed", "description": "Converts a bam file to a bed12 file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_BAMTOBED (Converts a bam file to a bed12 file.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_braker3_2", "category": "resource_profiling", "state": {"process": "BRAKER3", "tool": "braker3", "description": "Gene prediction in novel genomes using RNA-seq and protein homology information"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRAKER3 (Gene prediction in novel genomes using RNA-seq and protein homology information) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "data_format": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns are standard for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq input samplesheet?", "criteria": {"sample,well,fastq": null, "sample,matrix": null, "plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bio2zarr_vcf2zarrconvert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster. (tools: vcf2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/pluginsplit": null, "centrifuger/centrifuger": null, "aardvark/compare": null, "bio2zarr/vcf2zarrconvert": null, "bcftools/call": null}}, "target": "bio2zarr/vcf2zarrconvert", "target_idx": 3}
{"id": "mod_octopusv_svcf2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts octopusv SVCF files to the standard BED format (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"octopusv/correct": "Standardize a caller VCF into OctopuSV SVCF format.", "instrain/profile": "inStrain is python program for analysis of co-occurring genome populations from metagenomes that allows highly", "semibin/singleeasybin": "metagenomic binning with self-supervised learning", "octopusv/svcf2bed": "Converts octopusv SVCF files to the standard BED format", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file"}}, "target": "octopusv/svcf2bed", "target_idx": 3}
{"id": "resource_bwamem2_index_5", "category": "resource_profiling", "state": {"process": "BWAMEM2_INDEX", "tool": "bwamem2/index", "description": "Create BWA-mem2 index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAMEM2_INDEX (Create BWA-mem2 index for reference genome) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_high", "target_idx": 1}
{"id": "mod_alignoth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creating alignment plots from bam files (tools: alignoth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pharmcat/phenotyper": null, "alignoth": null, "agat/spmergeannotations": null, "agat/spfilterbyorfsize": null, "pbmm2/align": null}}, "target": "alignoth", "target_idx": 1}
{"id": "mod_foldmason_createdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a database for Foldmason. (tools: foldmason)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldmason/createdb": "Creates a database for Foldmason.", "rhocall/viz": "Call regions of homozygosity and make tentative UPD calls", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "alignoth": "Creating alignment plots from bam files", "cat/cat": "A module for concatenation of gzipped or uncompressed files"}}, "target": "foldmason/createdb", "target_idx": 0}
{"id": "field_constraint_bam_3_9", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "resource_bwamem2_index_4", "category": "resource_profiling", "state": {"process": "BWAMEM2_INDEX", "tool": "bwamem2/index", "description": "Create BWA-mem2 index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWAMEM2_INDEX (Create BWA-mem2 index for reference genome) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_high", "target_idx": 2}
{"id": "resource_bamclipper_1", "category": "resource_profiling", "state": {"process": "BAMCLIPPER", "tool": "bamclipper", "description": "This module is used to clip primer sequences from your alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCLIPPER (This module is used to clip primer sequences from your alignments.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_instrain_compare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strain-level comparisons across multiple inStrain profiles (tools: instrain)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"circexplorer2_annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse", "instrain_compare": "Strain-level comparisons across multiple inStrain profiles", "ribocode_gtfupdate": "Update GTF annotation file for RiboCode compatibility", "drep_compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "gffcompare": "Compare, merge, annotate and estimate accuracy of generated gtf files"}}, "target": "instrain_compare", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic tumor-normal calling from pre-aligned BAM files", "data_format": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted BAMs with index for tumor and normal samples?", "criteria": {"patient,sample,bam": null, "sample,bam,bai": null, "sample,vcf": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "pipe_all101_denovotranscript_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for denovo-assembly. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, "}}, "target": "denovotranscript", "target_idx": 4}
{"id": "noul_include_modular_process_syntax_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "schema_std_metapep_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metapep", "description": "From metagenomes to epitopes and beyond", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/metapep?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,bam,cram": null, "sample,alleles,mhc_class,filename": null, "condition,type,microbiome_path,alleles,weights_path": null}}, "target": "condition,type,microbiome_path,alleles,weights_path", "target_idx": 3}
{"id": "noul_include_modular_process_syntax_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_bbmap_clumpify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "fasta_build_add_kraken2": "KRAKEN2 build custom database subworkflow", "sylph_sketchsamples": "Sketching/indexing sequencing reads", "bbmap_clumpify": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon"}}, "target": "bbmap_clumpify", "target_idx": 3}
{"id": "mod_utils_references_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functionality for dealing with references that may be useful for any Nextflow pipeline (tools: utils_references)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"decoupler/decoupler": "decoupler is a package containing different statistical methods\nto extract biological activities from omics da", "fusioncatcher/build": "Build references for fusioncatcher", "aria2": "CLI Download utility", "amulety/esm2": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety.", "utils_references": "Functionality for dealing with references that may be useful for any Nextflow pipeline"}}, "target": "utils_references", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_1_1", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_4_0", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: BGZF-compressed VCF files with companion Tabix index files?", "criteria": {"sample,vcf,tbi": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "mod_savana_to_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tumour-only somatic SV calling with optional copy-number analysis in SAVANA (tools: savana)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv/annotsv": null, "sourmash/index": null, "caddsv/get": null, "savana/to": null, "busco/generateplot": null}}, "target": "savana/to", "target_idx": 3}
{"id": "mod_merqury_merqury_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: k-mer based assembly evaluation. (tools: merqury)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fargene": "tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full", "fastk_merge": "A tool to merge FastK histograms", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "merqury_merqury": "k-mer based assembly evaluation.", "fastk_fastk": "A fast K-mer counter for high-fidelity shotgun datasets"}}, "target": "merqury_merqury", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_35", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "intent_build_pipeline_22", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 2}
{"id": "mod_cnvkit_batch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy number variant detection from high-throughput sequencing data (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee_tcs": "Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just", "cnvkit_batch": "Copy number variant detection from high-throughput sequencing data", "cnvkit_genemetrics": "Copy number variant detection from high-throughput sequencing data", "ltrretriever_lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric ", "cnvkit_fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera"}}, "target": "cnvkit_batch", "target_idx": 1}
{"id": "mod_gatk4_collectreadcounts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects read counts at specified intervals. The count for each interval is calculated by counting the number of read starts that lie in the interval. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/collectreadcounts": "Collects read counts at specified intervals. The count for each interval is calculated by counting the number ", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big"}}, "target": "gatk4/collectreadcounts", "target_idx": 0}
{"id": "mod_concoct_mergecutupclustering_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "concoct/mergecutupclustering": "Merge consecutive parts of the original contigs original cut up by cut_up_fasta.py", "mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package", "rrnatranscripts": "Ribosomal RNA extraction from a GTF file.", "dastool/fastatocontig2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format"}}, "target": "concoct/mergecutupclustering", "target_idx": 1}
{"id": "pipe_all101_pixelator_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB). Topics: molecular-pixelation, pixelator, pixelgen-technologies, proteins, single-cell, single-cell-omics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]"}}, "target": "pixelator", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_33", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_4_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "PBMM2_ALIGN", "library_inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral amplicon sequencing with primers)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral amplicon sequencing with primers.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_affy_justrma_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read CEL files into an ExpressionSet and generate a matrix (tools: affy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr/propd": "Perform differential proportionality analysis", "qualimap/rnaseq": "Evaluate alignment data", "cellrangeratac/count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "limma/differential": "runs a differential expression analysis with Limma", "affy/justrma": "Read CEL files into an ExpressionSet and generate a matrix"}}, "target": "affy/justrma", "target_idx": 4}
{"id": "mod_odgi_stats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metrics describing a variation graph and its path relationship. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi_unchop": "Merge unitigs into a single node preserving the node order.", "odgi_stats": "Metrics describing a variation graph and its path relationship.", "deepvariant_callvariants": "Call variants from the examples produced by make_examples", "samtools_calmd": "calculates MD and NM tags", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format"}}, "target": "odgi_stats", "target_idx": 1}
{"id": "mod_motus_downloaddb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download the mOTUs database (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge_kreport": null, "centrifuge_centrifuge": null, "motus_downloaddb": null, "samtools_calmd": null, "fastq_qc_stats": null}}, "target": "motus_downloaddb", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_16", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_variantbenchmarking_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research. Topics: benchmark, small-variants, structural-variants, variant-calling. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "variantbenchmarking", "target_idx": 1}
{"id": "field_constraint_phenotype_1_4", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [normal, tumor]": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "mod_agat_convertgff2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes a GFF3 file and converts to a bed12 file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "varlociraptor/filterfdr": "Filter Varlociraptor variant calls using FDR control.", "kaiju/kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database"}}, "target": "agat/convertgff2bed", "target_idx": 0}
{"id": "mod_goleft_indexcov_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly estimate coverage from a whole-genome bam or cram index. A bam index has 16KB resolution so that's what this gives, but it provides what appears to be a high-quality coverage estimate in seconds per genome. (tools: goleft)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cmseq/polymut": null, "goleft/indexcov": null, "fq/generate": null, "bbmap/pileup": null, "sentieon/tnscope": null}}, "target": "goleft/indexcov", "target_idx": 1}
{"id": "mod_aardvark_compare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF. (tools: aardvark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "custom_tabulartogseachip": "Make a GSEA class file (.chip) from tabular inputs", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "gatk_unifiedgenotyper": "SNP and Indel variant caller on a per-locus basis"}}, "target": "aardvark_compare", "target_idx": 3}
{"id": "core_tool_featurecounts_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Assign and quantify mapped reads to genomic features such as exons, genes, and promoter annotations from sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"kallisto": null, "stringtie": null, "htseq": null, "featurecounts": null, "salmon": null}}, "target": "featurecounts", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_26", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_2_18", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Single-end Oxford Nanopore direct RNA)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Oxford Nanopore direct RNA with entry step NANOPLOT.", "criteria": {"sample,fast5": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay_type": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "data_format": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment input samplesheet?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_gatk_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/learnreadorientationmodel", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/learnreadorientationmodel, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK": null, "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk", "target_idx": 3}
{"id": "field_constraint_sample_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sample", "validation_type": "unique_identifier"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sample'.", "criteria": {"type: integer": null, "enum: [0, 1]": null, "format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_5_2", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Xenium in situ subcellular spatial RNA transcriptomics.", "criteria": {"sample,image": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "noul_executor_support_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_agat_spfilterfeaturefromkilllist_4", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERFEATUREFROMKILLLIST", "tool": "agat/spfilterfeaturefromkilllist", "description": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERFEATUREFROMKILLLIST (The script aims to remove features based on a kill list. The default behaviour i) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_8_3", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_bcftools_view_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF (tools: view)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_call": "generate VCF file from a BAM file using various calling methods", "bcftools_view": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF", "ucsc_bigwigaverageoverbed": "compute average score of bigwig over bed file", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "hmmer_hmmemit": "emit sequences from a profile HMM"}}, "target": "bcftools_view", "target_idx": 1}
{"id": "mod_htslib_bgziptabix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multi-purpose module to compress, decompress and index files using bgzip and tabix. (tools: htslib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat/fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "htslib/bgziptabix": "Multi-purpose module to compress, decompress and index files using bgzip and tabix.", "huggingface/download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "fastqc": "Run FastQC on sequenced reads", "tabix/bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde"}}, "target": "htslib/bgziptabix", "target_idx": 1}
{"id": "noul_subworkflow_structural_blocks_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_qcatch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cell-filtering and QC reporting tool for alevin-fry quantification results (tools: qcatch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"muscle5/super5": "Muscle is a program for creating multiple alignments of amino acid or nucleotide sequences. This particular mo", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "qcatch": "Cell-filtering and QC reporting tool for alevin-fry quantification results", "gapseq/fill": "Perform gap filling on draft metabolic model", "cellbender/removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data"}}, "target": "qcatch", "target_idx": 2}
{"id": "intent_debug_error_0", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wes_pe_0_1", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_vembrane_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter VCF files with vembrane (tools: vembrane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star/indexversion": "Get the minimal allowed index version from STAR", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bbmap/filterbyname": "Filter out sequences by sequence header name(s)", "vembrane/filter": "Filter VCF files with vembrane"}}, "target": "vembrane/filter", "target_idx": 4}
{"id": "core_tool_interproscan_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Scan protein and nucleotide sequences against multiple member databases to identify structural domains, functional sites, and protein families.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"eggnog": null, "diamond": null, "blastp": null, "interproscan": null, "hmmer": null}}, "target": "interproscan", "target_idx": 3}
{"id": "resource_agat_convertspgxf2gxf_3", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGXF2GXF", "tool": "agat/convertspgxf2gxf", "description": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGXF2GXF (Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_spades_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembles a small genome (bacterial, fungal, viral) (tools: spades)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "fastq_align_dedup_bismark": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort", "spades": "Assembles a small genome (bacterial, fungal, viral)", "abyss/abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}}, "target": "spades", "target_idx": 3}
{"id": "mod_gatk4_applybqsr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply base quality score recalibration (BQSR) to a bam file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "quast": "Quality Assessment Tool for Genome Assemblies", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "hifitrimmer/processblast": "Run hifi_trimmer process_blast to process a BLAST search of adapter sequences against PacBio HiFi reads.\nPrima", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "gatk4/applybqsr", "target_idx": 4}
{"id": "samplesheet_arch_viral_amplicon_artic_3_1", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral amplicon sequencing with primers with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_7", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_29", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_0_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking?", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bedtools_flank_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_FLANK", "tool": "bedtools/flank", "description": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_FLANK (Creates two new flanking intervals for each interval in a BED/GFF/VCF file.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "intent_build_pipeline_24", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "build_pipeline", "target_idx": 0}
{"id": "mod_scimap_mcmicro_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SCIMAP is a suite of tools that enables spatial single-cell analyses (tools: scimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk_sort": "Sort  CSV (or TSV) tables", "bedtools_sort": "Sorts a feature file by chromosome and other criteria.", "seqkit_concat": "Concatenating multiple uncompressed sequence files together", "bam_tumor_normal_somatic_variant_calling_strelka": "Perform variant calling on a paired tumor normal set of samples using strelka somatic mode.\nf1r2 output of mut", "scimap_mcmicro": "SCIMAP is a suite of tools that enables spatial single-cell analyses"}}, "target": "scimap_mcmicro", "target_idx": 4}
{"id": "samplesheet_arch_singlecell_parse_splitseq_6_5", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns are standard for Parse Biosciences Split-seq combinatorial barcoding input samplesheet?", "criteria": {"sample,well,plate": null, "sample,bam": null, "sample,fastq_1": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_chromap_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_CHROMAP", "modules": ["chromap/chromap", "picard/addorreplacereadgroups", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_CHROMAP (chromap/chromap, picard/addorreplacereadgroups, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_align_chromap": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_CHROMAP": null}}, "target": "Use nf-core subworkflow fastq_align_chromap", "target_idx": 1}
{"id": "schema_std_riboseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/riboseq. Description: Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/riboseq.", "criteria": {"id,raw_file": null, "sample,fastq_1,fastq_2,strandedness,type": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,fastq_1,fastq_2,batch,condition": null}}, "target": "sample,fastq_1,fastq_2,strandedness,type", "target_idx": 1}
{"id": "mod_msisensor2_msi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: msisensor2 detection of MSI regions. (tools: msisensor2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tmb/pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "msisensorpro/msisomatic": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "kma/kma": "Mapping raw reads directly against redundant databases via KMA alignment", "damageprofiler": "A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage", "msisensor2/msi": "msisensor2 detection of MSI regions."}}, "target": "msisensor2/msi", "target_idx": 4}
{"id": "resource_bbmap_index_0", "category": "resource_profiling", "state": {"process": "BBMAP_INDEX", "tool": "bbmap/index", "description": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_INDEX (Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_9", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "core_tool_multiqc_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Aggregate and summarize quality control metrics and analysis logs across FastQC, Cutadapt, and STAR into a single interactive HTML report.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"trimmomatic": "Flexible read trimming tool", "picard": "Command-line tools for manipulating high-throughput sequencing data", "fastqc": "Quality control tool for high throughput sequence data", "fastp": "All-in-one FASTQ preprocessor", "multiqc": "Aggregate bioinformatics analysis results across multiple tools into a single report"}}, "target": "multiqc", "target_idx": 4}
{"id": "mod_legsta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Typing of clinical and environmental isolates of Legionella pneumophila (tools: legsta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate_run": null, "cobs_compactconstruct": null, "snpsites": null, "legsta": null, "abritamr_run": null}}, "target": "legsta", "target_idx": 3}
{"id": "field_constraint_bai_1_1", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_4_2", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_yak_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: a tool to build k-mer hash table for fasta and fastq files (tools: yak)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yak_count": null, "genometester4_glistmaker": null, "merqury_hapmers": null, "rsem_calculateexpression": null, "anndata_getsize": null}}, "target": "yak_count", "target_idx": 0}
{"id": "mod_xz_compress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses files with xz. (tools: xz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"foldcomp/decompress": null, "xz/compress": null, "gunzip": null, "gapseq/findtransport": null, "hamronization/deeparg": null}}, "target": "xz/compress", "target_idx": 1}
{"id": "mod_samtools_dict_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a sequence dictionary file from a FASTA file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": null, "jvarkit/dict2bed": null, "fargene": null, "deacon/indexunion": null, "samtools/dict": null}}, "target": "samtools/dict", "target_idx": 4}
{"id": "subworkflow_pkg_bam_variant_demix_boot_freyja_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_DEMIX_BOOT_FREYJA", "modules": ["freyja/variants", "freyja/demix", "freyja/update", "freyja/boot"], "description": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to the Hu-1 reference)"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_DEMIX_BOOT_FREYJA (freyja/variants, freyja/demix, freyja/update, freyja/boot) be structured in DSL2?", "criteria": {"Local subworkflow BAM_VARIANT_DEMIX_BOOT_FREYJA": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_variant_demix_boot_freyja": null}}, "target": "Use nf-core subworkflow bam_variant_demix_boot_freyja", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_0_0", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_34", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_vsearch_usearchglobal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare target sequences to fasta-formatted query sequences using global pairwise alignment. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch/cluster": "Cluster sequences using a single-pass, greedy centroid-based clustering algorithm.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "mmseqs/createdb": "Create an MMseqs database from an existing FASTA/Q file", "vsearch/usearchglobal": "Compare target sequences to fasta-formatted query sequences using global pairwise alignment.", "sentieon/readwriter": "Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality S"}}, "target": "vsearch/usearchglobal", "target_idx": 3}
{"id": "noul_modular_subworkflow_composition_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_metaspace_converter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Export METASPACE datasets to AnnData and SpatialData objects (tools: metaspace_converter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"icountmini/metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks.", "metaspace/converter": "Export METASPACE datasets to AnnData and SpatialData objects", "holodeck/eval": "Evaluate alignment accuracy of holodeck-simulated reads", "diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "openms/fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX"}}, "target": "metaspace/converter", "target_idx": 1}
{"id": "field_constraint_strandedness_2_1", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "format: file-path": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "resource_anota2seq_anota2seqrun_4", "category": "resource_profiling", "state": {"process": "ANOTA2SEQ_ANOTA2SEQRUN", "tool": "anota2seq/anota2seqrun", "description": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANOTA2SEQ_ANOTA2SEQRUN (Generally applicable transcriptome-wide analysis of translational efficiency usi) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_bam_qc_picard_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces comprehensive statistics from BAM file (tools: bam_qc_picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eautils/fastqstats": null, "subread/featurecounts": null, "bam_qc_picard": null, "agat/spstatistics": null, "mcroni": null}}, "target": "bam_qc_picard", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Single-end Oxford Nanopore direct RNA", "data_format": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single fastq per sample?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1": null, "sample,fast5": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Visium spatial transcriptomics with histology image", "data_format": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fastq_1,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "mod_icountmini_summary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Report proportion of cross-link events/sites on each region type. (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clippy": "Runs the Clippy CLIP peak caller", "fibertoolsrs/addnucleosomes": "Add nucleosomes positions and MSP position to ONT BAM files", "icountmini/summary": "Report proportion of cross-link events/sites on each region type.", "mash/screen": "Screens query sequences against large sequence databases", "icountmini/segment": "Formats a GTF file for use with iCount sigxls"}}, "target": "icountmini/summary", "target_idx": 2}
{"id": "field_constraint_fastq_1_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "resource_binette_3", "category": "resource_profiling", "state": {"process": "BINETTE", "tool": "binette", "description": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BINETTE (A fast and accurate binning refinement tool to construct high quality MAGs from ) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_tumourevo_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tumourevo", "assay": "tumourevo pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/tumourevo (Analysis pipeline to model tumour clonal evolution from WGS )?", "criteria": {"sample,input,output_path,checksum_md5,checksum_sha": null, "patient,vcf,tbi,dataset,tumour_sample": null, "sample,fastq_1,fastq_2": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "patient,vcf,tbi,dataset,tumour_sample", "target_idx": 1}
{"id": "resource_allelecounter_5", "category": "resource_profiling", "state": {"process": "ALLELECOUNTER", "tool": "allelecounter", "description": "Generates a count of coverage of alleles"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALLELECOUNTER (Generates a count of coverage of alleles) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_3", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_homer_pos2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converting from HOMER peak to BED file formats (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"idr": "Measures reproducibility of ChIP-seq, ATAC-seq peaks using IDR (Irreproducible\nDiscovery Rate)", "custom/tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "homer/findpeaks": "Find peaks with HOMER suite", "homer/pos2bed": "Converting from HOMER peak to BED file formats", "sequenzautils/gcwiggle": "Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggl"}}, "target": "homer/pos2bed", "target_idx": 3}
{"id": "field_constraint_status_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [auto, forward, reverse]": null, "format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic tumor-normal calling from pre-aligned BAM files", "data_format": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "patient,sample,status,bam,bai": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_11", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_tn_3_1", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic cancer variant calling with tumor-normal pairs with entry step BWA_MEM.", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_sample_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"format: file-path": null, "type: integer": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "samplesheet_arch_ont_demux_barcodes_0_1", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,barcode": null, "sample,bam": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "noul_file_pairing_in_channel_tuples_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_abritamr_run_5", "category": "resource_profiling", "state": {"process": "ABRITAMR_RUN", "tool": "abritamr/run", "description": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRITAMR_RUN (A NATA accredited tool for reporting the presence of antimicrobial resistance ge) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "subworkflow_pkg_bam_rseqc_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_RSEQC", "modules": ["rseqc", "rseqc/tin", "rseqc/readduplication", "rseqc/readdistribution", "rseqc/junctionsaturation", "rseqc/junctionannotation", "rseqc/innerdistance", "rseqc/inferexperiment", "rseqc/bamstat"], "description": "Subworkflow to run multiple commands in the RSeqC package"}, "question": {"type": "choice", "instructions": "How should BAM_RSEQC (rseqc, rseqc/tin, rseqc/readduplication, rseqc/readdistribution, rseqc/junctionsaturation, rseqc/junctionannotation, rseqc/innerdistance, rseqc/inferexperiment, rseqc/bamstat) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_RSEQC": null, "Leave them out": null, "Use nf-core subworkflow bam_rseqc": null}}, "target": "Use nf-core subworkflow bam_rseqc", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_18", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_truvari_bench_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Given baseline and comparison sets of variants, calculate the recall/precision/f-measure (tools: truvari)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gappa/examineheattree": null, "gem3/gem3indexer": null, "truvari/bench": null, "gatk4/collectsvevidence": null, "annotsv/annotsv": null}}, "target": "truvari/bench", "target_idx": 2}
{"id": "mod_gstama_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge multiple transcriptomes while maintaining source information. (tools: gstama)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/annotate": "Add or remove annotations.", "gstama/polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)", "bcftools/pluginscatter": "Split VCF by chunks or regions, creating multiple VCFs.", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "gstama/merge": "Merge multiple transcriptomes while maintaining source information."}}, "target": "gstama/merge", "target_idx": 4}
{"id": "resource_bcftools_mpileup_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MPILEUP", "tool": "bcftools/mpileup", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MPILEUP (Compresses VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_6_4", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Somatic cancer variant calling with tumor-normal pairs input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_bulk_small_rna_5_5", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "template": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/smrnaseq, determine the input samplesheet column structure for: Small RNA / miRNA sequencing.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_1_5", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "template": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "mod_deepmased_features_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DeepMAsED features subcommand: extracts alignment-based features from BAM and assembly FASTA for each contig, producing feature tables used as input for DeepMAsED predict. (tools: deepmased)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "deepmased_features": "DeepMAsED features subcommand: extracts alignment-based features from BAM and assembly FASTA for each contig, ", "tidk_plot": "Plots telomeric repeat frequency against sliding window location\nusing data produced by `tidk/search`", "gatk4_composestrtablefile": "This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Drags", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "deepmased_features", "target_idx": 1}
{"id": "mod_elprep_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split bam file into manageable chunks (tools: elprep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr_extract": "Computes the coverage map along the reference genome", "dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "elprep_split": "Split bam file into manageable chunks", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "elprep_split", "target_idx": 2}
{"id": "noul_deprecated_dsl1_set_keyword_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "field_constraint_bai_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "mod_whamg_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The wham suite consists of two programs, wham and whamg. wham, the original tool, is a very sensitive method with a high false discovery rate. The second program, whamg, is more accurate and better suited for general structural variant (SV) discovery. (tools: whamg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whamg": null, "eklipse": null, "aardvark_compare": null, "annotsv_annotsv": null, "plink_vcf": null}}, "target": "whamg", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_6_0", "category": "samplesheet_schema", "state": {"technology": "Spatial In Situ", "workflow_entry": "INPUT_CHECK", "library_inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Xenium in situ subcellular spatial RNA transcriptomics input samplesheet?", "criteria": {"sample,image": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "field_constraint_bam_1_0", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_removeadapters_merge_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_REMOVEADAPTERS_MERGE", "modules": ["trimmomatic", "cutadapt", "trimgalore", "bbmap/bbduk", "leehom", "fastp", "adapterremoval", "cat/fastq"], "description": "Remove adapters and merge reads based on various module choices"}, "question": {"type": "choice", "instructions": "How should FASTQ_REMOVEADAPTERS_MERGE (trimmomatic, cutadapt, trimgalore, bbmap/bbduk, leehom, fastp, adapterremoval, cat/fastq) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_removeadapters_merge": null, "Local subworkflow FASTQ_REMOVEADAPTERS_MERGE": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_removeadapters_merge", "target_idx": 1}
{"id": "mod_hamronization_fargene_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize fARGene outputs using the hAMRonization specification (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ucsc_bedtobigbed": "Convert file from bed to bigBed format", "hamronization_abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "hamronization_fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "bio2zarr_vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster.", "hamronization_amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification."}}, "target": "hamronization_fargene", "target_idx": 2}
{"id": "pipe_all101_diaproteomics_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Automated quantitative analysis of DIA proteomics mass spectrometry measurements.. Topics: data-independent-proteomics, dia-proteomics, openms, proteomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": null, "isoseq": null, "eager": null, "mnaseseq": null, "diaproteomics": null, "mhcquant": null, "cageseq": null, "references": null}}, "target": "diaproteomics", "target_idx": 4}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_0_3", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "template": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,host_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_3_0", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Tumor-only somatic variant calling without matched normal with entry step FASTQC.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,normal,tumor": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_fastp_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_FASTP", "modules": ["fastqc", "umitools/extract", "fastp"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_FASTP (fastqc, umitools/extract, fastp) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_FASTQC_UMITOOLS_FASTP": null, "Use nf-core subworkflow fastq_fastqc_umitools_fastp": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_fastp", "target_idx": 3}
{"id": "mod_snpsift_annmem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-optimized indexed dataframes for high-performance annotation. (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsift/annmem": null, "bcftools/annotate": null, "ariba/run": null, "rgi/cardannotation": null, "aardvark/compare": null}}, "target": "snpsift/annmem", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_0_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_42", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bftools_showinf_1", "category": "resource_profiling", "state": {"process": "BFTOOLS_SHOWINF", "tool": "bftools/showinf", "description": "Extract OME xml data from OME-tif"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFTOOLS_SHOWINF (Extract OME xml data from OME-tif) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_sentieon_collectvcmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Accelerated implementation of the Picard CollectVariantCallingMetrics tool. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/collectvcmetrics": "Accelerated implementation of the Picard CollectVariantCallingMetrics tool.", "aria2": "CLI Download utility", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "multiqcsav": "Aggregate results from bioinformatics analyses across many samples into a single report, with support for mult"}}, "target": "sentieon/collectvcmetrics", "target_idx": 0}
{"id": "pipe_all101_pathogensurveillance_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Surveillance of pathogens using population genomics and sequencing. Topics: biosurveillance, pathogen-identification. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"variantbenchmarking": null, "viralmetagenome": null, "fetchngs": null, "pathogensurveillance": null, "rnavar": null}}, "target": "pathogensurveillance", "target_idx": 3}
{"id": "field_constraint_sex_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_5", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "field_constraint_status_1_14", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "samplesheet_arch_epigenomics_hic_0_3", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "template": "nf-core/hic"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hi-C chromosome conformation capture mapping?", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_4_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs?", "criteria": {"sample,fastq_1": null, "sample,bed": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_riker_multi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run multiple riker collectors in a single BAM pass using riker multi. Specify\ntools via ext.args (e.g. '--tools alignment basic isize'). The wgs, gcbias, and\nerror tools require a reference FASTA; the hybcap tool requires baits and targets. (tools: riker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "humann3/humann": "Functional analysis of metagenome or metatranscriptome data", "pasty": "Serogroup Pseudomonas aeruginosa assemblies", "riker/multi": "Run multiple riker collectors in a single BAM pass using riker multi. Specify\ntools via ext.args (e.g. '--tool", "atlas/splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "riker/multi", "target_idx": 3}
{"id": "resource_bcftools_index_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_INDEX", "tool": "bcftools/index", "description": "Index VCF tools"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_INDEX (Index VCF tools) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_3_1", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Fungal ITS1/ITS2 marker gene amplicon surveillance with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_barrnap_3", "category": "resource_profiling", "state": {"process": "BARRNAP", "tool": "barrnap", "description": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BARRNAP (barrnap uses a hmmer profile to find rrnas in reads or contig fasta files) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_fqtk_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex fastq files (tools: fqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bases2fastq": "Demultiplex Element Biosciences bases files", "idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "fqtk": "Demultiplex fastq files", "custom_getchromsizes": "Generates a FASTA file of chromosome sizes and a fasta index file", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs"}}, "target": "fqtk", "target_idx": 2}
{"id": "mod_localcdsearch_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A command-line tool for local protein domain annotation using NCBI's Conserved Domain Database (CDD) (tools: localcdsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"localcdsearch_annotate": "A command-line tool for local protein domain annotation using NCBI's Conserved Domain Database (CDD)", "localcdsearch_download": "A command-line tool for downloading databases for local protein domain annotation using NCBI's Conserved Domai", "bowtie2_align": "Align reads to a reference genome using bowtie2", "caalm_caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES", "meningotype": "Serotyping of Neisseria meningitidis assemblies"}}, "target": "localcdsearch_annotate", "target_idx": 0}
{"id": "mod_fasta_hmmsearch_rank_fastas_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hmmsearch and output separate fasta files for top scoring hits to each profile (tools: fasta_hmmsearch_rank_fastas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eklipse": null, "hmmer/eslsfetchindex": null, "fasta_hmmsearch_rank_fastas": null, "viennarna/rnacofold": null, "hmmer/eslreformat": null}}, "target": "fasta_hmmsearch_rank_fastas", "target_idx": 2}
{"id": "resource_atlas_recal_4", "category": "resource_profiling", "state": {"process": "ATLAS_RECAL", "tool": "atlas/recal", "description": "Gives an estimation of the sequencing bias based on known invariant sites"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_RECAL (Gives an estimation of the sequencing bias based on known invariant sites) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_simpleaf_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Indexing of transcriptome for gene expression quantification using SimpleAF (tools: simpleaf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi", "mmseqs/cluster": "Cluster sequences using MMSeqs2 cluster.", "gt/gff3validator": "GenomeTools gt-gff3validator utility to strictly validate a GFF3 file", "nanocomp": "Compare multiple runs of long read sequencing data and alignments", "simpleaf/index": "Indexing of transcriptome for gene expression quantification using SimpleAF"}}, "target": "simpleaf/index", "target_idx": 4}
{"id": "samplesheet_arch_viral_amplicon_artic_5_4", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral amplicon sequencing with primers.", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_force_tileextent_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute valid tiles for a given datacube definition and area of interest.\nThis list can be used by downstream analysis tasks to limit processing to the area of interest when satellite data covers a larger region. (tools: force)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"force_cube": "Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spat", "finaletoolkit_delfi": "Calculate the DELFI scores (Cristiano et al., 2019) from a BAM file.", "civicpy_annotate": "A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations o", "force_tileextent": "Compute valid tiles for a given datacube definition and area of interest.\nThis list can be used by downstream ", "staphopiasccmec": "Predicts Staphylococcus aureus SCCmec type based on primers."}}, "target": "force_tileextent", "target_idx": 3}
{"id": "noul_confusing_combine_with_mix_semantics_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bcftools_query_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_QUERY", "tool": "bcftools/query", "description": "Extracts fields from VCF or BCF files and outputs them in user-defined format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_QUERY (Extracts fields from VCF or BCF files and outputs them in user-defined format.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_biscuit_vcf2bed_2", "category": "resource_profiling", "state": {"process": "BISCUIT_VCF2BED", "tool": "biscuit/vcf2bed", "description": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_VCF2BED (Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compl) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "local_subworkflow_preparereports_0_2", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "How should PREPAREREPORTS (custom/preparereports, multiqc) be built?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow preparereports": null, "Local subworkflow PREPAREREPORTS": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 3}
{"id": "resource_bamstats_generalstats_2", "category": "resource_profiling", "state": {"process": "BAMSTATS_GENERALSTATS", "tool": "bamstats/generalstats", "description": "write your description here"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMSTATS_GENERALSTATS (write your description here) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_diseasemodulediscovery_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diseasemodulediscovery", "assay": "diseasemodulediscovery pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/diseasemodulediscovery (A pipeline for network-based disease module identification.)?", "criteria": {"seeds,network,perturbed_networks": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "seeds,network,perturbed_networks", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/methylseq --input samplesheet.csv (Assay: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq))", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_4_3", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs with pedigree relationships and affected status?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_executor_support_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_fetch_clean_hostile_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FETCH_CLEAN_HOSTILE", "modules": ["hostile/fetch", "hostile/clean"], "description": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files"}, "question": {"type": "choice", "instructions": "How should FASTQ_FETCH_CLEAN_HOSTILE (hostile/fetch, hostile/clean) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_fetch_clean_hostile": null, "Local subworkflow FASTQ_FETCH_CLEAN_HOSTILE": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_fetch_clean_hostile", "target_idx": 0}
{"id": "subworkflow_pkg_differential_functional_enrichment_0", "category": "subworkflow_packaging", "state": {"subworkflow": "DIFFERENTIAL_FUNCTIONAL_ENRICHMENT", "modules": ["gprofiler2/gost", "gsea/gsea", "decoupler/decoupler", "propr/grea", "custom/tabulartogseagct", "custom/tabulartogseacls", "custom/tabulartogseachip"], "description": "Run functional analysis on differential abundance analysis output"}, "question": {"type": "choice", "instructions": "How should DIFFERENTIAL_FUNCTIONAL_ENRICHMENT (gprofiler2/gost, gsea/gsea, decoupler/decoupler, propr/grea, custom/tabulartogseagct, custom/tabulartogseacls, custom/tabulartogseachip) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow DIFFERENTIAL_FUNCTIONAL_ENRICHMENT": null, "Use nf-core subworkflow differential_functional_enrichment": null}}, "target": "Use nf-core subworkflow differential_functional_enrichment", "target_idx": 3}
{"id": "resource_bedtools_makewindows_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAKEWINDOWS", "tool": "bedtools/makewindows", "description": "Makes adjacent or sliding windows across a genome or BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAKEWINDOWS (Makes adjacent or sliding windows across a genome or BED file.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_cageseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for cage. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]"}}, "target": "cageseq", "target_idx": 5}
{"id": "mod_mtnucratio_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A small Java tool to calculate ratios between MT and nuclear sequencing reads in a given BAM file. (tools: mtnucratio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiara/tiara": "Domain-level classification of contigs to bacterial, archaeal, eukaryotic, or organelle", "mtnucratio": "A small Java tool to calculate ratios between MT and nuclear sequencing reads in a given BAM file.", "fastdup": "FastDup is a tool designed to locate and tag duplicate reads in a coordinate-sorted SAM or BAM file, using the", "authentict/deam2cont": "Use deamination patterns to estimate contamination in single-stranded libraries", "seqkit/head": "Subset FASTA/FASTQ files to some number of sequences"}}, "target": "mtnucratio", "target_idx": 1}
{"id": "resource_bcftools_pluginfixploidy_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFIXPLOIDY", "tool": "bcftools/pluginfixploidy", "description": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFIXPLOIDY (The fixploidy plugin fixes ploidy in genotype fields according to specified ploi) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_taxpasta_standardise_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Standardise the output of a wide range of taxonomic profilers (tools: taxpasta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "taxpasta/standardise": "Standardise the output of a wide range of taxonomic profilers", "pairtools/sort": "Sort a .pairs/.pairsam file", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "qualimap/bamqc": "Evaluate alignment data"}}, "target": "taxpasta/standardise", "target_idx": 1}
{"id": "resource_agat_spstatistics_3", "category": "resource_profiling", "state": {"process": "AGAT_SPSTATISTICS", "tool": "agat/spstatistics", "description": "Provides different type of statistics in text format from a GFF/GTF annotation file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPSTATISTICS (Provides different type of statistics in text format from a GFF/GTF annotation f) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_finaletoolkit_aggbw_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aggregates a bigWig signal over constant-length intervals\ndefined in a BED file. (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit/aggbw": null, "agat/spfilterfeaturefromkilllist": null, "agat/spmergeannotations": null, "picard/collectwgsmetrics": null, "leafcutter/differentialsplicing": null}}, "target": "finaletoolkit/aggbw", "target_idx": 0}
{"id": "pipe_all101_hicar_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.. Topics: atac, atac-seq, hic, hicar, multi-omics, transcriptome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bamtofastq": null, "cutandrun": null, "differentialabundance": null, "cageseq": null, "multiplesequencealign": null, "hicar": null, "oncoanalyser": null, "readsimulator": null}}, "target": "hicar", "target_idx": 5}
{"id": "mod_bracken_combinebrackenoutputs_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine output of metagenomic samples analyzed by bracken. (tools: bracken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_build_add_kraken2_bracken": null, "vcf2maf": null, "bracken_combinebrackenoutputs": null, "dedup": null, "bracken_build": null}}, "target": "bracken_combinebrackenoutputs", "target_idx": 2}
{"id": "mod_fasta_index_dna_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate aligner index for a reference genome.\nPlease note, this workflow requires input CHANNELS. Input values will cause errors (tools: fasta_index_dna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "pbtk_pbindex": "Minimalistic tool which creates an index file that enables random access into PacBio BAM files", "fasta_index_dna": "Generate aligner index for a reference genome.\nPlease note, this workflow requires input CHANNELS. Input value", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}}, "target": "fasta_index_dna", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Standard Paired-end Whole Genome Sequencing (WGS))", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_glimpse2_splitreference_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to create a binary reference panel for quick reading time. (tools: glimpse2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/fq2fa": "Convert FASTQ to FASTA format", "glimpse2/splitreference": "Tool to create a binary reference panel for quick reading time.", "fqtk": "Demultiplex fastq files", "bedtools/split": "Split BED files into several smaller BED files", "csvtk/split": "Splits CSV/TSV into multiple files according to column values"}}, "target": "glimpse2/splitreference", "target_idx": 1}
{"id": "resource_agat_spfilterbyorfsize_2", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERBYORFSIZE", "tool": "agat/spfilterbyorfsize", "description": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF passing the test, the other contains the rest. By default the test is \"> 100\" that means all gene models that have ORF longer than 100 Amino acids, will pass the test."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERBYORFSIZE (The script reads a gff annotation file, and create two output files, one contain) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_wget_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The non-interactive network downloader (tools: wget)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vclust_prefilter": "The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by ", "octopusv_correct": "Standardize a caller VCF into OctopuSV SVCF format.", "blast_updateblastdb": "Downloads a BLAST database from NCBI", "wget": "The non-interactive network downloader", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo"}}, "target": "wget", "target_idx": 3}
{"id": "mod_qualimap_bamqccram_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment data (tools: qualimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco/plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "qualimap/bamqccram": "Evaluate alignment data", "busco/busco": "Benchmarking Universal Single Copy Orthologs", "nanoplot": "Run NanoPlot on nanopore-sequenced reads", "fastqscreen/fastqscreen": "Align reads to multiple reference genomes using fastq-screen"}}, "target": "qualimap/bamqccram", "target_idx": 1}
{"id": "mod_gatk4_denoisereadcounts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Denoises read counts to produce denoised copy ratios (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/denoisereadcounts": "Denoises read counts to produce denoised copy ratios", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "scoary": "Use pangenome outputs for GWAS", "gatk4/modelsegments": "Converts copy number ratios (and optonally allelic counts) to copy number segments", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "gatk4/denoisereadcounts", "target_idx": 0}
{"id": "mod_gens_preparecovandbaf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tools for preparing inputs for visualization in Gens (tools: gens)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sequali": null, "cellsnp/modea": null, "gens/preparecovandbaf": null, "pharmcat/vcfpreprocessor": null, "humann3/regroup": null}}, "target": "gens/preparecovandbaf", "target_idx": 2}
{"id": "mod_tabix_bgziptabix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix index (tools: tabix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tabix/bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files", "htslib/bgziptabix": "Multi-purpose module to compress, decompress and index files using bgzip and tabix.", "tabix/bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde", "custom/tabulartogseacls": "Make a GSEA class file (.cls) from tabular inputs", "epang/place": "phylogenetic placement of query sequences in a reference tree"}}, "target": "tabix/bgziptabix", "target_idx": 2}
{"id": "mod_picard_markduplicates_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Locate and tag duplicate reads in a BAM file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_markduplicates": null, "ngsbits_bedannotategc": null, "bam_variant_demix_boot_freyja": null, "picard_markduplicates": null, "dupblaster": null}}, "target": "picard_markduplicates", "target_idx": 3}
{"id": "mod_gatk4_variantfiltration_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter variants (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"merquryfk/merquryfk": null, "parsesdrf/convert": null, "arcane/filter": null, "gatk4/variantfiltration": null, "agat/spfilterbyorfsize": null}}, "target": "gatk4/variantfiltration", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_13", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_0_1", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1": null, "sample,tss_bed": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "noul_executor_support_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_26", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_pbcpgtools_alignedbamtocpgscores_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts aligned BAM files into CpG methylation scores (tools: pbcpgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbcpgtools/alignedbamtocpgscores": "Converts aligned BAM files into CpG methylation scores", "bowtie2/build": "Builds bowtie index for reference genome", "bismark/align": "Performs alignment of BS-Seq reads using bismark", "picard/createsequencedictionary": "Creates a sequence dictionary for a reference sequence.", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali"}}, "target": "pbcpgtools/alignedbamtocpgscores", "target_idx": 0}
{"id": "mod_lofreq_somatic_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to call low frequency variants from alignments when tumor-normal paired samples are available (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yak_count": null, "lofreq_somatic": null, "bcftools_consensus": null, "aardvark_compare": null, "cellrangerarc_count": null}}, "target": "lofreq_somatic", "target_idx": 1}
{"id": "mod_gangstr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GangSTR is a tool for genome-wide profiling tandem repeats from short reads. (tools: gangstr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"somalier/extract": null, "expansionhunter": null, "crisprcleanr/normalize": null, "gangstr": null, "expansionhunterdenovo/merge": null}}, "target": "gangstr", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_0_3", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "template": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_5", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_39", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_named_process_output_emits_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_phenotype_0_8", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"format: file-path": null, "type: string free-text": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "mod_glimpse_sample_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates haplotype calls by sampling haplotype estimates (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse/sample": null, "gprofiler2/gost": null, "eagle2": null, "gunc/downloaddb": null, "qcat": null}}, "target": "glimpse/sample", "target_idx": 0}
{"id": "pipe_all101_callingcards_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline for processing calling cards data. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "callingcards": "A pipeline for processing calling cards data", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]"}}, "target": "callingcards", "target_idx": 5}
{"id": "mod_decoupler_decoupler_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: decoupler is a package containing different statistical methods\nto extract biological activities from omics data within a unified framework.\nIt allows to flexibly test any enrichment method with any prior knowledge\nresource and incorporates methods that take into account the sign and weight.\nIt can be used with any omic, as long as its features can be linked to a\nbiological process based on prior knowledge. For example, in transcriptomics\ngene sets regulated by a transcription factor, or in phospho-proteomics\nphosphosites that are targeted by a kinase. (tools: decoupler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"decoupler_decoupler": "decoupler is a package containing different statistical methods\nto extract biological activities from omics da", "gens_preparecovandbaf": "Tools for preparing inputs for visualization in Gens", "fcs_fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi", "goatools_findenrichment": "Find enriched GO terms in a list of genes", "gsea_gsea": "run the Broad Gene Set Enrichment tool in GSEA mode"}}, "target": "decoupler_decoupler", "target_idx": 0}
{"id": "field_constraint_sample_0_5", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"enum: [0, 1]": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "field_constraint_bam_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bam", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bam'.", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_4_2", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification?", "criteria": {"sample,bed": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_pharokka_pharokka_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functional annotation of phages (tools: pharokka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whatshap/stats": "Compute statistics from phased variant file using Whatshap", "genomad/endtoend": "Identify mobile genetic elements present in genomic assemblies", "last/split": "Find split or spliced alignments in a MAF file", "pharokka/pharokka": "Functional annotation of phages", "genomad/download": "Download geNomad databases and related files"}}, "target": "pharokka/pharokka", "target_idx": 3}
{"id": "resource_bcftools_split_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SPLIT", "tool": "bcftools/split", "description": "Split a vcf file into files per chromosome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SPLIT (Split a vcf file into files per chromosome) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_rnafusion_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: RNA-seq analysis pipeline for detection of gene-fusions. Topics: fusion, fusion-genes, gene-fusion, rna, rna-seq. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples"}}, "target": "rnafusion", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_6_5", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns are standard for ChIP-seq with IP and input control design input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "mod_fgbio_zipperbams_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metaeuk/easypredict": "Annotation of eukaryotic metagenomes using MetaEuk", "fgbio/callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "fgbio/zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "fastq_create_umi_consensus_fgbio": "This workflow uses the suite FGBIO to identify and remove UMI tags from FASTQ reads\nconvert them to unmapped B", "famsa/align": "Aligns sequences using FAMSA"}}, "target": "fgbio/zipperbams", "target_idx": 2}
{"id": "mod_pbccs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pacbio ccs - Generate Highly Accurate Single-Molecule Consensus Reads (tools: pbccs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt/hifiadapterfilt": null, "mash/dist": null, "isoseq/refine": null, "pbccs": null, "dshbio/splitgff3": null}}, "target": "pbccs", "target_idx": 3}
{"id": "local_subworkflow_checkirma_0_4", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should CHECKIRMA (custom/checkirma) be built?", "criteria": {"Use nf-core subworkflow checkirma": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "mod_samplesheetparser_diff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff covering header changes, added/removed\nsamples, and per-sample field changes. Exits 0 if identical, 1 if\ndifferences are detected — useful as a CI pre-run guard. (tools: samplesheet-parser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamaps/mapdirectly": "Maps long reads to a metamaps database", "samplesheetparser/diff": "Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff cove", "bcl2fastq": "Demultiplex Illumina BCL files", "cellranger/mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command.", "plink/exclude": "Exclude variant identifiers from plink bfiles"}}, "target": "samplesheetparser/diff", "target_idx": 1}
{"id": "samplesheet_arch_cageseq_transcription_2_4", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping", "pipeline": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,tss_bed": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_snpsift_annmem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-optimized indexed dataframes for high-performance annotation. (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"upp_align": "Aligns protein structures using UPP", "atlas_call": "generate VCF file from a BAM file using various calling methods", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "picard_collectinsertsizemetrics": "Collect metrics about the insert size distribution of a paired-end library.", "snpsift_annmem": "Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-opt"}}, "target": "snpsift_annmem", "target_idx": 4}
{"id": "field_constraint_strandedness_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"type: boolean": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "subworkflow_pkg_bam_cnv_wisecondorx_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CNV_WISECONDORX", "modules": ["wisecondorx/convert", "wisecondorx/predict"], "description": "A subworkflow for calling CNVs using WisecondorX"}, "question": {"type": "choice", "instructions": "How should BAM_CNV_WISECONDORX (wisecondorx/convert, wisecondorx/predict) be structured in DSL2?", "criteria": {"Local subworkflow BAM_CNV_WISECONDORX": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_cnv_wisecondorx": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_cnv_wisecondorx", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay_type": "16S rRNA / ITS microbiome amplicon profiling", "data_format": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for 16S rRNA / ITS microbiome amplicon profiling input samplesheet?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fasta": null, "sample,otu_table": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_channel_operator_map_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_hicap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify cap locus serotype and structure in your Haemophilus influenzae assemblies (tools: hicap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylphtax/merge": "Merge multiple taxonomic profiles from sylphtaxt/taxprof into a tsv table", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "transdecoder/predict": "TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. Yo", "hicap": "Identify cap locus serotype and structure in your Haemophilus influenzae assemblies", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "hicap", "target_idx": 3}
{"id": "mod_isoseq_refine_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove polyA tail and artificial concatemers (tools: isoseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq/refine": null, "cooltools/insulation": null, "gstama/collapse": null, "isoseq/cluster": null, "bam_telomere_estimation": null}}, "target": "isoseq/refine", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_8_4", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "PBMM2_ALIGN", "library_inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "mod_odgi_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct a dynamic succinct variation graph in ODGI format from a GFAv1. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mlst": "Run Torsten Seemann's classic MLST on a genome assembly", "odgi/draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "velocyto": "Velocyto is a library for the analysis of RNA velocity. velocyto.py CLI use\n`Path(resolve_path=True)` and brea", "odgi/layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "odgi/build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1."}}, "target": "odgi/build", "target_idx": 4}
{"id": "samplesheet_arch_viral_amplicon_artic_2_4", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_reportho_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for ortholog analysis? Specific context: nf-core pipeline for comparative analysis of ortholog predictions. Topics: ortholog. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]"}}, "target": "reportho", "target_idx": 8}
{"id": "schema_std_pathogensurveillance_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pathogensurveillance", "description": "Surveillance of pathogens using population genomics and sequencing", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pathogensurveillance?", "criteria": {"sample,type,level,msfile": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "sample_id,name,description,path,path_2", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_gtf_bam_rpbp_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_GTF_BAM_RPBP", "modules": ["rpbp/preparegenome", "rpbp/extractmetageneprofiles", "rpbp/estimatemetagenebayesfactors", "rpbp/selectperiodicoffsets", "rpbp/getperiodiclengthsoffsets", "rpbp/extractorfprofiles", "rpbp/estimateorfbayesfactors", "rpbp/selectfinalpredictionset"], "description": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data"}, "question": {"type": "choice", "instructions": "How should FASTA_GTF_BAM_RPBP (rpbp/preparegenome, rpbp/extractmetageneprofiles, rpbp/estimatemetagenebayesfactors, rpbp/selectperiodicoffsets, rpbp/getperiodiclengthsoffsets, rpbp/extractorfprofiles, rpbp/estimateorfbayesfactors, rpbp/selectfinalpredictionset) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_GTF_BAM_RPBP": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fasta_gtf_bam_rpbp": null}}, "target": "Use nf-core subworkflow fasta_gtf_bam_rpbp", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_3_0", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Xenium in situ subcellular spatial RNA transcriptomics with entry step INPUT_CHECK.", "criteria": {"sample,image": null, "sample,vcf": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_2_0", "category": "samplesheet_schema", "state": {"technology": "3D Chromatin Structure", "workflow_entry": "FASTQC", "library_inputs": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,matrix,contacts": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bbmap_bbnorm_4", "category": "resource_profiling", "state": {"process": "BBMAP_BBNORM", "tool": "bbmap/bbnorm", "description": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result in a flat coverage distribution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBNORM (BBNorm is designed to normalize coverage by down-sampling reads over high-depth ) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_cellpose_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: cellpose segments cells in images using GPU-accelerated deep learning (tools: cellpose)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ilastik/multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "holodeck/eval": "Evaluate alignment accuracy of holodeck-simulated reads", "hiphase": "Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across ", "ilastik/pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning"}}, "target": "cellpose", "target_idx": 4}
{"id": "subworkflow_pkg_vcf_gather_bcftools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_GATHER_BCFTOOLS", "modules": ["bcftools/sort", "bcftools/concat", "htslib/bgziptabix"], "description": "Concatenate several VCF files using bcftools concat."}, "question": {"type": "choice", "instructions": "How should VCF_GATHER_BCFTOOLS (bcftools/sort, bcftools/concat, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow vcf_gather_bcftools": null, "Local subworkflow VCF_GATHER_BCFTOOLS": null}}, "target": "Use nf-core subworkflow vcf_gather_bcftools", "target_idx": 2}
{"id": "mod_bismark_genomepreparation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "bam2fastx/bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bismark/report": "Collects bismark alignment reports"}}, "target": "bismark/genomepreparation", "target_idx": 3}
{"id": "pipe_all101_demo_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for demo. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab"}}, "target": "demo", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_se_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Single-end Illumina RNA-seq with strandedness. Input files: Single-end FASTQ reads per library.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "resource_angsd_realsfs_1", "category": "resource_profiling", "state": {"process": "ANGSD_REALSFS", "tool": "angsd/realsfs", "description": "Estimate site frequency spectrum from site allele frequencies"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_REALSFS (Estimate site frequency spectrum from site allele frequencies) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_vcflib_vcfbreakmulti_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: If multiple alleles are specified in a single record, break the record into several lines preserving allele-specific INFO fields (tools: vcflib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem3_mem": "Align fastq reads to a fasta reference using bwa-mem3", "cdhit_cdhit": "Cluster protein sequences using sequence similarity", "vcflib_vcffixup": "Generates a VCF stream where AC and NS have been generated for each record using sample genotypes.", "vcflib_vcfbreakmulti": "If multiple alleles are specified in a single record, break the record into several lines preserving allele-sp", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "vcflib_vcfbreakmulti", "target_idx": 3}
{"id": "resource_amulety_translate_0", "category": "resource_profiling", "state": {"process": "AMULETY_TRANSLATE", "tool": "amulety/translate", "description": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_TRANSLATE (A module to translate BCR and TCR nucleotide sequences into amino acid sequences) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_evexplorer_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/evexplorer", "assay": "evexplorer pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/evexplorer (nf-core/evexplorer is a pipeline for analyzing RNA data from)?", "criteria": {"id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,batch,condition": null, "sample,tools,file,index": null, "patient,sample,vcf,status,cna": null}}, "target": "sample,fastq_1,fastq_2,batch,condition", "target_idx": 1}
{"id": "mod_pretextmap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converts sam/bam/cram/pairs into genome contact map (tools: pretextmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crispresso2": null, "atlas_pmd": null, "pretextmap": null, "bamaligncleaner": null, "rsem_calculateexpression": null}}, "target": "pretextmap", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diaproteomics", "assay_type": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "data_format": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,fasta": null, "sample,mzml": null, "sample,peptides_tsv": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "mod_slamdunk_all_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification (tools: slamdunk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "perbase": "Per-base metrics on BAM/CRAM files.", "slamdunk_all": "Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification", "arriba_visualisation": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "zip": "Compress file lists to produce ZIP archive files"}}, "target": "slamdunk_all", "target_idx": 2}
{"id": "mod_utils_nfschema_plugin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run nf-schema to validate parameters and create a summary of changed parameters (tools: utils_nfschema_plugin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nfschema_plugin": null, "bam_markduplicates_samtools": null, "gffread": null, "openms/peptideindexer": null, "ferrohgvs/parse": null}}, "target": "utils_nfschema_plugin", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_7", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_bowtie2_build_1", "category": "resource_profiling", "state": {"process": "BOWTIE2_BUILD", "tool": "bowtie2/build", "description": "Builds bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_BUILD (Builds bowtie index for reference genome) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_49", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "data_format": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multiplexed Oxford Nanopore run with barcode demultiplexing input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "mod_gappa_examineheattree_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: colours a phylogeny with placement densities (tools: gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"epang_place": null, "gappa_examineheattree": null, "windowmasker_ustat": null, "cafe": null, "rastair_mbiasparser": null}}, "target": "gappa_examineheattree", "target_idx": 1}
{"id": "mod_quantmsutils_mzmlstatistics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate statistics from mzML files using quantms-utils (tools: quantms-utils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quantmsutils/diann2mztab": "Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils", "srst2/srst2": "Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLS", "quantmsutils/dianncfg": "Generate DIA-NN configuration arguments from enzyme and Unimod modification parameters.\nThis module uses quant", "quantmsutils/mzmlstatistics": "Generate statistics from mzML files using quantms-utils", "fgbio/callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag."}}, "target": "quantmsutils/mzmlstatistics", "target_idx": 3}
{"id": "mod_nextgenmap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using NextGenMap (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nonpareil/nonpareil": "Calculate metagenome redundancy curve from FASTQ files", "plink2/pca": "Perform PCA analysis using PLINK", "bwa/mem": "Performs fastq alignment to a fasta reference using BWA", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "nextgenmap": "Performs fastq alignment to a fasta reference using NextGenMap"}}, "target": "nextgenmap", "target_idx": 4}
{"id": "mod_hifiadapterfilt_hifiadapterfilt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ output, filtering statistics, BLAST hits,\nand a list of blocked read IDs. (tools: hifiadapterfilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt_hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "bismark_align": "Performs alignment of BS-Seq reads using bismark", "bcftools_pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "bam2fastx_bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "hifiasm": "Whole-genome assembly using PacBio HiFi reads"}}, "target": "hifiadapterfilt_hifiadapterfilt", "target_idx": 0}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_gatk_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/learnreadorientationmodel", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/learnreadorientationmodel, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK": null, "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_1_2", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform", "pipeline": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_fastqrepair_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, and settles reads that became disordered. Topics: corruption, data-cleaning, data-recovery, fastq, fastq-corrupted, fastq-format. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"longraredisease": null, "viralmetagenome": null, "fastqrepair": null, "viralrecon": null, "rnasplice": null, "methylong": null, "rnadnavar": null, "ribomsqc": null, "hgtseq": null, "bacass": null}}, "target": "fastqrepair", "target_idx": 2}
{"id": "noul_deprecated_dsl1_set_keyword_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_bbmap_bbmerge_3", "category": "resource_profiling", "state": {"process": "BBMAP_BBMERGE", "tool": "bbmap/bbmerge", "description": "Merging overlapping paired reads into a single read."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBMERGE (Merging overlapping paired reads into a single read.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_taxprofiler_shotgun_0_4", "category": "samplesheet_schema", "state": {"technology": "Metagenomics Profiling", "workflow_entry": "FASTQC", "library_inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,fastq_1": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_39", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_calder2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Hierarchical Hi-C compartment computation (tools: calder2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "topas/gencons": "Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage presen", "calder2": "Hierarchical Hi-C compartment computation", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "abyss/abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}}, "target": "calder2", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_6_5", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Visium spatial transcriptomics with histology image input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null, "sample,fastq_1,image": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "mod_jvarkit_wgscoverageplotter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot whole genome coverage from BAM/CRAM file as SVG (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"homer/annotatepeaks": "Annotate peaks with HOMER suite", "jvarkit/wgscoverageplotter": "Plot whole genome coverage from BAM/CRAM file as SVG", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "svaba": "SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide ", "atlas/splitmerge": "split single end read groups by length and merge paired end reads"}}, "target": "jvarkit/wgscoverageplotter", "target_idx": 1}
{"id": "mod_rtgtools_svdecompose_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_leftalignandtrimvariants": "Left align and trim variants using GATK4 LeftAlignAndTrimVariants.", "rtgtools_svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs", "cooler_cload": "Create a cooler from genomic pairs and bins", "octopusv_correct": "Standardize a caller VCF into OctopuSV SVCF format.", "delly_call": "Call structural variants"}}, "target": "rtgtools_svdecompose", "target_idx": 1}
{"id": "noul_channel_join_operator_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_gtf_bam_rpbp_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_GTF_BAM_RPBP", "modules": ["rpbp/preparegenome", "rpbp/extractmetageneprofiles", "rpbp/estimatemetagenebayesfactors", "rpbp/selectperiodicoffsets", "rpbp/getperiodiclengthsoffsets", "rpbp/extractorfprofiles", "rpbp/estimateorfbayesfactors", "rpbp/selectfinalpredictionset"], "description": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data"}, "question": {"type": "choice", "instructions": "How should FASTA_GTF_BAM_RPBP (rpbp/preparegenome, rpbp/extractmetageneprofiles, rpbp/estimatemetagenebayesfactors, rpbp/selectperiodicoffsets, rpbp/getperiodiclengthsoffsets, rpbp/extractorfprofiles, rpbp/estimateorfbayesfactors, rpbp/selectfinalpredictionset) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_gtf_bam_rpbp": null, "Local subworkflow FASTA_GTF_BAM_RPBP": null}}, "target": "Use nf-core subworkflow fasta_gtf_bam_rpbp", "target_idx": 2}
{"id": "resource_bioawk_0", "category": "resource_profiling", "state": {"process": "BIOAWK", "tool": "bioawk", "description": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOAWK (Bioawk is an extension to Brian Kernighan's awk, adding the support of several c) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gatk4_preprocessintervals_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepares bins for coverage collection. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "controlfreec_makegraph": "Plot Freec output", "gatk4_preprocessintervals": "Prepares bins for coverage collection.", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "gatk4_preprocessintervals", "target_idx": 2}
{"id": "mod_gem3_gem3indexer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a GEM index from a FASTA file (tools: gem3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem3_gem3indexer": null, "art_illumina": null, "ariba_run": null, "krona_ktimporttaxonomy": null, "souporcell": null}}, "target": "gem3_gem3indexer", "target_idx": 0}
{"id": "mod_transdecoder_longorf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TransDecoder identifies candidate coding regions within transcript sequences. it is used to build gff file. (tools: transdecoder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "meningotype": "Serotyping of Neisseria meningitidis assemblies", "metamdbg/asm": "Metagenome assembler for long-read sequences (HiFi and ONT).", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "transdecoder/longorf": "TransDecoder identifies candidate coding regions within transcript sequences. it is used to build gff file."}}, "target": "transdecoder/longorf", "target_idx": 4}
{"id": "resource_bedtools_multiinter_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MULTIINTER", "tool": "bedtools/multiinter", "description": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MULTIINTER (Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_37", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_retry_errorstrategy_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "schema_std_variantprioritization_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/variantprioritization", "description": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR).", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/variantprioritization?", "criteria": {"patient,sample,vcf,status,cna": null, "ID,R1,R2,LongFastQ,Fast5": null, "id,fasta": null, "condition,type,microbiome_path,alleles,weights_path": null}}, "target": "patient,sample,vcf,status,cna", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_36", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_rnasplice_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for alternative-splicing analysis? Specific context: rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis. Topics: alternative-splicing, rna, rna-seq, splicing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]"}}, "target": "rnasplice", "target_idx": 4}
{"id": "resource_biscuit_vcf2bed_3", "category": "resource_profiling", "state": {"process": "BISCUIT_VCF2BED", "tool": "biscuit/vcf2bed", "description": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_VCF2BED (Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compl) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_samplesheetparser_diff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff covering header changes, added/removed\nsamples, and per-sample field changes. Exits 0 if identical, 1 if\ndifferences are detected — useful as a CI pre-run guard. (tools: samplesheet-parser)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ldak_thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "cellranger_mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command.", "samplesheetparser_diff": "Compare two Illumina SampleSheet.csv files (any combination of V1 and V2)\nand emit a structured JSON diff cove", "cellrangerarc_mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma", "bam_split_by_region": "Split the reads in the input bam by specified genomic region."}}, "target": "samplesheetparser_diff", "target_idx": 2}
{"id": "resource_bioformats2raw_4", "category": "resource_profiling", "state": {"process": "BIOFORMATS2RAW", "tool": "bioformats2raw", "description": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOFORMATS2RAW (Java application to convert image file formats, including .mrxs, to an intermedi) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "local_subworkflow_daisribosome_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should this step (dais) be packaged: Custom ribosomal frameshift translation analysis?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow DAISRIBOSOME": null, "Leave them out": null, "Use nf-core subworkflow daisribosome": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 1}
{"id": "samplesheet_arch_ont_demux_barcodes_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "data_format": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Nanopore sequencing run with sample to barcode assignment and flowcell type?", "criteria": {"sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Trio exome/genome sequencing (Proband, Mother, Father)", "data_format": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Trio exome/genome sequencing (Proband, Mother, Father) with entry step FASTQC.", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "pipe_all101_rnastructurome_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for dms. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo"}}, "target": "rnastructurome", "target_idx": 2}
{"id": "mod_hmmcopy_mapcounter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a bigwig file (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/antitarget": "Derive off-target (“antitarget”) bins from target regions.", "hmmcopy/mapcounter": "mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a big", "canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "gtdbtk/gtdbtoncbimajorityvote": "Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy", "td2/predict": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se"}}, "target": "hmmcopy/mapcounter", "target_idx": 1}
{"id": "resource_ampcombi2_complete_5", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_COMPLETE", "tool": "ampcombi2/complete", "description": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_COMPLETE (A submodule that merges all output summary tables from ampcombi/parsetables in o) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_pangenome_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609.. Topics: pangenome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": null, "slamseq": null, "genomeassembler": null, "cageseq": null, "rnafusion": null, "reportho": null, "marsseq": null, "pangenome": null, "pairgenomealign": null, "fastquorum": null}}, "target": "pangenome", "target_idx": 7}
{"id": "samplesheet_arch_taxprofiler_shotgun_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/taxprofiler", "assay_type": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "data_format": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,kraken_db": null, "sample,fastq_1": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bedtools_shift_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHIFT", "tool": "bedtools/shift", "description": "Shifts each feature by specific number of bases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHIFT (Shifts each feature by specific number of bases) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_fasta_vclust_prefilter_align_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter\nof candidate sequence pairs with `vclust prefilter`, 2) compute pairwise\nalignments and similarity metrics with `vclust align`, and 3) generate\nthreshold-based clusters with `vclust cluster`. (tools: fasta_vclust_prefilter_align_cluster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"raw2ometiff": "write your description here", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "bam_docounts_contamination_angsd": "Calculate contamination of the X-chromosome with ANGSD", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "fasta_vclust_prefilter_align_cluster": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter\nof candidate sequence pairs with `v"}}, "target": "fasta_vclust_prefilter_align_cluster", "target_idx": 4}
{"id": "samplesheet_arch_proteomics_dia_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/diaproteomics --input samplesheet.csv (Assay: Data-Independent Acquisition (DIA) quantitative mass spectrometry)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,peptides_tsv": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_2_0", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "NANOPLOT", "library_inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_26", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_1_4", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "pipe_all101_callingcards_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for callingcards analysis? Specific context: A pipeline for processing calling cards data. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "callingcards": "A pipeline for processing calling cards data", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-"}}, "target": "callingcards", "target_idx": 4}
{"id": "mod_custom_rsemmergecounts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge per-sample RSEM results into wide and long format TSV matrices (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"idr": null, "custom_rsemmergecounts": null, "custom_tx2gene": null, "taxonkit_list": null, "sentieon_rsempreparereference": null}}, "target": "custom_rsemmergecounts", "target_idx": 1}
{"id": "intent_build_pipeline_22", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "mod_custom_addmostsevereconsequence_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate a VEP annotated VCF with the most severe consequence field (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv_annotsv": "Annotation and Ranking of Structural Variation", "plastid_metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "pydamage_filter": "Damage parameter estimation for ancient DNA", "custom_addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field"}}, "target": "custom_addmostsevereconsequence", "target_idx": 4}
{"id": "pipe_all101_viralintegration_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach.. Topics: chimeric-alignment, ctat, viral-integration, virus, virusintegrationfinder. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "seqsubmit": "nf-core pipeline for data submission to ENA", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d"}}, "target": "viralintegration", "target_idx": 4}
{"id": "mod_coptr_map_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Maps the reads to the reference database (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr/map": "Maps the reads to the reference database", "odgi/view": "Project a graph into other formats.", "coptr/estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "kmcp/profile": "Generate taxonomic profile from search results", "coptr/merge": "Merge reads that were mapped to multiple indices"}}, "target": "coptr/map", "target_idx": 0}
{"id": "mod_gamma_gamma_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gene Allele Mutation Microbial Assessment (tools: gamma)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_combinegvcfs": null, "gamma_gamma": null, "prodigal": null, "qualimap_rnaseq": null, "allelecounter": null}}, "target": "gamma_gamma", "target_idx": 1}
{"id": "mod_bedtools_makewindows_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Makes adjacent or sliding windows across a genome or BED file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"localcdsearch_download": "A command-line tool for downloading databases for local protein domain annotation using NCBI's Conserved Domai", "bedtools_makewindows": "Makes adjacent or sliding windows across a genome or BED file.", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "gstama_collapse": "Collapse redundant transcript models in Iso-Seq data.", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file"}}, "target": "bedtools_makewindows", "target_idx": 1}
{"id": "mod_leviosam2_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index chain files for lift over (tools: leviosam2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann/insilicolibrarygeneration": null, "bedtools/shift": null, "biscuit/index": null, "leviosam2/index": null, "leviosam2/lift": null}}, "target": "leviosam2/index", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_5_2", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping", "pipeline": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/cageseq, determine the input samplesheet column structure for: CAGE-seq 5-prime capped transcript end sequencing.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,tss_bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_parabricks_minimap2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference database using an accelerated KSW2 to convert FASTQ to BAM/CRAM. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "parabricks/minimap2": "NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference da", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}}, "target": "parabricks/minimap2", "target_idx": 3}
{"id": "resource_biscuit_bsconv_3", "category": "resource_profiling", "state": {"process": "BISCUIT_BSCONV", "tool": "biscuit/bsconv", "description": "Summarize and/or filter reads based on bisulfite conversion rate"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BSCONV (Summarize and/or filter reads based on bisulfite conversion rate) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gtdbtk_classifywf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes based on the Genome Database Taxonomy GTDB. (tools: gtdbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"whatshap_haplotag": "Tag reads by haplotype", "pharmcat_reporter": "The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescri", "gtdbtk_gtdbtoncbimajorityvote": "Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy", "gtdbtk_classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "catpack_contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins)."}}, "target": "gtdbtk_classifywf", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_7_1", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "pipe_all101_metaboigniter_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data.. Topics: identification, mass-spectrometry, metabolomics, ms1, ms2, quantification. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metaboigniter": null, "eager": null, "callingcards": null, "cageseq": null, "scnanoseq": null}}, "target": "metaboigniter", "target_idx": 0}
{"id": "mod_chelae_trim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adapter and quality trimming of short-read FASTQ data using chelae. (tools: chelae)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae_trim": null, "truvari_segment": null, "adapterremoval": null, "clipkit": null, "miniprot_index": null}}, "target": "chelae_trim", "target_idx": 0}
{"id": "resource_apbs_4", "category": "resource_profiling", "state": {"process": "APBS", "tool": "apbs", "description": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Boltzmann Solver). Produces electrostatic potential\nmaps and solvation energy values for large biomolecular assemblages."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to APBS (Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nus) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_1_3", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Tumor-only somatic variant calling without matched normal?", "criteria": {"patient,normal,tumor": null, "sample,bam": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_28", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_32", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_rtgtools_rocplot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI isn't possible for nextflow. (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nanoplot": "Run NanoPlot on nanopore-sequenced reads", "narfmap/align": "Performs fastq alignment to a reference using NARFMAP", "rtgtools/rocplot": "Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI is", "rtgtools/pedfilter": "Converts a PED file to VCF headers", "ferrohgvs/parse": "Parse and validate HGVS variant descriptions with ferro"}}, "target": "rtgtools/rocplot", "target_idx": 2}
{"id": "mod_goat_taxonsearch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Query metadata for any taxon across the tree of life. (tools: goat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fcs/fcsadaptor": "Run NCBI's FCS adaptor on assembled genomes", "goat/taxonsearch": "Query metadata for any taxon across the tree of life.", "disambiguate": "Disambiguates reads aligned to two different organisms (e.g. human and mouse)\nfrom the same source of FASTQ fi", "stadeniolib/scramble": "Advanced sequence file format conversions", "fcs/fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi"}}, "target": "goat/taxonsearch", "target_idx": 1}
{"id": "samplesheet_arch_vcf_annotation_pipeline_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Downstream functional annotation of pre-called VCF files", "data_format": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: BGZF-compressed VCF files with companion Tabix index files?", "criteria": {"sample,vcf,tbi": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "mod_instrain_compare_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strain-level comparisons across multiple inStrain profiles (tools: instrain)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "amulety/balmpaired": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety.", "drep/compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "drep/dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome", "instrain/compare": "Strain-level comparisons across multiple inStrain profiles"}}, "target": "instrain/compare", "target_idx": 4}
{"id": "mod_sylph_query_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sylph query command for querying genome databases against reads/metagenomes (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nextgenmap": "Performs fastq alignment to a fasta reference using NextGenMap", "sylph/query": "Sylph query command for querying genome databases against reads/metagenomes", "bbmap/sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "svdb/query": "Query a structural variant database, using a vcf file as query", "ldak/thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne"}}, "target": "sylph/query", "target_idx": 1}
{"id": "noul_module_metadata_propagation_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_createtaxdb_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Parallelised and automated construction of metagenomic classifier databases of different tools. Topics: database, database-builder, metagenomic-profiling, metagenomics, profiling, taxonomic-profiling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "callingcards": "A pipeline for processing calling cards data"}}, "target": "createtaxdb", "target_idx": 5}
{"id": "qc_adapt_singlecell_multiqc_0_40", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_dastool_fastatocontig2bin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format (tools: dastool)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dastool/fastatocontig2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "clame": "binning of metagenomic sequences", "genomescope2": "Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical "}}, "target": "dastool/fastatocontig2bin", "target_idx": 0}
{"id": "mod_preseq_ccurve_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software for predicting library complexity and genome coverage in high-throughput sequencing (tools: preseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stare": null, "preseq_lcextrap": null, "preseq_ccurve": null, "nonpareil_nonpareil": null, "hicexplorer_hicpca": null}}, "target": "preseq_ccurve", "target_idx": 2}
{"id": "schema_std_rnaseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnaseq. Description: RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnaseq.", "criteria": {"sample,bam,pbi,fail,repeat_id": null, "sample_id,mapped,index,file_type": null, "sample,type,level,msfile": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null}}, "target": "sample,fastq_1,fastq_2,strandedness,seq_platform", "target_idx": 3}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/dualrnaseq) for Dual RNA-seq simultaneous host and pathogen transcriptomics. Input files: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null, "sample,host_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_1_49", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_picard_collecthsmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects hybrid-selection (HS) metrics for a SAM or BAM file. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "picard/collecthsmetrics": "Collects hybrid-selection (HS) metrics for a SAM or BAM file.", "alignoth": "Creating alignment plots from bam files", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "fgbio/copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag."}}, "target": "picard/collecthsmetrics", "target_idx": 1}
{"id": "resource_bcftools_plugintag2tag_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINTAG2TAG", "tool": "bcftools/plugintag2tag", "description": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINTAG2TAG (Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_metatdenovo_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for eukaryotes analysis? Specific context: Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses.. Topics: eukaryotes, metagenomics, metatranscriptomics, prokaryotes, viruses. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, "}}, "target": "metatdenovo", "target_idx": 2}
{"id": "mod_ferrohgvs_parse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parse and validate HGVS variant descriptions with ferro (tools: ferrohgvs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"igvreports": null, "ferrohgvs/parse": null, "clair3": null, "autocycler/trim": null, "xeniumranger/relabel": null}}, "target": "ferrohgvs/parse", "target_idx": 1}
{"id": "mod_samtools_sormadup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collate/Fixmate/Sort/Markdup SAM/BAM/CRAM file (tools: samtools_cat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/prepare": null, "samtools/sormadup": null, "samtools/collate": null, "stainwarpy/register": null, "sratools/prefetch": null}}, "target": "samtools/sormadup", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_1_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ", "pipeline": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "resource_bracken_bracken_1", "category": "resource_profiling", "state": {"process": "BRACKEN_BRACKEN", "tool": "bracken/bracken", "description": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BRACKEN (Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_autocycler_subsample_1", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_SUBSAMPLE", "tool": "autocycler/subsample", "description": "Downsample long-read sequencing data to the requested coverage using Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_SUBSAMPLE (Downsample long-read sequencing data to the requested coverage using Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_catpack_reads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "bcftools/view": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF", "catpack/download": "Downloads the required files for either Nr or GTDB for building into a CAT database", "catpack/reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "fibertoolsrs/extract": "Extract Fiber-seq information (such as m6A, CpG, nucleosomes, and MSPs) from BAM file into BED file"}}, "target": "catpack/reads", "target_idx": 3}
{"id": "field_constraint_status_2_3", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "format: file-path": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "mod_mobster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subclonal deconvolution of cancer genome sequencing data. (tools: mobster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_sort": "Sort SAM/BAM/CRAM file", "mobster": "Subclonal deconvolution of cancer genome sequencing data.", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq", "angsd_dosaf": "Estimate site allele frequencies from BAM files.", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "mobster", "target_idx": 1}
{"id": "mod_fastq_sanitise_seqkit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters and reports malformed FASTQ sequences with seqkit/sana,\nand then pairs any paired-end files using seqkit/pair (tools: fastq_sanitise_seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "fastq_sanitise_seqkit": "Filters and reports malformed FASTQ sequences with seqkit/sana,\nand then pairs any paired-end files using seqk"}}, "target": "fastq_sanitise_seqkit", "target_idx": 4}
{"id": "samplesheet_arch_cageseq_transcription_4_3", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "template": "nf-core/cageseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "resource_bedtools_unionbedg_0", "category": "resource_profiling", "state": {"process": "BEDTOOLS_UNIONBEDG", "tool": "bedtools/unionbedg", "description": "Combines multiple BedGraph files into a single file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_UNIONBEDG (Combines multiple BedGraph files into a single file) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_blobtk_depth_1", "category": "resource_profiling", "state": {"process": "BLOBTK_DEPTH", "tool": "blobtk/depth", "description": "Creates a bed file containing the depth of data at intervals of an aligned bam."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_DEPTH (Creates a bed file containing the depth of data at intervals of an aligned bam.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_autocycler_compress_0", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMPRESS", "tool": "autocycler/compress", "description": "Package candidate assemblies for clustering by Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMPRESS (Package candidate assemblies for clustering by Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "core_tool_star_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Splice-aware alignment of paired-end RNA-seq reads against human genome GRCh38 generating coordinate-sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"star": "Spliced read aligner for RNA-seq", "bowtie2": "Fast aligner for short reads", "minimap2": "Versatile pairwise aligner", "bwa_mem": "Burrows-Wheeler aligner for DNA", "salmon": "Transcript quantification from RNA-seq"}}, "target": "star", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Single-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Single-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "mod_idemux_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex paired-end FASTQ files from QuantSeq-Pool (tools: idemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fqtk": "Demultiplex fastq files", "drep_dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome", "mgikit_demultiplex": "Demultiplex MGI fastq files", "idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "sniffles": "structural-variant calling with sniffles"}}, "target": "idemux", "target_idx": 3}
{"id": "mod_misopy_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build an indexed representation of a GFF for efficient retrieval of genes (tools: misopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eklipse": "tool for detection and quantification of large mtDNA rearrangements.", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "purgedups_calcuts": "Calculate coverage cutoffs to determine when to purge duplicated sequence.", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "misopy_index": "Build an indexed representation of a GFF for efficient retrieval of genes"}}, "target": "misopy_index", "target_idx": 4}
{"id": "mod_octopusv_clean_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clean broken VCF/SVCF files using OctopuSV clean (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/annotate": "Add or remove annotations.", "octopusv/clean": "Clean broken VCF/SVCF files using OctopuSV clean", "ciri2": "Circular RNA identification based on multiple seed matching", "bam_markduplicates_picard": "Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "octopusv/clean", "target_idx": 1}
{"id": "pipe_all101_airrflow_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework. Topics: airr, b-cell, immcantation, immunorepertoire, repseq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqinspector": null, "airrflow": null, "spatialaxe": null, "proteinfamilies": null, "pixelator": null}}, "target": "airrflow", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_6_0", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "NANOPLOT", "library_inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Oxford Nanopore direct RNA input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_ucsc_liftover_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: convert between genome builds (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "hmmer_eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "ucsc_liftover": "convert between genome builds", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "cpc2": "Coding Potential Calculator 2"}}, "target": "ucsc_liftover", "target_idx": 2}
{"id": "resource_autocycler_subsample_0", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_SUBSAMPLE", "tool": "autocycler/subsample", "description": "Downsample long-read sequencing data to the requested coverage using Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_SUBSAMPLE (Downsample long-read sequencing data to the requested coverage using Autocycler.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_genomeassembler_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads. Topics: genome-assembly. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"raredisease": null, "nanostring": null, "hlatyping": null, "magmap": null, "genomeassembler": null, "viralintegration": null, "reportho": null, "demultiplex": null}}, "target": "genomeassembler", "target_idx": 4}
{"id": "samplesheet_arch_pediatric_trio_somatic_6_5", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns are standard for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) input samplesheet?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_24", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "pipe_all101_longraredisease_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders. Topics: nanopore, pacbio. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]"}}, "target": "longraredisease", "target_idx": 5}
{"id": "resource_amulety_antiberta2_1", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTA2", "tool": "amulety/antiberta2", "description": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTA2 (A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences ) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_hasheddrops_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generating cell hashing calls from a matrix of count data. (tools: hasheddrops)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bff": null, "hasheddrops": null, "zip": null, "demuxem": null, "shigapass": null}}, "target": "hasheddrops", "target_idx": 1}
{"id": "field_constraint_status_0_4", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "enum: [auto, forward, reverse]": null, "format: file-path": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_40", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "subworkflow_pkg_bam_methyldackel_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_METHYLDACKEL", "modules": ["methyldackel/extract", "methyldackel/mbias"], "description": "Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignments using Methyldackel."}, "question": {"type": "choice", "instructions": "How should BAM_METHYLDACKEL (methyldackel/extract, methyldackel/mbias) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_methyldackel": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_METHYLDACKEL": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_methyldackel", "target_idx": 0}
{"id": "resource_bismark_methylationextractor_2", "category": "resource_profiling", "state": {"process": "BISMARK_METHYLATIONEXTRACTOR", "tool": "bismark/methylationextractor", "description": "Extracts methylation information for individual cytosines from alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_METHYLATIONEXTRACTOR (Extracts methylation information for individual cytosines from alignments.) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_45", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_35", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "noul_retry_errorstrategy_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_3_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_ale_2", "category": "resource_profiling", "state": {"process": "ALE", "tool": "ale", "description": "ALE: assembly likelihood estimator."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALE (ALE: assembly likelihood estimator.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_2_9", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_vclust_prefilter_align_cluster_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER", "modules": ["vclust/prefilter", "vclust/align", "vclust/cluster"], "description": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter"}, "question": {"type": "choice", "instructions": "How should FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER (vclust/prefilter, vclust/align, vclust/cluster) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER": null}}, "target": "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster", "target_idx": 1}
{"id": "mod_cooler_cload_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a cooler from genomic pairs and bins (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooltools/eigscis": "Perform eigen value decomposition on a cooler matrix to calculate compartment signal by finding the eigenvecto", "regenie/step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions", "cooltools/insulation": "Calculate the diamond insulation scores and call insulating boundaries", "gapseq/find": "Predict metabolic pathways from genomic data using gapseq", "cooler/cload": "Create a cooler from genomic pairs and bins"}}, "target": "cooler/cload", "target_idx": 4}
{"id": "noul_include_modular_process_syntax_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_bismark_summary_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngmerge": "Merging paired-end reads and removing sequencing adapters.", "bismark/report": "Collects bismark alignment reports", "xeniumranger/resegment": "The xeniumranger resegment module allows you to generate a new segmentation of the morphology image space by r", "bismark/summary": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report.", "bismark/align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "bismark/summary", "target_idx": 3}
{"id": "mod_elprep_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split bam file into manageable chunks (tools: elprep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": null, "bamclipper": null, "elprep/split": null, "drep/dereplicate": null, "mm2plus/align": null}}, "target": "elprep/split", "target_idx": 2}
{"id": "mod_vcf_annotate_ensemblvep_snpeff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkflow uses the scatter-gather method to run VEP/snpEff in parallel to increase throughput. The input VCF is split into multiple smaller VCFs of fixed size, which are annotated separately and concatenated back together to a single output file per sample. Only VCF/BCF outputs are currently supported. (tools: vcf_annotate_ensemblvep_snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusioncatcher/build": null, "vcf_annotate_ensemblvep_snpeff": null, "aardvark/merge": null, "bcftools/call": null, "finaletoolkit/adjustwps": null}}, "target": "vcf_annotate_ensemblvep_snpeff", "target_idx": 1}
{"id": "subworkflow_pkg_bedgraph_bedclip_bedgraphtobigwig_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG", "modules": ["ucsc/bedclip", "ucsc/bedgraphtobigwig"], "description": "Convert bedgraph to bigwig with clip"}, "question": {"type": "choice", "instructions": "How should BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG (ucsc/bedclip, ucsc/bedgraphtobigwig) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG": null, "Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig", "target_idx": 2}
{"id": "subworkflow_pkg_bam_subsampledepth_samtools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SUBSAMPLEDEPTH_SAMTOOLS", "modules": ["samtools/coverage", "samtools/view"], "description": "Subsample a BAM/CRAM/SAM file using samtools to a given mean depth."}, "question": {"type": "choice", "instructions": "How should BAM_SUBSAMPLEDEPTH_SAMTOOLS (samtools/coverage, samtools/view) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_subsampledepth_samtools": null, "Local subworkflow BAM_SUBSAMPLEDEPTH_SAMTOOLS": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_subsampledepth_samtools", "target_idx": 0}
{"id": "field_constraint_bai_0_9", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "resource_agat_convertspgff2tsv_3", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2TSV", "tool": "agat/convertspgff2tsv", "description": "Converts a GFF/GTF file into a TSV file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2TSV (Converts a GFF/GTF file into a TSV file) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_binette_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools. (tools: binette)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fcs_fcsgx": null, "binette": null, "bwa_mem": null, "comebin_runcomebin": null, "concoct_extractfastabins": null}}, "target": "binette", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_32", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_rseqc_junctionsaturation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: compare detected splice junctions to reference gene model (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rseqc_junctionsaturation": "compare detected splice junctions to reference gene model", "ctatsplicing_prepgenomelib": "Reference preparation for CTAT-splicing", "nextclade_datasetget": "Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ impleme", "hisat2_extractsplicesites": "Extracts splicing sites from a gtf files", "mirdeep2_mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs."}}, "target": "rseqc_junctionsaturation", "target_idx": 0}
{"id": "mod_liftoff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses Liftoff to accurately map annotations in GFF or GTF between assemblies of the same,\nor closely-related species (tools: liftoff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"liftoff": "Uses Liftoff to accurately map annotations in GFF or GTF between assemblies of the same,\nor closely-related sp", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "pretextmap": "converts sam/bam/cram/pairs into genome contact map", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "trimgalore": "A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith e"}}, "target": "liftoff", "target_idx": 0}
{"id": "mod_openms_filefilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters peptide/protein identification results by different criteria. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "bbmap/filterbyname": "Filter out sequences by sequence header name(s)", "shigatyper": "Determine Shigella serotype from Illumina or Oxford Nanopore reads", "openms/filefilter": "Filters peptide/protein identification results by different criteria.", "seacr/callpeak": "Call peaks using SEACR on sequenced reads in bedgraph format"}}, "target": "openms/filefilter", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_29", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_antismash_antismash_1", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASH", "tool": "antismash/antismash", "description": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASH (antiSMASH allows the rapid genome-wide identification, annotation\nand analysis o) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_42", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "pipe_all101_fastqrepair_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for corruption. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]"}}, "target": "fastqrepair", "target_idx": 6}
{"id": "qc_adapt_bulk_multiqc_2_35", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_cellpose_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: cellpose segments cells in images using GPU-accelerated deep learning (tools: cellpose)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "propr_logratio": "Transform the data matrix using centered logratio transformation (CLR) or additive logratio transformation (AL", "ilastik_pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "seqfu_stats": "Statistics for FASTA or FASTQ files", "numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit."}}, "target": "cellpose", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_7", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_fungtion_fungtion_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predicts fungal effector proteins from protein FASTA sequences using ESM-1b\nprotein language model embeddings and R-based SVM models. Optionally produces\nsimilarity-network and relationship-tree visualizations and an HTML report for\npredicted effectors. Requires the pretrained ESM-1b weights from\nFUNGTION_DOWNLOADMODELS as input. (tools: fungtion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clusty": null, "fungtion/fungtion": null, "fungtion/downloadmodels": null, "metaphlan/metaphlan": null, "gatk4/combinegvcfs": null}}, "target": "fungtion/fungtion", "target_idx": 1}
{"id": "mod_motus_preplong_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic meta-omics profiling using universal marker genes (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"motus_preplong": "Taxonomic meta-omics profiling using universal marker genes", "pharmcat_matcher": "The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to", "centrifuge_centrifuge": "Classifies metagenomic sequence data", "ganon_classify": "Classify FASTQ files against ganon database", "sistr": "Serovar prediction of salmonella assemblies"}}, "target": "motus_preplong", "target_idx": 0}
{"id": "schema_std_ribomsqc_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/ribomsqc. Description: QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/ribomsqc.", "criteria": {"id,raw_file": null, "sample,fasta": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample,fastq_1,fastq_2,bam,bai": null}}, "target": "id,raw_file", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_5_4", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Genome analysis from reference-compressed CRAM files.", "criteria": {"sample,cram,crai": null, "sample,cram": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 0}
{"id": "resource_biscuit_align_1", "category": "resource_profiling", "state": {"process": "BISCUIT_ALIGN", "tool": "biscuit/align", "description": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_ALIGN (Aligns single- or paired-end reads from bisulfite-converted libraries to a refer) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_contam_seqtk_kraken_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_CONTAM_SEQTK_KRAKEN", "modules": ["kraken2/kraken2", "seqtk/sample"], "description": "Produces a contamination report from FastQ input after subsampling"}, "question": {"type": "choice", "instructions": "How should FASTQ_CONTAM_SEQTK_KRAKEN (kraken2/kraken2, seqtk/sample) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_contam_seqtk_kraken": null, "Local subworkflow FASTQ_CONTAM_SEQTK_KRAKEN": null}}, "target": "Use nf-core subworkflow fastq_contam_seqtk_kraken", "target_idx": 2}
{"id": "mod_gatk_realignertargetcreator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a list of locations that should be considered for local realignment prior genotyping. (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "gatk_realignertargetcreator": "Generates a list of locations that should be considered for local realignment prior genotyping.", "ascat": "copy number profiles of tumour cells.", "svtk_rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format.", "modkit_repair": "Repair the MM/ML tags on trimmed or hard-clipped ONT reads using untrimmed ONT reads."}}, "target": "gatk_realignertargetcreator", "target_idx": 1}
{"id": "mod_modkit_pileup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A bioinformatics tool for working with modified bases (tools: modkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_hmmfetch": null, "bismark_report": null, "bismark_deduplicate": null, "modkit_pileup": null, "vcf_filter_bcftools_ensemblvep": null}}, "target": "modkit_pileup", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_8", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/chipseq) for ChIP-seq with IP and input control design. Input files: Paired-end FASTQ reads for immunoprecipitation and input chromatin.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/chipseq, determine the input samplesheet column structure for: ChIP-seq with IP and input control design.", "criteria": {"sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "mod_gridss_extractoverlappingfragments_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for targeted GRIDSS structural variant calling. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "gridss/extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "gridss/annotate": "Annotates single breakends in a GRIDSS VCF with RepeatMasker annotations using gridss_annotate_vcf_repeatmaske", "caalm/caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES", "octopusv/svcf2vcf": "Converts octopusv SVCF files to the standard VCF format"}}, "target": "gridss/extractoverlappingfragments", "target_idx": 1}
{"id": "mod_samtools_quickcheck_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly check that input files appear to be intact. Checks that beginning of the file contains a valid header (all formats) containing at least one target sequence and then seeks to the end of the file and checks that an end-of-file (EOF) is present and intact (BAM and CRAM only). Alignment records are not checked. The quickcheck module returns a non-zero EXIT_CODE if any input files don't have a valid header or are missing an EOF block. Otherwise EXIT_CODE is zero. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_quickcheck": "Quickly check that input files appear to be intact. Checks that beginning of the file contains a valid header ", "htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "rclone_check": "Check that files in source and destination paths match", "sylph_sketchgenomes": "Sylph profile command for taxonoming profiling of genomes", "gridss_extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for"}}, "target": "samtools_quickcheck", "target_idx": 0}
{"id": "field_constraint_phenotype_0_1", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "enum: [normal, tumor]": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "pipe_all101_funcprofiler_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for funcprofiler. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "seqsubmit": "nf-core pipeline for data submission to ENA", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra"}}, "target": "funcprofiler", "target_idx": 1}
{"id": "noul_dynamic_resource_allocation_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_mobsuite_typer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bacterial plasmid typing and mobility prediction (tools: mobsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mobsuite_typer": "Bacterial plasmid typing and mobility prediction", "rtgtools_format": "Converts the contents of sequence data files (FASTA/FASTQ/SAM/BAM) into the RTG Sequence Data File (SDF) forma", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "autocycler_trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}}, "target": "mobsuite_typer", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_4_0", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_42", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "schema_std_bacmodel_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacmodel", "assay": "bacmodel pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/bacmodel (Systems-based bacterial functional modeling pipeline)?", "criteria": {"sample,fastq_1,fastq_2": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,run,group,short_reads_1,short_reads_2": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bismark_align_1", "category": "resource_profiling", "state": {"process": "BISMARK_ALIGN", "tool": "bismark/align", "description": "Performs alignment of BS-Seq reads using bismark"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_ALIGN (Performs alignment of BS-Seq reads using bismark) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_1_12", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_amulety_balmpaired_3", "category": "resource_profiling", "state": {"process": "AMULETY_BALMPAIRED", "tool": "amulety/balmpaired", "description": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_BALMPAIRED (A module to create BALM paired embeddings of antibody (BCR) amino acid sequences) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_rnafusion_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnafusion", "description": "RNA-seq analysis pipeline for detection of gene-fusions", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnafusion?", "criteria": {"sample,fastq_1,fastq_2,bam,bai": null, "id,path": null, "sample,bam,pbi,fail,repeat_id": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 0}
{"id": "mod_circexplorer2_parse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate. (tools: circexplorer2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"circexplorer2_parse": null, "beagle5_beagle": null, "pairtools_parse": null, "ciri2": null, "bwamem2_mem": null}}, "target": "circexplorer2_parse", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_39", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "field_constraint_sample_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "noul_modular_subworkflow_composition_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_phenotype_0_13", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 1}
{"id": "mod_krona_kronadb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KronaTools Update Taxonomy downloads a taxonomy database (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqfu_stats": "Statistics for FASTA or FASTQ files", "antismash_antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "blast_makeblastdb": "Builds a BLAST database", "krona_kronadb": "KronaTools Update Taxonomy downloads a taxonomy database", "svtools_vcftobedpe": "Convert a VCF file to a BEDPE file."}}, "target": "krona_kronadb", "target_idx": 3}
{"id": "field_constraint_expected_cells_0_5", "category": "samplesheet_schema", "state": {"field_name": "expected_cells", "datatype": "numeric_integer", "description": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'expected_cells'?", "criteria": {"pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "resource_blobtk_snail_4", "category": "resource_profiling", "state": {"process": "BLOBTK_SNAIL", "tool": "blobtk/snail", "description": "Creates blobtk snail plots."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_SNAIL (Creates blobtk snail plots.) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_bai_3_7", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_4_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "MUTECT2", "library_inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted BAMs with index for tumor and normal samples?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_48", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_6_4", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs", "pipeline": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) input samplesheet?", "criteria": {"sample,cpg,methylation": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bedtools_getfasta_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_GETFASTA", "tool": "bedtools/getfasta", "description": "extract sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_GETFASTA (extract sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_quarto_prerender_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pre-render a Quarto document to markdown, including parametrization (tools: quarto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yte": "A YAML template engine with Python expressions", "quartonotebook": "Render a Quarto notebook, including parametrization.", "calder2": "Hierarchical Hi-C compartment computation", "longstitch": "\"A genome assembly correction and scaffolding pipeline using long reads, consisting of up to three steps:\n  - ", "quarto_prerender": "Pre-render a Quarto document to markdown, including parametrization"}}, "target": "quarto_prerender", "target_idx": 4}
{"id": "resource_bowtie_align_4", "category": "resource_profiling", "state": {"process": "BOWTIE_ALIGN", "tool": "bowtie/align", "description": "Align reads to a reference genome using bowtie"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_ALIGN (Align reads to a reference genome using bowtie) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_funcscan_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/funcscan. Description: (Meta-)genome screening for functional and natural product gene sequences.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/funcscan.", "criteria": {"sample,fasta,protein,gbk,gff": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "sample,fasta,protein,gbk,gff", "target_idx": 0}
{"id": "resource_ampcombi2_parsetables_2", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_PARSETABLES", "tool": "ampcombi2/parsetables", "description": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_PARSETABLES (A submodule that parses and standardizes the results from various antimicrobial ) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_upd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simple software to call UPD regions from germline exome/wgs trios. (tools: upd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile", "ngsbits/updhunter": "UPD detection from trio variant data.", "varlociraptor/filterfdr": "Filter Varlociraptor variant calls using FDR control.", "upd": "Simple software to call UPD regions from germline exome/wgs trios.", "circexplorer2/annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse"}}, "target": "upd", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_hic_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Analysis of Chromosome Conformation Capture data (Hi-C). Topics: chromosome-conformation-capture, hi-c. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "callingcards": "A pipeline for processing calling cards data", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "hic", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for 16S rRNA / ITS microbiome amplicon profiling. Input files: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: 16S rRNA / ITS microbiome amplicon profiling.", "criteria": {"sample,otu_table": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_core10_sarek_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Whole-genome sequencing for germline variant calling with GATK HaplotypeCaller, DeepVariant, and Strelka2.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "sarek", "target_idx": 9}
{"id": "mod_raxmlng_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: RAxML-NG is a phylogenetic tree inference tool which uses maximum-likelihood (ML) optimality criterion. (tools: raxmlng)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"holodeck/eval": "Evaluate alignment accuracy of holodeck-simulated reads", "openms/peakpickerhires": "A tool for peak detection in high-resolution profile data (Orbitrap or FTICR)", "cafe": "Analysis of gene family evolution", "raxmlng": "RAxML-NG is a phylogenetic tree inference tool which uses maximum-likelihood (ML) optimality criterion.", "cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm"}}, "target": "raxmlng", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wes_pe_4_4", "category": "samplesheet_schema", "state": {"technology": "Bulk DNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from Agilent/Twist exome target capture"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from Agilent/Twist exome target capture?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_5_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_35", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "subworkflow_pkg_gtf_hybridmerge_gffcompare_3", "category": "subworkflow_packaging", "state": {"subworkflow": "GTF_HYBRIDMERGE_GFFCOMPARE", "modules": ["gffcompare", "gawk", "bedtools/intersect"], "description": "Build a hybrid GTF by classifying a novel-transcript GTF against a reference"}, "question": {"type": "choice", "instructions": "How should GTF_HYBRIDMERGE_GFFCOMPARE (gffcompare, gawk, bedtools/intersect) be structured in DSL2?", "criteria": {"Use nf-core subworkflow gtf_hybridmerge_gffcompare": null, "Local subworkflow GTF_HYBRIDMERGE_GFFCOMPARE": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow gtf_hybridmerge_gffcompare", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_27", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "subworkflow_pkg_tiff_segmentation_vpt_3", "category": "subworkflow_packaging", "state": {"subworkflow": "TIFF_SEGMENTATION_VPT", "modules": ["vizgenpostprocessing/preparesegmentation", "vizgenpostprocessing/runsegmentationontile", "vizgenpostprocessing/compiletilesegmentation"], "description": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool"}, "question": {"type": "choice", "instructions": "How should TIFF_SEGMENTATION_VPT (vizgenpostprocessing/preparesegmentation, vizgenpostprocessing/runsegmentationontile, vizgenpostprocessing/compiletilesegmentation) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow tiff_segmentation_vpt": null, "Keep the modules in the main workflow": null, "Local subworkflow TIFF_SEGMENTATION_VPT": null}}, "target": "Use nf-core subworkflow tiff_segmentation_vpt", "target_idx": 1}
{"id": "resource_braker3_1", "category": "resource_profiling", "state": {"process": "BRAKER3", "tool": "braker3", "description": "Gene prediction in novel genomes using RNA-seq and protein homology information"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRAKER3 (Gene prediction in novel genomes using RNA-seq and protein homology information) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_7_0", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,vcf": null, "patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_38", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_macsyfinder_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download MacSyFinder models using msf_data (tools: macsyfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fqtk": "Demultiplex fastq files", "alignoth": "Creating alignment plots from bam files", "macsyfinder/download": "Download MacSyFinder models using msf_data", "survivor/stats": "Report multiple stats over a VCF file", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "macsyfinder/download", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_0_10", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_quartonotebook_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render a Quarto notebook, including parametrization. (tools: quartonotebook)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"phispy": null, "rmarkdownnotebook": null, "yte": null, "ctree": null, "quartonotebook": null}}, "target": "quartonotebook", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_1_29", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_1_16", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_rnadnavar_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for rnadnavar analysis? Specific context: Pipeline for RNA and DNA integrated analysis for somatic mutation detection. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina"}}, "target": "rnadnavar", "target_idx": 4}
{"id": "mod_gatk4_gatherpileupsummaries_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_gatherpileupsummaries": null, "holodeck_simulate": null, "lofreq_indelqual": null, "gatk4_applyvqsr": null, "gatk4_annotateintervals": null}}, "target": "gatk4_gatherpileupsummaries", "target_idx": 0}
{"id": "mod_gapseq_medium_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict growth medium from a draft model and pathway predictions (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq/medium": "Predict growth medium from a draft model and pathway predictions", "fastawindows": "Quickly compute statistics over a fasta file in windows.", "seqkit/fq2fa": "Convert FASTQ to FASTA format", "gapseq/draft": "Create draft metabolic model from pathway and transporter predictions", "gapseq/doall": "Complete gapseq workflow from genome to gap-filled model"}}, "target": "gapseq/medium", "target_idx": 0}
{"id": "pipe_all101_multiplesequencealign_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for multiplesequencealign analysis? Specific context: A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]"}}, "target": "multiplesequencealign", "target_idx": 0}
{"id": "mod_gecco_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomic and metagenomic data using Conditional Random Fields (CRFs). (tools: gecco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_lastdb": "Prepare sequences for subsequent alignment with lastal.", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs", "gecco_run": "GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomi"}}, "target": "gecco_run", "target_idx": 4}
{"id": "mod_mudskipper_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM files. (tools: mudskipper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "mudskipper/index": "Build and store a gtf index, which is useful for converting genomic BAM/SAM files to transcriptomic BAM/SAM fi", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "ultra/align": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Map reads on genome", "pilon": "Automatically improve draft assemblies and find variation among strains, including large event detection"}}, "target": "mudskipper/index", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Multi-lane Illumina sequencing run of clinical samples", "data_format": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multi-lane Illumina sequencing run of clinical samples input samplesheet?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "sample,bam": null, "lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_rgi_main_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict antibiotic resistance from protein or nucleotide data (tools: rgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "refsolver_score": "Score a query sequence dictionary against a reference using ref-solver", "untarfiles": "Extract files.", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "rgi_main": "Predict antibiotic resistance from protein or nucleotide data"}}, "target": "rgi_main", "target_idx": 4}
{"id": "mod_bwamem3_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create bwa-mem3 index for reference genome (tools: bwamem3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "bbmap/bbduk": "Adapter and quality trimming of sequencing reads", "bwamem3/index": "Create bwa-mem3 index for reference genome", "fq/generate": "fq generate is a FASTQ file pair generator. It creates two reads, formatting names as described by Illumina. W", "biscuit/index": "Indexes a reference genome for use with Biscuit"}}, "target": "bwamem3/index", "target_idx": 2}
{"id": "mod_cellrangeratac_count_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC. (tools: cellranger-atac)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "cellrangeratac/count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "viber": "Multisample subclonal deconvolution of cancer genome sequencing data.", "gatk4/gatherpileupsummaries": "write your description here", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "cellrangeratac/count", "target_idx": 1}
{"id": "resource_atlas_call_5", "category": "resource_profiling", "state": {"process": "ATLAS_CALL", "tool": "atlas/call", "description": "generate VCF file from a BAM file using various calling methods"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_CALL (generate VCF file from a BAM file using various calling methods) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_samtools_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: convert and then index CRAM -> BAM or BAM -> CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_convert": "convert and then index CRAM -> BAM or BAM -> CRAM file", "telescope_assign": "The telescope assign program finds overlapping reads between an alignment (SAM/BAM) and an annotation (GTF) th", "racon": "Consensus module for raw de novo DNA assembly of long uncorrected reads", "samtools_getrg": "filter/convert SAM/BAM/CRAM file", "samtools_view": "filter/convert SAM/BAM/CRAM file"}}, "target": "samtools_convert", "target_idx": 0}
{"id": "mod_any2fasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input files may be gzip, bzip2, zip, or zstd compressed. (tools: any2fasta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "refsolver_score": "Score a query sequence dictionary against a reference using ref-solver", "angsd_dosaf": "Estimate site allele frequencies from BAM files.", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "any2fasta", "target_idx": 4}
{"id": "mod_expansionhunterdenovo_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge STR profiles into a multi-sample STR profile (tools: expansionhunterdenovo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam_bammerge": null, "agat_spmergeannotations": null, "lofreq_viterbi": null, "openms_peakpickerhires": null, "expansionhunterdenovo_merge": null}}, "target": "expansionhunterdenovo_merge", "target_idx": 4}
{"id": "mod_fastq_find_mirna_mirdeep2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, processes and replaces any whitespace in sequence IDs, builds a Bowtie index of the genome, and then maps reads using miRDeep2 mapper before identifying known and novel miRNAs. (tools: fastq_find_mirna_mirdeep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "clame": "binning of metagenomic sequences", "bwamem3/index": "Create bwa-mem3 index for reference genome", "fastq_find_mirna_mirdeep2": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, proc", "mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package"}}, "target": "fastq_find_mirna_mirdeep2", "target_idx": 3}
{"id": "field_constraint_fastq_2_0_14", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "type: required string": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "resource_abyss_abysspe_1", "category": "resource_profiling", "state": {"process": "ABYSS_ABYSSPE", "tool": "abyss/abysspe", "description": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABYSS_ABYSSPE (ABySS is a de novo sequence assembler intended for short paired-end reads and ge) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_0_43", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_find_concatenate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size (tools: find)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"graphtyper_vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "cat_fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "fcs_fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi", "blast_blastn": "Queries a BLAST DNA database", "find_concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size"}}, "target": "find_concatenate", "target_idx": 4}
{"id": "pipe_all101_hlatyping_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for dna. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "callingcards": "A pipeline for processing calling cards data", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra"}}, "target": "hlatyping", "target_idx": 3}
{"id": "noul_executor_support_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "schema_std_hicar_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hicar", "description": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/hicar?", "criteria": {"sample,fasta,protein,gbk,gff": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null}}, "target": "fastq_1,fastq_2,group,replicate,md5_1", "target_idx": 2}
{"id": "mod_kmcp_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct KMCP database from k-mer files (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "ncbitools/vecscreen": "NCBI tool for detecting vector contamination in nucleic acid sequences. This tool is older than NCBI's FCS-ada", "kmcp/index": "Construct KMCP database from k-mer files", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "ngscheckmate/patterngenerator": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate"}}, "target": "kmcp/index", "target_idx": 2}
{"id": "subworkflow_pkg_orftable_fasta_gtf_buildorfcatalogue_1", "category": "subworkflow_packaging", "state": {"subworkflow": "ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE", "modules": ["custom/orfnormalise", "custom/orfmerge", "bedtools/getfasta", "seqkit/translate", "mmseqs/easycluster", "custom/orfcollapse"], "description": "Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller"}, "question": {"type": "choice", "instructions": "How should ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE (custom/orfnormalise, custom/orfmerge, bedtools/getfasta, seqkit/translate, mmseqs/easycluster, custom/orfcollapse) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow ORFTABLE_FASTA_GTF_BUILDORFCATALOGUE": null, "Leave them out": null, "Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue": null}}, "target": "Use nf-core subworkflow orftable_fasta_gtf_buildorfcatalogue", "target_idx": 3}
{"id": "intent_debug_error_15", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "prepare_data": null, "debug_error": null, "build_pipeline": null}}, "target": "debug_error", "target_idx": 2}
{"id": "schema_std_rnaseq_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "description": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnaseq?", "criteria": {"fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "sample,fastq_1,fastq_2,strandedness,type": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "sample,fastq_1,fastq_2,strandedness,seq_platform", "target_idx": 1}
{"id": "mod_pypgx_computecontrolstatistics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute summary statistics for control gene from BAM files. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx_computecontrolstatistics": null, "nucmer": null, "quant_tximport_summarizedexperiment": null, "pypgx_createinputvcf": null, "pypgx_preparedepthofcoverage": null}}, "target": "pypgx_computecontrolstatistics", "target_idx": 0}
{"id": "mod_rattle_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reference-free reconstruction and quantification of transcriptomes from long-read sequencing (tools: rattle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cdhit/cdhitest": null, "trgt/genotype": null, "rattle/cluster": null, "lsa/cosine": null, "clusty": null}}, "target": "rattle/cluster", "target_idx": 2}
{"id": "mod_proovframe_fix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: frame-shift correction for long read (meta)genomics - fix frameshifts in reads (tools: proovframe)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"proovframe_fix": null, "bcftools_call": null, "proovframe_map": null, "deepbgc_download": null, "primerprospector_analyzeprimers": null}}, "target": "proovframe_fix", "target_idx": 0}
{"id": "schema_std_rnadnavar_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnadnavar", "description": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnadnavar?", "criteria": {"ID,R1,R2,LongFastQ,Fast5": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,condition,assay,peak_file,footprinting": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 3}
{"id": "mod_civicpy_annotate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations of Variants in Cancer (CIViC) knowledgebase (tools: civicpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "civicpy/annotate": "A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations o", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "orfipy": "orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner.", "abacas": "Contiguate draft genome assembly"}}, "target": "civicpy/annotate", "target_idx": 1}
{"id": "intent_build_pipeline_18", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "build_pipeline", "target_idx": 3}
{"id": "schema_std_proteinfold_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinfold", "description": "Protein 3D structure prediction pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/proteinfold?", "criteria": {"sample,fasta,protein,gbk,gff": null, "id,raw_file": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "id,fasta,sequence": null}}, "target": "id,fasta,sequence", "target_idx": 3}
{"id": "schema_std_nanostring_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanostring", "assay": "nanostring pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/nanostring (An analysis pipeline for Nanostring nCounter expression data)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT", "target_idx": 2}
{"id": "schema_std_genomicrelatedness_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomicrelatedness", "assay": "genomicrelatedness pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/genomicrelatedness (Bioinformatics pipeline for estimating genetic relatedness f)?", "criteria": {"id,test_vcf,test_regions,caller,subsample": null, "sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,bam,cram": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,fastq_1,fastq_2,bam,cram", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Metagenomic MAG assembly with comparative groups. Input files: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Metagenomic MAG assembly with comparative groups.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "noul_single_hyphen_cli_params_error_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_scrnaseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection. Topics: 10x-genomics, 10xgenomics, alevin, bustools, cellranger, kallisto. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnaseq": null, "rnavar": null, "molkart": null, "stableexpression": null, "scrnaseq": null}}, "target": "scrnaseq", "target_idx": 4}
{"id": "samplesheet_arch_chipseq_with_control_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/chipseq", "assay_type": "ChIP-seq with IP and input control design", "data_format": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads for immunoprecipitation and input chromatin?", "criteria": {"sample,antibody,control": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "noul_mix_operator_async_emission_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_0_1", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,spikein,fastq": null, "sample,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_strelka_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA", "modules": ["gatk4/mergevcfs", "strelka/somatic"], "description": "Perform variant calling on a paired tumor normal set of samples using strelka somatic mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA (gatk4/mergevcfs, strelka/somatic) be structured in DSL2?", "criteria": {"Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_STRELKA": null, "Leave them out": null, "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_strelka", "target_idx": 2}
{"id": "subworkflow_pkg_faa_seqfu_seqkit_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FAA_SEQFU_SEQKIT", "modules": ["seqfu/stats", "seqkit/seq", "seqkit/rmdup", "seqkit/replace"], "description": "Subworkflow that optionally preprocesses amino acid FASTA sequences"}, "question": {"type": "choice", "instructions": "How should FAA_SEQFU_SEQKIT (seqfu/stats, seqkit/seq, seqkit/rmdup, seqkit/replace) be structured in DSL2?", "criteria": {"Local subworkflow FAA_SEQFU_SEQKIT": null, "Use nf-core subworkflow faa_seqfu_seqkit": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow faa_seqfu_seqkit", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_apbs_2", "category": "resource_profiling", "state": {"process": "APBS", "tool": "apbs", "description": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Boltzmann Solver). Produces electrostatic potential\nmaps and solvation energy values for large biomolecular assemblages."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to APBS (Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nus) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wes_pe_1_5", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Whole Exome Sequencing (WES) target capture?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_biscuit_biscuitblaster_1", "category": "resource_profiling", "state": {"process": "BISCUIT_BISCUITBLASTER", "tool": "biscuit/biscuitblaster", "description": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BISCUITBLASTER (A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM f) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_falint_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fasta linter/validator (tools: falint)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "gridss_extractoverlappingfragments": "Extract read fragments from a BAM file whose reads overlap a set of target regions, producing a subset BAM for", "falint": "A fasta linter/validator", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "cooler_balance": "Run matrix balancing on a cool file"}}, "target": "falint", "target_idx": 2}
{"id": "mod_pigz_compress_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compresses files with pigz. (tools: pigz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pigz/compress": "Compresses files with pigz.", "cat/fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "maltextract": "Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening", "tabix/bgziptabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. bgzip a sorted tab-delimited genome file and then create tabix inde", "rtgtools/bndeval": "The bndeval tool of RTG tools. It is used to evaluate called BND type of variants for agreement with a BND bas"}}, "target": "pigz/compress", "target_idx": 0}
{"id": "noul_container_environment_specification_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_download_prefetch_fasterqdump_sratools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS", "modules": ["custom/sratoolsncbisettings", "sratools/prefetch", "sratools/fasterqdump"], "description": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA)."}, "question": {"type": "choice", "instructions": "How should FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS (custom/sratoolsncbisettings, sratools/prefetch, sratools/fasterqdump) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools": null, "Local subworkflow FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools", "target_idx": 1}
{"id": "schema_std_rnadnavar_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnadnavar. Description: Pipeline for RNA and DNA integrated analysis for somatic mutation detection.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnadnavar.", "criteria": {"patient,sample,fastq_1,fastq_2,bam": null, "sample,fastq_1,fastq_2,strandedness,type": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "id,fasta,query": null}}, "target": "patient,sample,fastq_1,fastq_2,bam", "target_idx": 0}
{"id": "mod_busco_busco_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Benchmarking Universal Single Copy Orthologs (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"orfipy": "orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner.", "busco/generateplot": "BUSCO plot generation tool", "plastid/makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-", "busco/busco": "Benchmarking Universal Single Copy Orthologs", "cnaqc": "Quality control of copy number data from bulk WGS assays"}}, "target": "busco/busco", "target_idx": 3}
{"id": "mod_nextclade_datasetget_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation) (tools: nextclade)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nextclade_datasetget": "Get dataset for SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ impleme", "immunedeconv": "Perform immune cell deconvolution using RNA-seq data and various computational methods.", "ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro", "clair3": "Clair3 is a germline small variant caller for long-reads", "svim_alignment": "Structural variant detection from long-read sequencing alignments using SVIM."}}, "target": "nextclade_datasetget", "target_idx": 0}
{"id": "mod_regenie_step2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run REGENIE step 2 association testing from precomputed step 1 predictions (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lsa/cosine": "Calculates the cosine similarity matrix between samples based on a gene expression matrix.", "regenie/runl1": "Finish REGENIE step 1 from split level-0 prediction files", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "regenie/step2": "Run REGENIE step 2 association testing from precomputed step 1 predictions", "openms/idscoreswitcher": "Switches between different scores of peptide or protein hits in identification data"}}, "target": "regenie/step2", "target_idx": 3}
{"id": "mod_controlfreec_assesssignificance_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC (tools: controlfreec/assesssignificance)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec_freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "deeparg_downloaddata": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "deeptools_alignmentsieve": "This tool filters alignments in a BAM/CRAM file according the the specified parameters.", "controlfreec_assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "cnvnator_convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format."}}, "target": "controlfreec_assesssignificance", "target_idx": 3}
{"id": "resource_bcftools_pluginfilltags_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFILLTAGS", "tool": "bcftools/pluginfilltags", "description": "Compute and fill various INFO tags"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFILLTAGS (Compute and fill various INFO tags) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_2_5", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,unite_fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_11", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_31", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_arriba_visualisation_3", "category": "resource_profiling", "state": {"process": "ARRIBA_VISUALISATION", "tool": "arriba/visualisation", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_VISUALISATION (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "subworkflow_pkg_bam_applybqsr_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_APPLYBQSR", "modules": ["gatk4/applybqsr", "samtools/merge"], "description": "Apply Base Quality Score Recalibration (BQSR) to a BAM or CRAM file using"}, "question": {"type": "choice", "instructions": "How should BAM_APPLYBQSR (gatk4/applybqsr, samtools/merge) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_APPLYBQSR": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_applybqsr": null}}, "target": "Use nf-core subworkflow bam_applybqsr", "target_idx": 3}
{"id": "noul_single_hyphen_cli_params_error_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_viral_amplicon_artic_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral amplicon sequencing with primers", "data_format": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Viral amplicon sequencing with primers with entry step FASTQC.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_4", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_picard_collectvariantcallingmetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects per-sample and aggregate (spanning all samples) metrics from the provided VCF file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm2_databasedownload": "CheckM2 database download", "atlas_call": "generate VCF file from a BAM file using various calling methods", "picard_collectvariantcallingmetrics": "Collects per-sample and aggregate (spanning all samples) metrics from the provided VCF file", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "mashtree": "Quickly create a tree using Mash distances"}}, "target": "picard_collectvariantcallingmetrics", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_2_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_seqkit_tab2fx_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert tabular format (first two/three columns) to FASTA/Q format. (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "gatk4_fastqtosam": "Converts FastQ file to SAM/BAM format", "seqkit_tab2fx": "Convert tabular format (first two/three columns) to FASTA/Q format.", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "biscuit_vcf2bed": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file."}}, "target": "seqkit_tab2fx", "target_idx": 2}
{"id": "mod_pairtools_dedup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find and remove PCR/optical duplicates (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools_prepareforrsem": "Make the output from umi_tools dedup or group compatible with RSEM", "pairtools_dedup": "Find and remove PCR/optical duplicates", "dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "tidk_explore": "`tidk explore` attempts to find the simple telomeric repeat unit in the genome provided.\nIt will report this r", "prinseqplusplus": "PRINSEQ++ is a C++ implementation of the prinseq-lite.pl program. It can be used to filter, reformat or trim g"}}, "target": "pairtools_dedup", "target_idx": 1}
{"id": "mod_refsolver_identify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver (tools: refsolver)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit/index": "Indexes a reference genome for use with Biscuit", "deacon/indexdiff": "Subtract minimizers in deacon index (or fasta file) from another index (A - B)", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "refsolver/identify": "Identify which reference genome a BAM/SAM/CRAM was aligned to using ref-solver", "llamacpppython/run": "Python wrapper for running locally-hosted LLM with llama.cpp"}}, "target": "refsolver/identify", "target_idx": 3}
{"id": "resource_anndata_getsize_2", "category": "resource_profiling", "state": {"process": "ANNDATA_GETSIZE", "tool": "anndata/getsize", "description": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_GETSIZE (Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_18", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "field_constraint_status_1_1", "category": "samplesheet_schema", "state": {"column": "status", "purpose": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'status' (Tissue status for somatic cancer workflows).", "criteria": {"format: file-path": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_bam_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Somatic tumor-normal calling from pre-aligned BAM files. Input files: Coordinate-sorted BAMs with index for tumor and normal samples.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "sample,vcf": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "mod_gridss_preprocess_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and coverage metrics) from an input BAM file prior to assembly and variant calling. (tools: gridss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tetranscripts": "Runs TEtranscripts which summarises transposable element content of a bam file.", "gridss_generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "gridss_assemble": "Assemble breakend contigs for GRIDSS structural variant calling", "fcs_fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi", "gridss_preprocess": "Run the preprocess step of GRIDSS to extract multiple Picard metrics (insert size, MAPQ, CIGAR, IDSV, tag and "}}, "target": "gridss_preprocess", "target_idx": 4}
{"id": "samplesheet_arch_mira_influenza_sc2_6_3", "category": "samplesheet_schema", "state": "nextflow run custom/mira-nf --input samplesheet.csv (Assay: Custom MIRA-NF Influenza / SC2 pipeline)", "question": {"type": "choice", "instructions": "Which columns are standard for Custom MIRA-NF Influenza / SC2 pipeline input samplesheet?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_22", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/pacvar) for PacBio HiFi unaligned BAM variant calling. Input files: Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for PacBio HiFi unaligned BAM variant calling with entry step PBMM2_ALIGN.", "criteria": {"sample,bam,bai": null, "sample,vcf": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "mod_genomad_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download geNomad databases and related files (tools: genomad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "metamdbg/asm": "Metagenome assembler for long-read sequences (HiFi and ONT).", "seqkit/rmdup": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "genomad/download": "Download geNomad databases and related files", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "genomad/download", "target_idx": 3}
{"id": "mod_fastq_removeadapters_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove adapters and merge reads based on various module choices (tools: fastq_removeadapters_merge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_removeadapters_merge": "Remove adapters and merge reads based on various module choices", "fastqc": "Run FastQC on sequenced reads", "icountmini/segment": "Formats a GTF file for use with iCount sigxls", "fastq_shortreads_preprocess_qc": "Quality check and preprocessing subworkflow of Illumina short reads\nthat can do: quality check of input reads ", "pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g"}}, "target": "fastq_removeadapters_merge", "target_idx": 0}
{"id": "mod_t1k_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: t1k)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan/database": "command from run_dbcan to prepare the database for dbCAN annotation.", "t1k/run": "write your description here", "saltshaker/plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "hlala/preparegraph": "Pre-compute the graph index structure.", "t1k/build": "A module to create a reference database and coordinate files for T1K."}}, "target": "t1k/run", "target_idx": 1}
{"id": "resource_autocycler_resolve_2", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_RESOLVE", "tool": "autocycler/resolve", "description": "Resolve trimmed assembly graphs into final contigs within Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_RESOLVE (Resolve trimmed assembly graphs into final contigs within Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_module_metadata_propagation_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "schema_std_rnaseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "description": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/rnaseq?", "criteria": {"patient,sample,vcf,status,cna": null, "sample,bundle,image": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null, "ID,R1,R2,LongFastQ,Fast5": null}}, "target": "sample,fastq_1,fastq_2,strandedness,seq_platform", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_49", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Calling `Channel.fromPath()` inside the body of a process is valid Nextflow DSL2.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_tcoffee_regressive_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "alignoth": "Creating alignment plots from bam files", "stringtie_merge": "Merges the annotation gtf file and the stringtie output gtf files", "suppa_psiperisoform": "Calculate PSI values for transcript isoforms using SUPPA", "tcoffee_regressive": "Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package"}}, "target": "tcoffee_regressive", "target_idx": 4}
{"id": "mod_cellrangerarc_mkgtf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build a filtered gtf needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkgtf command. (tools: cellrangerarc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"muse_sump": null, "salmon_index": null, "cellrangerarc_mkgtf": null, "arriba_download": null, "bowtie_build": null}}, "target": "cellrangerarc_mkgtf", "target_idx": 2}
{"id": "resource_ashlar_2", "category": "resource_profiling", "state": {"process": "ASHLAR", "tool": "ashlar", "description": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASHLAR (Alignment by Simultaneous Harmonization of Layer/Adjacency Registration) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/scrnaseq) for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq. Input files: Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq with entry step FASTQC.", "criteria": {"plate,sample,bam": null, "sample,matrix": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_0_27", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_chipseq_with_control_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/chipseq", "assay_type": "ChIP-seq with IP and input control design", "data_format": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for ChIP-seq with IP and input control design with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null, "sample,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 0}
{"id": "resource_atlas_call_1", "category": "resource_profiling", "state": {"process": "ATLAS_CALL", "tool": "atlas/call", "description": "generate VCF file from a BAM file using various calling methods"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_CALL (generate VCF file from a BAM file using various calling methods) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_1_20", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_malt_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics. (tools: malt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"malt/run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "malt/build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "fcsgx/fetchdb": "Fetches the NCBI FCS-GX database using a provided manifest URL", "maltextract": "Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening", "picard/fastqtosam": "Converts a FASTQ file to an unaligned BAM or SAM file."}}, "target": "malt/build", "target_idx": 1}
{"id": "pipe_all101_pathogensurveillance_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for biosurveillance analysis? Specific context: Surveillance of pathogens using population genomics and sequencing. Topics: biosurveillance, pathogen-identification. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]"}}, "target": "pathogensurveillance", "target_idx": 1}
{"id": "pipe_all101_slamseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for differential-expression analysis? Specific context: SLAMSeq processing and analysis pipeline. Topics: differential-expression, quantseq, slamseq, transcriptomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u"}}, "target": "slamseq", "target_idx": 8}
{"id": "field_constraint_fastq_1_0_11", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "mod_snpsift_split_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits/Joins VCF(s) file into chromosomes (tools: snpsift)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/split": null, "mmseqs/createtaxdb": null, "bcftools/pluginsplit": null, "affy/justrma": null, "snpsift/split": null}}, "target": "snpsift/split", "target_idx": 4}
{"id": "samplesheet_arch_viral_ont_single_1_5", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "schema_std_genephylomodeler_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genephylomodeler", "assay": "genephylomodeler pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/genephylomodeler (A bioinformatics pipeline that fits evolutionary models and )?", "criteria": {"sample,group,path,ref,method": null, "id,fasta,query": null, "id,path": null, "gene_name,alignment,tree,suite,tool": null}}, "target": "gene_name,alignment,tree,suite,tool", "target_idx": 3}
{"id": "mod_pneumocat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine Streptococcus pneumoniae serotype from Illumina paired-end reads (tools: pneumocat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pypgx/preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "pneumocat": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "pairtools/restrict": "Assign restriction fragments to pairs"}}, "target": "pneumocat", "target_idx": 3}
{"id": "resource_bamaligncleaner_3", "category": "resource_profiling", "state": {"process": "BAMALIGNCLEANER", "tool": "bamaligncleaner", "description": "removes unused references from header of sorted BAM/CRAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMALIGNCLEANER (removes unused references from header of sorted BAM/CRAM files.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bbmap_index_3", "category": "resource_profiling", "state": {"process": "BBMAP_INDEX", "tool": "bbmap/index", "description": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_INDEX (Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_qualimap_rnaseq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment data (tools: qualimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clippy": "Runs the Clippy CLIP peak caller", "busco_busco": "Benchmarking Universal Single Copy Orthologs", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "qualimap_rnaseq": "Evaluate alignment data", "bcftools_convert": "Converts certain output formats to VCF"}}, "target": "qualimap_rnaseq", "target_idx": 3}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_5_3", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/bacass, determine the input samplesheet column structure for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "schema_std_rnasplice_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/rnasplice. Description: rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/rnasplice.", "criteria": {"sample,fastq_1,fastq_2,strandedness,condition": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "vcf,fasta,genome,site,source": null}}, "target": "sample,fastq_1,fastq_2,strandedness,condition", "target_idx": 0}
{"id": "mod_gcta_bivariatereml_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run bivariate REML analysis with a single dense GRM (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clame": "binning of metagenomic sequences", "gcta/adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`", "gcta/bivariatereml": "Run bivariate REML analysis with a single dense GRM", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs"}}, "target": "gcta/bivariatereml", "target_idx": 2}
{"id": "mod_imc2mc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes optional hot pixel removal. (tools: imc2mc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"icountmini/summary": "Report proportion of cross-link events/sites on each region type.", "imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op", "deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell", "holodeck/simulate": "Simulate sequencing reads from a reference genome with holodeck", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope"}}, "target": "imc2mc", "target_idx": 1}
{"id": "intent_prepare_data_13", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "ask_question": null, "debug_error": null, "prepare_data": null}}, "target": "prepare_data", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral genome sequencing on Oxford Nanopore MinION / GridION)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "noul_confusing_combine_with_mix_semantics_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_pygenprop_info_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assignments, step assignments, InterProScan matches, and protein sequences. (tools: pygenprop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_dumpsoftwareversions": "Custom module used to dump software versions within the nf-core pipeline template", "pygenprop_info": "Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assign", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "taxpasta_standardise": "Standardise the output of a wide range of taxonomic profilers", "eggnogmapper": "Fast genome-wide functional annotation through orthology assignment."}}, "target": "pygenprop_info", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_2_5", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_36", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_eautils_fastqstats_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate general and per-base statistics from FASTQ files (tools: eautils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "ensemblvep_download": "Ensembl Variant Effect Predictor (VEP). The cache downloading options are controlled through `task.ext.args`.", "ariba_getref": "Download and prepare database for Ariba analysis", "eautils_fastqstats": "Calculate general and per-base statistics from FASTQ files", "gemmi_cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi."}}, "target": "eautils_fastqstats", "target_idx": 3}
{"id": "resource_bedtools_complement_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COMPLEMENT", "tool": "bedtools/complement", "description": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COMPLEMENT (Returns all intervals in a genome that are not covered by at least one interval ) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_gfaffix_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collapse walk-preserving shared affixes in variation graphs in GFA format (tools: gfaffix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gfatools/gfa2fa": "Converts GFA or rGFA files to FASTA", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format", "fastani": "Alignment-free computation of Average Nucleotide Identity (ANI)", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "gfatools/stat": "Summary statistics for GFA files"}}, "target": "gfaffix", "target_idx": 1}
{"id": "mod_viennarna_rnafold_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary structures and partition function of RNAs. (tools: viennarna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "fgumi/clip": "Clip overlapping reads in a BAM file with fgumi", "fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "viennarna/rnafold": "Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary str", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "viennarna/rnafold", "target_idx": 3}
{"id": "mod_glimpse_ligate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenates imputation chunks in a single VCF/BCF file ligating phased information. (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"glimpse/phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "parabricks/minimap2": "NVIDIA Clara Parabricks GPU-accelerated minimap2 for aligning long read sequences against a large reference da", "gatk4/variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo", "glimpse/ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information."}}, "target": "glimpse/ligate", "target_idx": 4}
{"id": "field_constraint_sample_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"format: file-path": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_cellrangeratac_mkref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkref command. (tools: cellranger-atac)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie/build": "Create bowtie index for reference genome", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "cdhit/cdhitest": "Cluster nucleotide sequences using sequence similarity", "cellrangeratac/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkref", "metaspace/download": "A module to download dataset results from the METASPACE platform and save them as CSV files, using a container"}}, "target": "cellrangeratac/mkref", "target_idx": 3}
{"id": "samplesheet_arch_proteomics_dia_3_2", "category": "samplesheet_schema", "state": {"technology": "Mass Spectrometry", "workflow_entry": "INPUT_CHECK", "library_inputs": "Thermo / Bruker RAW or mzML mass spectrometry runs across biological conditions"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Data-Independent Acquisition (DIA) quantitative mass spectrometry with entry step INPUT_CHECK.", "criteria": {"sample,fasta": null, "sample,raw_file,condition": null, "sample,mzml": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,raw_file,condition", "target_idx": 1}
{"id": "mod_centrifuge_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build centrifuge database for taxonomic profiling (tools: centrifuge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash_antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "strobealign": "Align short reads using dynamic seed size with strobemers", "deseq2_differential": "runs a differential expression analysis with DESeq2", "centrifuge_build": "Build centrifuge database for taxonomic profiling"}}, "target": "centrifuge_build", "target_idx": 4}
{"id": "qc_adapt_ont_nanoplot_1_40", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "pipe_all101_oncoanalyser_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A comprehensive cancer DNA/RNA analysis and reporting pipeline. Topics: cancer, clinical, ctdna, dna, exome, longitudinal. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]"}}, "target": "oncoanalyser", "target_idx": 3}
{"id": "mod_plink2_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subset plink pfiles with a text file of variant identifiers (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_extract": "Subset plink pfiles with a text file of variant identifiers", "humann3_humann": "Functional analysis of metagenome or metatranscriptome data", "eigenstratdatabasetools_eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset.", "plink2_pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "plink2_pca": "Perform PCA analysis using PLINK"}}, "target": "plink2_extract", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "data_format": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "mod_biobambam_bamsormadup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Parallel sorting and duplicate marking (tools: biobambam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifitrimmer_trim": "Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/F", "dupradar": "Assessment of duplication rates in RNA-Seq datasets", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "picard_markduplicates": "Locate and tag duplicate reads in a BAM file", "dupblaster": "Streaming duplicate marking for NGS alignments with dupblaster; for maximum throughput it can also run inline "}}, "target": "biobambam_bamsormadup", "target_idx": 2}
{"id": "mod_svync_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to standardize VCF files from structural variant callers (tools: svync)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "gridss/gridss": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "caddsv/run": "Score structural variants with CADD-SV.", "ssuissero": "Serotype prediction of Streptococcus suis assemblies", "svync": "A tool to standardize VCF files from structural variant callers"}}, "target": "svync", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_32", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_picard_liftovervcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lifts over a VCF file from one reference build to another. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O", "scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "picard/liftovervcf": "Lifts over a VCF file from one reference build to another.", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "atlas/call": "generate VCF file from a BAM file using various calling methods"}}, "target": "picard/liftovervcf", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_1_3", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,fastq_1,fastq_2,environment": null, "sample,bam": null, "sample,rrna_fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 0}
{"id": "noul_single_hyphen_cli_params_error_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow, `params.my_var` values can be overridden from the command line using single hyphen `-my_var value`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Genome analysis from reference-compressed CRAM files", "data_format": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Genome analysis from reference-compressed CRAM files?", "criteria": {"sample,vcf": null, "sample,cram": null, "sample,cram,crai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_46", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "subworkflow_pkg_bam_qc_rnaseq_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_QC_RNASEQ", "modules": ["preseq/lcextrap", "qualimap/rnaseq", "dupradar", "subread/featurecounts", "custom/multiqccustombiotype", "samtools/sort", "bam_rseqc"], "description": "Run post-alignment QC tools on RNA-seq BAM files including library complexity"}, "question": {"type": "choice", "instructions": "How should BAM_QC_RNASEQ (preseq/lcextrap, qualimap/rnaseq, dupradar, subread/featurecounts, custom/multiqccustombiotype, samtools/sort, bam_rseqc) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_qc_rnaseq": null, "Local subworkflow BAM_QC_RNASEQ": null}}, "target": "Use nf-core subworkflow bam_qc_rnaseq", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay_type": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "data_format": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,spikein,fastq": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "mod_hamronization_fargene_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize fARGene outputs using the hAMRonization specification (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": null, "hamronization/abricate": null, "miniasm": null, "hamronization/fargene": null, "pindel/pindel": null}}, "target": "hamronization/fargene", "target_idx": 3}
{"id": "mod_gatk4_unmarkduplicates_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool locates and unmark the marked duplicate reads in a BAM or SAM file, where duplicate reads are defined as originating from a single fragment of DNA. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamclipper": "This module is used to clip primer sequences from your alignments.", "entrezdirect/xtract": "Queries an NCBI database using an UID", "gatk4/unmarkduplicates": "This tool locates and unmark the marked duplicate reads in a BAM or SAM file, where duplicate reads are define", "gfatools/stat": "Summary statistics for GFA files", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "gatk4/unmarkduplicates", "target_idx": 2}
{"id": "resource_adapterremoval_4", "category": "resource_profiling", "state": {"process": "ADAPTERREMOVAL", "tool": "adapterremoval", "description": "Trim sequencing adapters and collapse overlapping reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ADAPTERREMOVAL (Trim sequencing adapters and collapse overlapping reads) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_plastid_psite_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate position of ribosomal P-site within ribosome profiling read alignments as a function of read length (tools: plastid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quilt/quilt2": null, "plastid/psite": null, "agat/spfilterfeaturefromkilllist": null, "agat/spextractsequences": null, "openms/peptideindexer": null}}, "target": "plastid/psite", "target_idx": 1}
{"id": "core_tool_picard_markduplicates_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Identify and flag PCR and optical duplicate reads in coordinate-sorted BAM files based on 5-prime mapping coordinates.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"samtools": null, "gatk_markduplicates": null, "picard_markduplicates": null, "sambamba": null, "fastp": null}}, "target": "picard_markduplicates", "target_idx": 2}
{"id": "resource_biohansel_1", "category": "resource_profiling", "state": {"process": "BIOHANSEL", "tool": "biohansel", "description": "Use k-mers to rapidly subtype S. enterica genomes"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOHANSEL (Use k-mers to rapidly subtype S. enterica genomes) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_huggingface_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download a file from a Hugging Face Hub repository using the `hf` CLI (tools: huggingface_hub)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caalm/downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "jvarkit/vcf2table": "Convert VCF to a user friendly table", "picard/collecthsmetrics": "Collects hybrid-selection (HS) metrics for a SAM or BAM file.", "huggingface/download": "Download a file from a Hugging Face Hub repository using the `hf` CLI", "blast/updateblastdb": "Downloads a BLAST database from NCBI"}}, "target": "huggingface/download", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_0_47", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_fastq_fastqc_umitools_fastp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Read QC, UMI extraction and trimming (tools: fastq_fastqc_umitools_fastp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": null, "gapseq/medium": null, "bcftools/isec": null, "fastq_fastqc_umitools_fastp": null, "ariba/getref": null}}, "target": "fastq_fastqc_umitools_fastp", "target_idx": 3}
{"id": "mod_plink2_indeppairwise_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produce pruned set of variants in approximatelinkage equilibrium (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/stats": null, "plink2/pca": null, "plink2/pmerge": null, "arcashla/extract": null, "plink2/indeppairwise": null}}, "target": "plink2/indeppairwise", "target_idx": 4}
{"id": "mod_samtools_reheader_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Replace the header in the bam file with the header generated by the command.\nThis command is much faster than replacing the header with a BAM→SAM→BAM conversion. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"td2_predict": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "samtools_reheader": "Replace the header in the bam file with the header generated by the command.\nThis command is much faster than ", "ascat": "copy number profiles of tumour cells.", "bwafastalign_mem": "Performs fastq alignment to a fasta reference using BWA-FastAlign.", "ucsc_wigtobigwig": "Convert ascii format wig file to binary big wig format"}}, "target": "samtools_reheader", "target_idx": 1}
{"id": "mod_scoary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use pangenome outputs for GWAS (tools: scoary)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_gwas": "Generate GWAS association studies", "pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "regenie_runl1": "Finish REGENIE step 1 from split level-0 prediction files", "scoary": "Use pangenome outputs for GWAS", "nanocomp": "Compare multiple runs of long read sequencing data and alignments"}}, "target": "scoary", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_32", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_1_6", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_0_1", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,fasta": null, "sample,primer_fwd,primer_rev": null, "sample,otu_table": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_blast_blastn_1", "category": "resource_profiling", "state": {"process": "BLAST_BLASTN", "tool": "blast/blastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_25", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_homer_findpeaks_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find peaks with HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annosine": null, "agat/spfilterbyorfsize": null, "homer/findpeaks": null, "ctatsplicing/startocancerintrons": null, "tximeta/tximport": null}}, "target": "homer/findpeaks", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_16", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_lissero_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serogrouping Listeria monocytogenes assemblies (tools: lissero)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bases2fastq": "Demultiplex Element Biosciences bases files", "lissero": "Serogrouping Listeria monocytogenes assemblies", "cellrangerarc_mkgtf": "Module to build a filtered gtf needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkgtf ", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}}, "target": "lissero", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_6_4", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs", "pipeline": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for 16S rRNA / ITS microbiome amplicon profiling input samplesheet?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fastq_1,fastq_2": null, "sample,otu_table": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bcftools_pluginsplit_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSPLIT", "tool": "bcftools/pluginsplit", "description": "Split VCF by sample, creating single- or multi-sample VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSPLIT (Split VCF by sample, creating single- or multi-sample VCFs.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcftools_pluginsetgt_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSETGT", "tool": "bcftools/pluginsetgt", "description": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSETGT (Sets genotypes according to the specified criteria and filtering expressions. Fo) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_tabix_bgzip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Compresses/decompresses files (tools: bgzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"grabix/check": null, "cat/fastq": null, "tabix/bgzip": null, "gnu/split": null, "catpack/addnames": null}}, "target": "tabix/bgzip", "target_idx": 2}
{"id": "mod_trgt_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualize tandem repeats genotyped by TRGT (tools: trgt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"simpleaf_index": null, "genmod_score": null, "trgt_merge": null, "trgt_plot": null, "bam2fastx_bam2fastq": null}}, "target": "trgt_plot", "target_idx": 3}
{"id": "schema_std_marsseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/marsseq. Description: MARS-seq v2 pre-processing pipeline with velocity.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/marsseq.", "criteria": {"id,path": null, "sample,fastq_1,fastq_2,library_id,lane": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "fastq_1,fastq_2,batch,amp_batches,seq_batches", "target_idx": 2}
{"id": "mod_gcta_remlldms_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run REML-LDMS heritability estimation with an MGRM manifest (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/remlldms": "Run REML-LDMS heritability estimation with an MGRM manifest", "gcta/bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "sentieon/collectvcmetrics": "Accelerated implementation of the Picard CollectVariantCallingMetrics tool.", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "manta/somatic": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for "}}, "target": "gcta/remlldms", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_1_4", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,image": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 3}
{"id": "subworkflow_pkg_bam_stringtie_merge_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STRINGTIE_MERGE", "modules": ["stringtie/stringtie", "stringtie/merge"], "description": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a unified annotation."}, "question": {"type": "choice", "instructions": "How should BAM_STRINGTIE_MERGE (stringtie/stringtie, stringtie/merge) be structured in DSL2?", "criteria": {"Local subworkflow BAM_STRINGTIE_MERGE": null, "Leave them out": null, "Use nf-core subworkflow bam_stringtie_merge": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_stringtie_merge", "target_idx": 2}
{"id": "noul_dynamic_resource_allocation_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_picard_collectmultiplemetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect multiple metrics from a BAM file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "tiff_segmentation_vpt": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool", "picard_collectmultiplemetrics": "Collect multiple metrics from a BAM file", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "crumble": "Controllable lossy compression of BAM/CRAM files"}}, "target": "picard_collectmultiplemetrics", "target_idx": 2}
{"id": "core_tool_salmon_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Transcript-level abundance estimation and pseudo-alignment directly from raw paired-end RNA-seq FASTQ reads without full genome mapping.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"rsem": null, "samtools": null, "salmon": null, "featurecounts": null, "kallisto": null}}, "target": "salmon", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_index_dna_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_INDEX_DNA", "modules": ["bowtie2/build", "bwa/index", "bwamem2/index", "dragmap/hashtable", "snapaligner/index"], "description": "Generate aligner index for a reference genome."}, "question": {"type": "choice", "instructions": "How should FASTA_INDEX_DNA (bowtie2/build, bwa/index, bwamem2/index, dragmap/hashtable, snapaligner/index) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_INDEX_DNA": null, "Leave them out": null, "Use nf-core subworkflow fasta_index_dna": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_index_dna", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_6_4", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns are standard for Viral amplicon sequencing with primers input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_blast_blastdbcmd_1", "category": "resource_profiling", "state": {"process": "BLAST_BLASTDBCMD", "tool": "blast/blastdbcmd", "description": "Retrieve entries from a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTDBCMD (Retrieve entries from a BLAST database) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_kmcp_profile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate taxonomic profile from search results (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "kmcp_profile": "Generate taxonomic profile from search results", "tcoffee_seqreformat": "Reformats files with t-coffee", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "kmcp_profile", "target_idx": 2}
{"id": "mod_phispy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict prophages in bacterial genomes (tools: phispy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spmergeannotations": null, "phispy": null, "s4pred/runmodel": null, "agat/spfilterbyorfsize": null, "bcftools/pluginsplit": null}}, "target": "phispy", "target_idx": 1}
{"id": "mod_seqkit_pair_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: match up paired-end reads from two fastq files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ldak/thinpredictors": null, "seqkit/head": null, "seqkit/pair": null, "seqkit/sliding": null, "bam_qc_rnaseq": null}}, "target": "seqkit/pair", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "FAIRE-seq / DNAse-seq open chromatin profiling", "data_format": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bed": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_jvarkit_wgscoverageplotter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot whole genome coverage from BAM/CRAM file as SVG (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metacache_query": null, "jvarkit_wgscoverageplotter": null, "bamclipper": null, "homer_annotatepeaks": null, "bamaligncleaner": null}}, "target": "jvarkit_wgscoverageplotter", "target_idx": 1}
{"id": "resource_amulety_embed_3", "category": "resource_profiling", "state": {"process": "AMULETY_EMBED", "tool": "amulety/embed", "description": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_EMBED (A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) ) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_glimpse_ligate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenates imputation chunks in a single VCF/BCF file ligating phased information. (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samshee": "Module to validate illumina® Sample Sheet v2 files.", "wisecondorx_predict": "Find copy number aberrations", "glimpse_ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information.", "glimpse2_ligate": "Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks tha", "glimpse_phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods"}}, "target": "glimpse_ligate", "target_idx": 2}
{"id": "mod_propr_logratio_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transform the data matrix using centered logratio transformation (CLR) or additive logratio transformation (ALR) (tools: propr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr_propr": "Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coeff", "propr_logratio": "Transform the data matrix using centered logratio transformation (CLR) or additive logratio transformation (AL", "plink_indeppairwise": "Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. Pairs of varia", "cnvpytor_callcnvs": "Command line tool for calling CNVs in whole genome sequencing data", "propr_grea": "Perform Gene Ratio Enrichment Analysis"}}, "target": "propr_logratio", "target_idx": 1}
{"id": "mod_seqkit_fq2fa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert FASTQ to FASTA format (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_concordance": "Evaluate concordance of an input VCF against a validated truth VCF", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "sourmash_index": "Create a database of sourmash signatures (a group of FracMinHash sketches) to be used as references.", "seqkit_fq2fa": "Convert FASTQ to FASTA format"}}, "target": "seqkit_fq2fa", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_2_12", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_25", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "core_tool_cellranger_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Demultiplexing, barcode processing, alignment, and UMI counting for 10x Genomics single-cell RNA-seq libraries.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"cellranger": "Set of analysis pipelines that process Chromium single cell data to output expression matrices", "seurat": "R analysis package", "starsolo": "STAR single-cell mode", "alevin": "Salmon single-cell", "kallisto_bustools": "Single-cell quantifier"}}, "target": "cellranger", "target_idx": 0}
{"id": "mod_topas_gencons_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage present in ancient DNA (tools: topas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"midas/run": "A tool to estimate bacterial species abundance", "bcftools/consensus": "Compresses VCF files", "topas/gencons": "Create fasta consensus with TOPAS toolkit with options to penalize substitutions for typical DNA damage presen", "bedtools/intersect": "Allows one to screen for overlaps between two sets of genomic features.", "autocycler/combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}}, "target": "topas/gencons", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_0_23", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "field_constraint_fastq_2_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "mod_catpack_bins_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack/summarise": "Summarises results from CAT/BAT/RAT classification steps", "catpack/bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "catpack/download": "Downloads the required files for either Nr or GTDB for building into a CAT database", "gcta/addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "deeptools/bigwigcompare": "Compare two bigWig files based on the number of mapped reads"}}, "target": "catpack/bins", "target_idx": 1}
{"id": "resource_ariba_run_0", "category": "resource_profiling", "state": {"process": "ARIBA_RUN", "tool": "ariba/run", "description": "Query input FASTQs against Ariba formatted databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_RUN (Query input FASTQs against Ariba formatted databases) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_vcf_annotation_pipeline_3_0", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Downstream functional annotation of pre-called VCF files with entry step ENSEMBLVEP.", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "mod_samblaster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This module combines samtools and samblaster in order to use\nsamblaster capability to filter or tag SAM files, with the advantage\nof maintaining both input and output in BAM format.\nSamblaster input must contain a sequence header: for this reason it has been piped\nwith the \"samtools view -h\" command.\nAdditional desired arguments for samtools can be passed using:\noptions.args2 for the input bam file\noptions.args3 for the output bam file (tools: samblaster)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"optitype": "Perform HLA-I typing of sequencing data", "crisprcleanr_normalize": "remove false positives of functional crispr genomics due to CNVs", "samblaster": "This module combines samtools and samblaster in order to use\nsamblaster capability to filter or tag SAM files,", "deeptools_multibamsummary": "Computes read coverage for genomic regions (bins) across the entire genome.", "clame": "binning of metagenomic sequences"}}, "target": "samblaster", "target_idx": 2}
{"id": "mod_hlala_typing_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs HLA typing based on a population reference graph and employs a new linear projection method to align reads to the graph. (tools: hlala)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety/antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety.", "arcashla/extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "finaletoolkit/adjustwps": "Adjusts raw Windowed Protection Score (WPS) by applying a median filter\nand Savitsky-Golay filter.", "hlala/typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "t1k/run": "write your description here"}}, "target": "hlala/typing", "target_idx": 3}
{"id": "mod_fq_generate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fq generate is a FASTQ file pair generator. It creates two reads, formatting names as described by Illumina. While generate creates \"valid\" FASTQ reads, the content of the files are completely random. The sequences do not align to any genome. This requires a seed (--seed) to be supplied in ext.args. (tools: fq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "ariba_run": "Query input FASTQs against Ariba formatted databases", "opt_flip": "flip corrects probes that are aligning to the opposite strand of their intended target genes by reverse comple", "fq_generate": "fq generate is a FASTQ file pair generator. It creates two reads, formatting names as described by Illumina. W", "picard_collectinsertsizemetrics": "Collect metrics about the insert size distribution of a paired-end library."}}, "target": "fq_generate", "target_idx": 3}
{"id": "schema_std_methylong_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylong", "assay": "methylong pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/methylong (Extract methylation calls from long reads (ONT/ PacBio) )?", "criteria": {"sample,fastq_1,fastq_2,genome": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,group,path,ref,method": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "sample,group,path,ref,method", "target_idx": 2}
{"id": "mod_krakentools_extractkrakenreads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract reads classified at any user-specified taxonomy IDs. (tools: krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_bracken": null, "kraken2_build": null, "gstama_merge": null, "krakentools_extractkrakenreads": null, "getorganelle_fromreads": null}}, "target": "krakentools_extractkrakenreads", "target_idx": 3}
{"id": "schema_std_drop_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/drop. Description: Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/drop.", "criteria": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,seed": null, "sample,fastq_1,fastq_2,replicate,antibody": null}}, "target": "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE", "target_idx": 0}
{"id": "mod_rundbcan_cazymeannotation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CAZyme annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZymes) from genomic data using the dbCAN annotation tool. (tools: dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan_easycgc": null, "rclone_checksum": null, "upp_align": null, "rundbcan_easysubstrate": null, "rundbcan_cazymeannotation": null}}, "target": "rundbcan_cazymeannotation", "target_idx": 4}
{"id": "samplesheet_arch_ont_metagenome_single_4_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: High molecular weight environmental metagenomic long reads per sampling site?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "mod_gatk4_selectvariants_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select a subset of variants from a VCF file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "deeparg/predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "gatk4/baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "expansionhunterdenovo/merge": "Merge STR profiles into a multi-sample STR profile", "gatk4/selectvariants": "Select a subset of variants from a VCF file"}}, "target": "gatk4/selectvariants", "target_idx": 4}
{"id": "schema_std_pairgenomealign_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pairgenomealign", "assay": "pairgenomealign pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/pairgenomealign (Pairwise genome comparison pipeline using the LAST software )?", "criteria": {"sample,fasta": null, "sample,seed": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "sample,fasta", "target_idx": 0}
{"id": "resource_blast_makeblastdb_3", "category": "resource_profiling", "state": {"process": "BLAST_MAKEBLASTDB", "tool": "blast/makeblastdb", "description": "Builds a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_MAKEBLASTDB (Builds a BLAST database) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/riboseq --input samplesheet.csv (Assay: Ribosome profiling (Ribo-seq) footprint sequencing)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Ribosome profiling (Ribo-seq) footprint sequencing with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_40", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_salmon_quant_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: gene/transcript quantification with Salmon (tools: salmon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hamronization_summarize": null, "bbmap_index": null, "biscuit_index": null, "rseqc_innerdistance": null, "salmon_quant": null}}, "target": "salmon_quant", "target_idx": 4}
{"id": "intent_build_pipeline_3", "category": "intent_routing", "state": "Classify this user request: \"Write a Nextflow DSL2 workflow that takes raw ONT FASTQ files and runs Flye assembly followed by Medaka polishing.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "prepare_data": null, "build_pipeline": null, "ask_question": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "mod_bowtie2_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds bowtie index for reference genome (tools: bowtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl/align": null, "rseqc/bamstat": null, "bowtie2/build": null, "catpack/prepare": null, "hisat3n/build": null}}, "target": "bowtie2/build", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_34", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bismark_coverage2cytosine_1", "category": "resource_profiling", "state": {"process": "BISMARK_COVERAGE2CYTOSINE", "tool": "bismark/coverage2cytosine", "description": "Relates methylation calls back to genomic cytosine contexts."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_COVERAGE2CYTOSINE (Relates methylation calls back to genomic cytosine contexts.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Visium spatial transcriptomics with histology image)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for 10x Visium spatial transcriptomics with histology image with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "mod_hasheddrops_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generating cell hashing calls from a matrix of count data. (tools: hasheddrops)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"isoseq/refine": "Remove polyA tail and artificial concatemers", "parabricks/fq2bam": "NVIDIA Clara Parabricks GPU-accelerated alignment, sorting, BQSR calculation, and duplicate marking. Note this", "gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU", "hasheddrops": "Generating cell hashing calls from a matrix of count data.", "bff": "Generating cell hashing calls from a matrix of count data."}}, "target": "hasheddrops", "target_idx": 3}
{"id": "mod_cooler_makebins_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate fixed-width genomic bins (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash_sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "cooler_digest": "Generate fragment-delimited genomic bins", "cooler_makebins": "Generate fixed-width genomic bins", "fastq_subsample_fq_salmon": "Subsample fastq", "cooler_dump": "Dump a cooler’s data to a text stream."}}, "target": "cooler_makebins", "target_idx": 2}
{"id": "mod_vg_deconstruct_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deconstruct snarls present in a variation graph in GFA format to variants in VCF format (tools: vg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_call": null, "bcftools_annotate": null, "vg_deconstruct": null, "telescope_assign": null, "bam_impute_stitch": null}}, "target": "vg_deconstruct", "target_idx": 2}
{"id": "mod_fastk_fastk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast K-mer counter for high-fidelity shotgun datasets (tools: fastk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon/table": "Generate a multi-sample report file from the output of ganon report runs", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "fastplong": "Perform adapter/quality trimming and QC on long sequencing reads (ONT, PacBio, etc.)", "fastk/fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "vcfanno": "quickly annotate your VCF with any number of INFO fields from any number of VCFs or BED files"}}, "target": "fastk/fastk", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_25", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/atacseq --input samplesheet.csv (Assay: ATAC-seq chromatin accessibility with biological replicates)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: ATAC-seq chromatin accessibility with biological replicates.", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "noul_file_pairing_in_channel_tuples_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_rtgtools_pedfilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a PED file to VCF headers (tools: rtgtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "pairix": "a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates", "crabs_insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR.", "atlas_call": "generate VCF file from a BAM file using various calling methods", "rtgtools_pedfilter": "Converts a PED file to VCF headers"}}, "target": "rtgtools_pedfilter", "target_idx": 4}
{"id": "schema_std_lsmquant_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/lsmquant. Description: A pipeline for processing and analysis of light-sheet microscopy images..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/lsmquant.", "criteria": {"gene_name,alignment,tree,suite,tool": null, "sample_id,img_directory,parameter_file": null, "id,raw_file": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null}}, "target": "sample_id,img_directory,parameter_file", "target_idx": 1}
{"id": "mod_wipertools_fastqscatter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool of the wipertools suite that splits FASTQ files into chunks (tools: fastqscatter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "wipertools/fastqscatter": "A tool of the wipertools suite that splits FASTQ files into chunks", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "seqkit/pair": "match up paired-end reads from two fastq files", "bcftools/pluginfixploidy": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignmen"}}, "target": "wipertools/fastqscatter", "target_idx": 1}
{"id": "pipe_all101_nanostring_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: An analysis pipeline for Nanostring nCounter expression data.. Topics: nanostring, nanostringnorm. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]"}}, "target": "nanostring", "target_idx": 2}
{"id": "intent_ask_question_1", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "prepare_data": null, "ask_question": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 2}
{"id": "intent_debug_error_16", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "debug_error", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_3_1", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Oxford Nanopore direct RNA with entry step NANOPLOT.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_biscuit_biscuitblaster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/samples": "Write sample names and path to reference genome of an alignment to a text file.", "plasmidid": "assembles bacterial plasmids", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "biscuit/epiread": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compl", "biscuit/biscuitblaster": "A fast, compact one-liner to produce duplicate-marked, sorted, and indexed BAM files using Biscuit"}}, "target": "biscuit/biscuitblaster", "target_idx": 4}
{"id": "pipe_all101_createtaxdb_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Parallelised and automated construction of metagenomic classifier databases of different tools. Topics: database, database-builder, metagenomic-profiling, metagenomics, profiling, taxonomic-profiling. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"coproid": null, "createtaxdb": null, "mcmicro": null, "methylseq": null, "multiplesequencealign": null, "seqsubmit": null, "genomeassembler": null, "crisprseq": null, "nascent": null, "reportho": null}}, "target": "createtaxdb", "target_idx": 1}
{"id": "mod_basicpy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BaSiCPy is a python package for background and shading correction of optical microscopy images. It is developed based on the Matlab version of BaSiC tool with major improvements in the algorithm. (tools: basicpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope", "bftools_showinf": "Extract OME xml data from OME-tif", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "chromograph": "Chromograph is a python package to create PNG images from genetics data such as BED and WIG files.", "gem2_gemindexer": "Create a GEM index from a FASTA file"}}, "target": "basicpy", "target_idx": 0}
{"id": "resource_bbmap_pileup_4", "category": "resource_profiling", "state": {"process": "BBMAP_PILEUP", "tool": "bbmap/pileup", "description": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_PILEUP (Calculates per-scaffold or per-base coverage information from an unsorted sam or) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_last_train_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find suitable score parameters for sequence alignment (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"viennarna_rnafold": "Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary str", "last_dotplot": "Makes a dotplot (Oxford Grid) of pair-wise sequence alignments", "last_train": "Find suitable score parameters for sequence alignment", "last_postmask": "Post-alignment masking", "bedtools_map": "Allows one to screen for overlaps between two sets of genomic features."}}, "target": "last_train", "target_idx": 2}
{"id": "noul_undeclared_process_file_inputs_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_0_3", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "template": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "mod_ensemblvep_filtervep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter variants based on Ensembl Variant Effect Predictor (VEP) annotations. (tools: ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv_annotsv": "Annotation and Ranking of Structural Variation", "ensemblvep_filtervep": "Filter variants based on Ensembl Variant Effect Predictor (VEP) annotations.", "coptr_estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "mapdamage2": "Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads ge", "annotsv_installannotations": "Install the AnnotSV annotations"}}, "target": "ensemblvep_filtervep", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_27", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "noul_file_pairing_in_channel_tuples_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `tuple val(meta), path('*.vcf.gz'), path('*.tbi')` bundles index files with data files.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_3_0", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hybrid bacterial assembly combining short Illumina and long Nanopore reads with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "mod_vcf2db_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to create a Gemini-compatible DB file from an annotated VCF (tools: vcf2db)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirdeep2/mirdeep2": null, "vcf2db": null, "aardvark/compare": null, "aardvark/merge": null, "vembrane/filter": null}}, "target": "vcf2db", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_extract_kraken_krakentools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS", "modules": ["kraken2/kraken2", "krakentools/extractkrakenreads"], "description": "Extract classified Kraken2 reads by taxonomic id"}, "question": {"type": "choice", "instructions": "How should FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS (kraken2/kraken2, krakentools/extractkrakenreads) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_extract_kraken_krakentools": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_EXTRACT_KRAKEN_KRAKENTOOLS": null}}, "target": "Use nf-core subworkflow fastq_extract_kraken_krakentools", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_5", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "noul_invalid_process_communication_via_globals_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "core_tool_interproscan_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Scan protein and nucleotide sequences against multiple member databases to identify structural domains, functional sites, and protein families.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"diamond": "Fast protein aligner", "hmmer": "HMM protein search", "interproscan": "Scans protein sequences against InterPro member databases (Pfam, PRINTS, PROSITE)", "blastp": "Protein blast", "eggnog": "Orthology mapper"}}, "target": "interproscan", "target_idx": 2}
{"id": "mod_gtf_hybridmerge_gffcompare_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a hybrid GTF by classifying a novel-transcript GTF against a reference\nannotation with gffcompare, filtering the resulting annotated GTF down to a\nuser-supplied set of class codes (e.g. \"u\" for novel intergenic), optionally\nsubtracting features that overlap a user-supplied blacklist BED, and merging\nthe survivors into an annotation backbone GTF. Gene rows missing from the\nbackbone for surviving novel transcripts are synthesised with coordinates\nspanning the union of their child transcripts so the output is a\nself-consistent GTF.\n\nInput format scope: standard GTF2 with `gene_id` / `transcript_id`\nattributes in column 9 and `gene` / `transcript` (and child `exon` etc.)\nfeature types in column 3. GFF3 dialects (Parent= / ID= attributes) and\nprokaryotic GTFs without transcript rows are out of scope.\n\nResource sizing: GAWK steps hold the full input in memory under\n`process_single`. Fine for annotation-scale GTFs; for >~500 MB inputs\noverride `memory` / `cpus` directly via `withName`. (tools: gtf_hybridmerge_gffcompare)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mafft_guidetree": "Guide tree rendering using MAFFT", "hamronization_summarize": "Tool to summarize and combine all hAMRonization reports into a single file", "gtf_hybridmerge_gffcompare": "Build a hybrid GTF by classifying a novel-transcript GTF against a reference\nannotation with gffcompare, filte", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file"}}, "target": "gtf_hybridmerge_gffcompare", "target_idx": 2}
{"id": "mod_segemehl_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection (tools: segemehl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr_estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "gatk4_estimatelibrarycomplexity": "Estimates the numbers of unique molecules in a sequencing library.", "segemehl_align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection"}}, "target": "segemehl_align", "target_idx": 4}
{"id": "local_subworkflow_prepontreads_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "How should PREPONTREADS (porechop, nanoplot) be built?", "criteria": {"Local subworkflow PREPONTREADS": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 0}
{"id": "mod_bcftools_pluginimputeinfo_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available. (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/concat": "Concatenate VCF files", "hmmer/hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "foldseek/easysearch": "Search for protein structural hits against a foldseek database of protein structures", "bcftools/pluginimputeinfo": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO met", "bcftools/convert": "Converts certain output formats to VCF"}}, "target": "bcftools/pluginimputeinfo", "target_idx": 3}
{"id": "resource_bcftools_pluginfilltags_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFILLTAGS", "tool": "bcftools/pluginfilltags", "description": "Compute and fill various INFO tags"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFILLTAGS (Compute and fill various INFO tags) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_gatk4spark_markduplicates_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originating from a single fragment of DNA. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4spark/markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "ascat": "copy number profiles of tumour cells.", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}}, "target": "gatk4spark/markduplicates", "target_idx": 0}
{"id": "mod_gapseq_fill_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform gap filling on draft metabolic model (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann/insilicolibrarygeneration": "Generate in silico predicted spectral library using DIA-NN deep learning predictor.\nThis module uses DIA-NN so", "gatk4/selectvariants": "Select a subset of variants from a VCF file", "gapseq/fill": "Perform gap filling on draft metabolic model", "gapseq/requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "gapseq/draft": "Create draft metabolic model from pathway and transporter predictions"}}, "target": "gapseq/fill", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_27", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_smrnaseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A small-RNA sequencing analysis pipeline. Topics: small-rna, smrna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scrnaseq": null, "smrnaseq": null, "demultiplex": null, "bacass": null, "rnavar": null}}, "target": "smrnaseq", "target_idx": 1}
{"id": "subworkflow_pkg_bam_cnv_wisecondorx_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CNV_WISECONDORX", "modules": ["wisecondorx/convert", "wisecondorx/predict"], "description": "A subworkflow for calling CNVs using WisecondorX"}, "question": {"type": "choice", "instructions": "How should BAM_CNV_WISECONDORX (wisecondorx/convert, wisecondorx/predict) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_CNV_WISECONDORX": null, "Use nf-core subworkflow bam_cnv_wisecondorx": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_cnv_wisecondorx", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_38", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_bigslice_bigslice_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenBank format along with an HMM database and produces a SQLite database and FASTA outputs of predicted features. (tools: bigslice)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"civicpy/annotate": "A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations o", "cellrangeratac/count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "bigslice/bigslice": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenB", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "bigslice/bigslice", "target_idx": 2}
{"id": "mod_kraken2_buildstandard_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads and builds Kraken2 standard database (tools: kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gemmi_cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "kraken2_buildstandard": "Downloads and builds Kraken2 standard database", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "samplesheetparser_info": "Display a structured JSON summary of an Illumina SampleSheet.csv (V1 or V2)\nincluding format version, sample c", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "kraken2_buildstandard", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Multi-lane Illumina sequencing run of clinical samples. Input files: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_bacass_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Simple bacterial assembly and annotation pipeline. Topics: assembly, bacterial-genomes, denovo, denovo-assembly, genome-assembly, hybrid-assembly. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]"}}, "target": "bacass", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_bam_indexed_7_1", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam,bai": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "mod_samtools_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort SAM/BAM/CRAM file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ivar_trim": "Trim primer sequences rom a BAM file with iVar", "picard_scatterintervalsbyns": "Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into inte", "samtools_sort": "Sort SAM/BAM/CRAM file", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast "}}, "target": "samtools_sort", "target_idx": 2}
{"id": "subworkflow_pkg_quantify_rsem_3", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_RSEM", "modules": ["rsem/calculateexpression", "sentieon/rsemcalculateexpression", "custom/rsemmergecounts", "quant_tximport_summarizedexperiment"], "description": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_RSEM (rsem/calculateexpression, sentieon/rsemcalculateexpression, custom/rsemmergecounts, quant_tximport_summarizedexperiment) be structured in DSL2?", "criteria": {"Use nf-core subworkflow quantify_rsem": null, "Leave them out": null, "Local subworkflow QUANTIFY_RSEM": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow quantify_rsem", "target_idx": 0}
{"id": "pipe_all101_proteogenomicsdb_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis.. Topics: cosmic, gnomad, protein-databases, proteogenomics, proteomics, pypgatk. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "metapep": "From metagenomes to epitopes and beyond"}}, "target": "proteogenomicsdb", "target_idx": 3}
{"id": "resource_blast_tblastn_4", "category": "resource_profiling", "state": {"process": "BLAST_TBLASTN", "tool": "blast/tblastn", "description": "Queries a BLAST DNA database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_TBLASTN (Queries a BLAST DNA database) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_43", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_rtn_tni_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses the RTN R package for transcriptional regulatory network inference (TNI). (tools: rtn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem3/index": "Create bwa-mem3 index for reference genome", "parabricks/dbsnp": "NVIDIA Clara Parabricks GPU-accelerated variant calls annotation based on dbSNP database", "proseg/proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "rtn/tni": "Uses the RTN R package for transcriptional regulatory network inference (TNI)."}}, "target": "rtn/tni", "target_idx": 4}
{"id": "samplesheet_arch_viral_ont_single_2_4", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons", "pipeline": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_stacks_refmap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available. (tools: stacks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "stacks/refmap": "ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available.", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "stacks/refmap", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_6_5", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns are standard for Long-read Oxford Nanopore environmental metagenomic sequencing input samplesheet?", "criteria": {"sample,fastq_1,group": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_picard_renamesampleinvcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: changes name of sample in the vcf file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/renamesampleinvcf": "changes name of sample in the vcf file", "centrifuger/centrifuger": "Classification of sequencing reads using the Centrifuger tool.", "oatk": "An nf-core module for the OATK", "picard/bedtointervallist": "Creates an interval list from a bed file and a reference dict", "picard/addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group"}}, "target": "picard/renamesampleinvcf", "target_idx": 0}
{"id": "schema_std_reportho_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/reportho. Description: nf-core pipeline for comparative analysis of ortholog predictions.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/reportho.", "criteria": {"sample,vcf,tbi": null, "id,fasta,query": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,seq_data,pbi,start_from": null}}, "target": "id,fasta,query", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_1_2", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter", "pipeline": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1,mirna_id": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_24", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_1_4", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_41", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "core_tool_kraken2_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Exact k-mer matching taxonomic classifier mapping metagenomic reads to bacterial and viral reference genomes with lowest common ancestor algorithm.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"kraken2": "Taxonomic sequence classification system that uses exact k-mer matches", "metaphlan": "Marker gene classifier", "motus": "Marker gene classifier", "diamond": "Protein aligner", "centrifuge": "Taxonomic classifier"}}, "target": "kraken2", "target_idx": 0}
{"id": "resource_bbmap_clumpify_0", "category": "resource_profiling", "state": {"process": "BBMAP_CLUMPIFY", "tool": "bbmap/clumpify", "description": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_CLUMPIFY (Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "local_subworkflow_prepilluminareads_2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPILLUMINAREADS (trimmomatic).", "criteria": {"Use nf-core subworkflow prepilluminareads": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPILLUMINAREADS": null, "Leave them out": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 2}
{"id": "mod_survivor_bedpetovcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a bedpe file to a VCF file (beta version) (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtools_vcftobedpe": "Convert a VCF file to a BEDPE file.", "fcsgx_rungx": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to screen and remove foreign contamination from ", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "ampir": "A fast and user-friendly method to predict antimicrobial peptides (AMPs) from any given size protein dataset. ", "survivor_bedpetovcf": "Converts a bedpe file to a VCF file (beta version)"}}, "target": "survivor_bedpetovcf", "target_idx": 4}
{"id": "mod_repeatmodeler_builddatabase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a database for RepeatModeler (tools: repeatmodeler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"repeatmodeler/builddatabase": "Create a database for RepeatModeler", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "mummer": "MUMmer is a system for rapidly aligning entire genomes", "blast/blastn": "Queries a BLAST DNA database", "alignoth": "Creating alignment plots from bam files"}}, "target": "repeatmodeler/builddatabase", "target_idx": 0}
{"id": "pipe_all101_atacseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: ATAC-seq peak-calling and QC analysis pipeline. Topics: atac-seq, chromatin-accessibiity. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"chipseq": null, "spatialaxe": null, "reportho": null, "atacseq": null, "hgtseq": null, "funcprofiler": null, "methylseq": null, "pangenome": null}}, "target": "atacseq", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_6_4", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness", "pipeline": "nf-core/riboseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ribosome profiling (Ribo-seq) footprint sequencing input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "sample,cdna_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_19", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_bclconvert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Illumina BCL files (tools: bclconvert)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mgikit_demultiplex": "Demultiplex MGI fastq files", "qcat": "Demultiplexer for Nanopore samples", "fibertoolsrs_extract": "Extract Fiber-seq information (such as m6A, CpG, nucleosomes, and MSPs) from BAM file into BED file", "toulligqc": "A post sequencing QC tool for Oxford Nanopore sequencers", "bclconvert": "Demultiplex Illumina BCL files"}}, "target": "bclconvert", "target_idx": 4}
{"id": "mod_fastk_histex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A fast K-mer counter for high-fidelity shotgun datasets (tools: fastk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_gtf_bam_rpbp": null, "fastk/fastk": null, "ganon/classify": null, "fastk/histex": null, "regenie/step2": null}}, "target": "fastk/histex", "target_idx": 3}
{"id": "mod_archive_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip (tools: archive_extract)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2/pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "archive_extract": "Extract archive(s) from any format\nCurrently supported format are .gz, .tar.gz, .zip", "tar": "Compress directories into tarballs with various compression options", "find/concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate"}}, "target": "archive_extract", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_2_5", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_tcoffee_seqreformat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reformats files with t-coffee (tools: tcoffee)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "methurator/gtestimator": "Run estimator for DNA methylation sequencing saturation.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "tcoffee/seqreformat": "Reformats files with t-coffee", "bam_markduplicates_samtools": "Samtools markduplicate SAM/BAM/CRAM file"}}, "target": "tcoffee/seqreformat", "target_idx": 3}
{"id": "mod_metaspace_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to download dataset results from the METASPACE platform and save them as CSV files, using a containerized Python script. Inputs are provided via a CSV file or a list of datasets, with results saved to a specified output directory. (tools: metaspace2020)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"csvtk/mutate2": "Create a new column from selected fields by awk-like arithmetic/string expressions", "csvtk/split": "Splits CSV/TSV into multiple files according to column values", "learnmsa/align": "Align sequences using learnMSA", "metaspace/download": "A module to download dataset results from the METASPACE platform and save them as CSV files, using a container", "methurator/gtestimator": "Run estimator for DNA methylation sequencing saturation."}}, "target": "metaspace/download", "target_idx": 3}
{"id": "resource_aardvark_compare_4", "category": "resource_profiling", "state": {"process": "AARDVARK_COMPARE", "tool": "aardvark/compare", "description": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AARDVARK_COMPARE (A tool to evaluate variant calling performance by comparing a query VCF against ) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_vcf_impute_glimpse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference panel, and genetic maps to perform imputation\nand outputs phased and imputed VCF files.\nMeta map of all channels, except ch_input, will be used to perform joint operations.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: vcf_impute_glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "galah": "Cluster genome FASTA files by average nucleotide identity", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "clame": "binning of metagenomic sequences", "glimpse2/ligate": "Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks tha"}}, "target": "vcf_impute_glimpse", "target_idx": 0}
{"id": "schema_std_crisprseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/crisprseq", "description": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments using targeted next generation sequencing (NGS) data (`targeted`) as well as the discovery of important genes from knock-out or activation CRISPR-Cas9 screens using CRISPR pooled DNA (`screening`).", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/crisprseq?", "criteria": {"sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,condition,reference": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,condition,reference", "target_idx": 1}
{"id": "mod_fcs_fcsgx_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excluding the given taxid. (tools: fcs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fcs/fcsgx": "Run FCS-GX on assembled genomes. The contigs of the assembly are searched against a reference database excludi", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ale": "ALE: assembly likelihood estimator.", "falint": "A fasta linter/validator", "parabricks/haplotypecaller": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating GATK haplotypecaller."}}, "target": "fcs/fcsgx", "target_idx": 0}
{"id": "mod_fasta_bgzip_index_dict_samtools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA file. (tools: fasta_bgzip_index_dict_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paraphase": "HiFi-based caller for highly homologous genes", "fasta_bgzip_index_dict_samtools": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA f", "grabix_check": "Checks if the input file is bgzip compressed or not", "eagle2": "Perform phasing of genotyped data with or without a reference panel", "samtools_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP"}}, "target": "fasta_bgzip_index_dict_samtools", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_33", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_2_4", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "inputs": "BGZF-compressed VCF files with companion Tabix index files", "pipeline": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf,tbi": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "intent_ask_question_8", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_1_24", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "field_constraint_sample_1_9", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null, "type: integer": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "noul_default_empty_channel_behavior_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_amplicon_16s_paired_4_3", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "template": "nf-core/ampliseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs?", "criteria": {"sample,primer_fwd,primer_rev": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_17", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_datavzrd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables. (tools: datavzrd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"drep/compare": null, "bcftools/rohviz": null, "datavzrd": null, "varlociraptor/preprocess": null, "getorganelle/config": null}}, "target": "datavzrd", "target_idx": 2}
{"id": "field_constraint_expected_cells_1_13", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "mod_presto_filterseq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter reads by quality score. (tools: presto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "plink_ld": "LD analysis in PLINK examines genetic variant associations within populations", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "presto_filterseq": "Filter reads by quality score.", "nanoq": "Nanoq implements ultra-fast read filters and summary reports for high-throughput nanopore reads."}}, "target": "presto_filterseq", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_4_2", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs?", "criteria": {"sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_sex_1_12", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "field_constraint_sex_3_4", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "resource_bandage_image_2", "category": "resource_profiling", "state": {"process": "BANDAGE_IMAGE", "tool": "bandage/image", "description": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BANDAGE_IMAGE (Render an assembly graph in GFA 1.0 format to PNG and SVG image formats) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_nucmer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences. (tools: nucmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo", "amulety/translate": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast.", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "nucmer": "NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences."}}, "target": "nucmer", "target_idx": 4}
{"id": "noul_dynamic_resource_allocation_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_1_3", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multi-taxonomic profiling of complex metagenomic shotgun reads?", "criteria": {"sample,kraken_db": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_qc_trim_filter_setstrandedness_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS", "modules": ["bbmap/bbsplit", "cat/fastq", "fastqc", "fq/lint", "fastq_remove_rrna", "fastq_subsample_fq_salmon", "fastq_fastqc_umitools_trimgalore", "fastq_fastqc_umitools_fastp"], "description": "Performs linting, quality control, trimming, filtering, and strandedness determination on RNA-seq FASTQ files, preparing them for downstream analysis."}, "question": {"type": "choice", "instructions": "How should FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS (bbmap/bbsplit, cat/fastq, fastqc, fq/lint, fastq_remove_rrna, fastq_subsample_fq_salmon, fastq_fastqc_umitools_trimgalore, fastq_fastqc_umitools_fastp) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness": null, "Local subworkflow FASTQ_QC_TRIM_FILTER_SETSTRANDEDNESS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_qc_trim_filter_setstrandedness", "target_idx": 1}
{"id": "resource_artic_guppyplex_5", "category": "resource_profiling", "state": {"process": "ARTIC_GUPPYPLEX", "tool": "artic/guppyplex", "description": "Aggregates fastq files with demultiplexed reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_GUPPYPLEX (Aggregates fastq files with demultiplexed reads) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_1_5", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "template": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,bam": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_18", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_samtools_sormadup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collate/Fixmate/Sort/Markdup SAM/BAM/CRAM file (tools: samtools_cat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cat_fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "samtools_sormadup": "Collate/Fixmate/Sort/Markdup SAM/BAM/CRAM file", "samtools_collate": "shuffles and groups reads together by their names", "ngmaster": "Serotyping Neisseria gonorrhoeae assemblies", "humann3_renorm": "Normalizing RPKs to relative abundance"}}, "target": "samtools_sormadup", "target_idx": 1}
{"id": "mod_genomad_endtoend_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify mobile genetic elements present in genomic assemblies (tools: genomad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf_annotate_ensemblvep": "Perform annotation with ensemblvep and bgzip + tabix index the resulting VCF file", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "metamdbg/asm": "Metagenome assembler for long-read sequences (HiFi and ONT).", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "genomad/endtoend": "Identify mobile genetic elements present in genomic assemblies"}}, "target": "genomad/endtoend", "target_idx": 4}
{"id": "mod_survivor_simsv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simulate an SV VCF file based on a reference genome (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caddsv_get": null, "rclone_copy": null, "annotsv_annotsv": null, "survivor_simsv": null, "wisecondorx_gender": null}}, "target": "survivor_simsv", "target_idx": 3}
{"id": "mod_meryl_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A genomic k-mer counter (and sequence utility) with nice features. (tools: meryl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkv_downloaddatabase": "Construct the database necessary for checkv's quality assessment", "mafft_guidetree": "Guide tree rendering using MAFFT", "meryl_count": "A genomic k-mer counter (and sequence utility) with nice features.", "fastk_fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "ganon_classify": "Classify FASTQ files against ganon database"}}, "target": "meryl_count", "target_idx": 2}
{"id": "field_constraint_bai_3_6", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "subworkflow_pkg_deepvariant_2", "category": "subworkflow_packaging", "state": {"subworkflow": "DEEPVARIANT", "modules": ["deepvariant/makeexamples", "deepvariant/callvariants", "deepvariant/postprocessvariants"], "description": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data"}, "question": {"type": "choice", "instructions": "How should DEEPVARIANT (deepvariant/makeexamples, deepvariant/callvariants, deepvariant/postprocessvariants) be structured in DSL2?", "criteria": {"Use nf-core subworkflow deepvariant": null, "Keep the modules in the main workflow": null, "Local subworkflow DEEPVARIANT": null, "Leave them out": null}}, "target": "Use nf-core subworkflow deepvariant", "target_idx": 0}
{"id": "core_tool_picard_markduplicates_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Identify and flag PCR and optical duplicate reads in coordinate-sorted BAM files based on 5-prime mapping coordinates.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"gatk_markduplicates": "GATK duplicate marking", "picard_markduplicates": "Identifies duplicate reads in BAM files", "fastp": "FASTQ trimmer", "sambamba": "Fast BAM tools", "samtools": "SAM/BAM utilities"}}, "target": "picard_markduplicates", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_5_2", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/atacseq, determine the input samplesheet column structure for: FAIRE-seq / DNAse-seq open chromatin profiling.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "core_tool_minimap2_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Long-read mapping of Oxford Nanopore and PacBio HiFi sequencing reads against human and microbial reference assemblies.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"star": "RNA aligner", "subread": "Alignment tool", "bowtie2": "Short read aligner", "bwa_mem": "DNA aligner", "minimap2": "Versatile pairwise aligner for long reads, spliced transcripts, and assemblies"}}, "target": "minimap2", "target_idx": 4}
{"id": "field_constraint_bam_1_13", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "resource_bcftools_norm_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_NORM", "tool": "bcftools/norm", "description": "Normalize VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_NORM (Normalize VCF file) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_autocycler_compress_2", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMPRESS", "tool": "autocycler/compress", "description": "Package candidate assemblies for clustering by Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMPRESS (Package candidate assemblies for clustering by Autocycler.) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_regtools_junctionsextract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format. (tools: regtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arcashla/extract": null, "kled": null, "disambiguate": null, "regtools/junctionsextract": null, "jasminesv": null}}, "target": "regtools/junctionsextract", "target_idx": 3}
{"id": "samplesheet_arch_germline_lane_split_5_5", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Multi-lane Illumina sequencing run of clinical samples.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_smrnaseq_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A small-RNA sequencing analysis pipeline. Topics: small-rna, smrna-seq. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"smrnaseq": null, "scrnaseq": null, "pathogensurveillance": null, "readsimulator": null, "dualrnaseq": null}}, "target": "smrnaseq", "target_idx": 0}
{"id": "mod_agat_spextractsequences_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This script extracts sequences in fasta format according to features described\nin a gff file. (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "samtools_bgzip": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Converts an arbitrary compressed or uncompressed file to BGZIP", "haplogrep3_classify": "classification into haplogroups", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "agat_spextractsequences", "target_idx": 0}
{"id": "mod_kalign_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using kalign (tools: kalign)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "varscan_processsomatic": "VarScan2 is a tool for variant detection in massively parallel sequencing data. It can detect SNPs, indels, an", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "kalign_align": "Aligns sequences using kalign", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "kalign_align", "target_idx": 3}
{"id": "mod_fastk_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to merge FastK histograms (tools: fastk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/merge": "Merge VCF files", "biobambam/bammerge": "Merge a list of sorted bam files", "fastk/merge": "A tool to merge FastK histograms", "rpbp/extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "nextclade/run": "SARS-CoV-2 genome clade assignment, mutation calling, and sequence quality checks (C++ implementation)"}}, "target": "fastk/merge", "target_idx": 2}
{"id": "samplesheet_arch_scrna_multiome_4_2", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired FASTQs for both GEX and ATAC modalities per nucleus?", "criteria": {"sample,matrix": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "mod_svtk_baftest_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs tests on BAF files (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtk/standardize": "Convert SV calls to a standardized format.", "svtk/baftest": "Performs tests on BAF files", "raven": "De novo genome assembler for long uncorrected reads.", "svtk/rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format.", "gstama/merge": "Merge multiple transcriptomes while maintaining source information."}}, "target": "svtk/baftest", "target_idx": 1}
{"id": "noul_named_process_output_emits_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_10", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_demultiplex_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/demultiplex", "description": "Demultiplexing pipeline for sequencing data", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/demultiplex?", "criteria": {"sample,bundle,image": null, "sample,alleles,mhc_class,filename": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "id,samplesheet,lane,flowcell,per_flowcell_manifest", "target_idx": 2}
{"id": "mod_knotannotsv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simple tool to create a customizable html file (to be displayed on a web browser) from an AnnotSV output (tools: knotannotsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"knotannotsv": "Simple tool to create a customizable html file (to be displayed on a web browser) from an AnnotSV output", "expansionhunterdenovo_profile": "Compute genome-wide STR profile", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "knotannotsv", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_42", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_1_26", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "core_tool_star_described_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Splice-aware alignment of paired-end RNA-seq reads against human genome GRCh38 generating coordinate-sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"star": "Spliced read aligner for RNA-seq", "minimap2": "Versatile pairwise aligner", "salmon": "Transcript quantification from RNA-seq", "bwa_mem": "Burrows-Wheeler aligner for DNA", "bowtie2": "Fast aligner for short reads"}}, "target": "star", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay_type": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "data_format": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_svtyper_svtypersso_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SVTyper-sso computes structural variant (SV) genotypes based on breakpoint depth on a SINGLE sample (tools: svtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv_annotsv": "Annotation and Ranking of Structural Variation", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "macrel_contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid", "autocycler_compress": "Package candidate assemblies for clustering by Autocycler.", "svtyper_svtypersso": "SVTyper-sso computes structural variant (SV) genotypes based on breakpoint depth on a SINGLE sample"}}, "target": "svtyper_svtypersso", "target_idx": 4}
{"id": "mod_longphase_phase_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modifications for Nanopore and PacBio platforms. (tools: longphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ucsc/bedgraphtobigwig": "Convert a bedGraph file to bigWig format.", "vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "longphase/phase": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi", "autocycler/cluster": "Cluster replicons in compressed assemblies with Autocycler.", "sylph/profile": "Sylph profile command for taxonoming profiling"}}, "target": "longphase/phase", "target_idx": 2}
{"id": "mod_picard_collectvariantcallingmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects per-sample and aggregate (spanning all samples) metrics from the provided VCF file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"misopy/index": "Build an indexed representation of a GFF for efficient retrieval of genes", "bam_dedup_stats_samtools_umicollapse": "umicollapse, index BAM file and run samtools stats, flagstat and idxstats", "atlas/call": "generate VCF file from a BAM file using various calling methods", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "picard/collectvariantcallingmetrics": "Collects per-sample and aggregate (spanning all samples) metrics from the provided VCF file"}}, "target": "picard/collectvariantcallingmetrics", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_1_13", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "schema_std_callingcards_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/callingcards. Description: A pipeline for processing calling cards data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/callingcards.", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample,fastq_1,fastq_2,barcode_details": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "sample,fastq_1,fastq_2,barcode_details", "target_idx": 2}
{"id": "mod_mmseqs_cluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences using MMSeqs2 cluster. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/createtsv": "Create a tsv file from a query and a target database as well as the result database", "pasty": "Serogroup Pseudomonas aeruginosa assemblies", "mmseqs/easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "mmseqs/cluster": "Cluster sequences using MMSeqs2 cluster.", "vcf2zarr/explode": "Convert VCF(s) to intermediate columnar format"}}, "target": "mmseqs/cluster", "target_idx": 3}
{"id": "field_constraint_bai_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "bai", "validation_type": "companion_index"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'bai'.", "criteria": {"pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "mod_miniasm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A very fast OLC-based de novo assembler for noisy long reads (tools: miniasm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq_findtransport": "Predict transporters from genomic data using gapseq", "miniasm": "A very fast OLC-based de novo assembler for noisy long reads", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "fcsgx_fetchdb": "Fetches the NCBI FCS-GX database using a provided manifest URL", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "miniasm", "target_idx": 1}
{"id": "resource_bcftools_plotvcfstats_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLOTVCFSTATS", "tool": "bcftools/plotvcfstats", "description": "Plots the output of bcftools stats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLOTVCFSTATS (Plots the output of bcftools stats) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_svtk_vcf2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts VCFs containing structural variants to BED format (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtk_vcf2bed": "Converts VCFs containing structural variants to BED format", "pygenprop_info": "Display a summary of the contents of a Micromeda file, including the number of samples,\ngenome property assign", "expansionhunter": "Estimate repeat sizes using NGS data", "bcftools_annotate": "Add or remove annotations.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "svtk_vcf2bed", "target_idx": 0}
{"id": "mod_vcflib_vcffixup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a VCF stream where AC and NS have been generated for each record using sample genotypes. (tools: vcflib)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcflib/vcffixup": null, "bcftools/annotate": null, "td2/predict": null, "methylsieve": null, "aardvark/merge": null}}, "target": "vcflib/vcffixup", "target_idx": 0}
{"id": "resource_agrvate_4", "category": "resource_profiling", "state": {"process": "AGRVATE", "tool": "agrvate", "description": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGRVATE (Rapid identification of Staphylococcus aureus agr locus type and agr operon vari) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_diseasemodulediscovery_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/diseasemodulediscovery. Description: A pipeline for network-based disease module identification..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/diseasemodulediscovery.", "criteria": {"sample,type,level,msfile": null, "patient,vcf,tbi,dataset,tumour_sample": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "seeds,network,perturbed_networks": null}}, "target": "seeds,network,perturbed_networks", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_35", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_cnvnator_convert2vcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: convert2vcf.pl is command line tool to convert CNVnator calls to vcf format. (tools: cnvnator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canvas_germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "cnvnator_convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "cnvkit_target": "Transform bait intervals into targets more suitable for CNVkit.", "longphase_haplotag": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi", "bases2fastq": "Demultiplex Element Biosciences bases files"}}, "target": "cnvnator_convert2vcf", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_5_5", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "template": "nf-core/viralrecon"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral amplicon sequencing with primers.", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_eklipse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: tool for detection and quantification of large mtDNA rearrangements. (tools: eklipse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eklipse": null, "getorganelle/fromreads": null, "ataqv/ataqv": null, "finaletoolkit/fraglengthbins": null, "haplocheck": null}}, "target": "eklipse", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Genome analysis from reference-compressed CRAM files. Input files: Coordinate-sorted CRAM alignments with companion CRAI indexes.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Genome analysis from reference-compressed CRAM files with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,vcf": null, "sample,cram,crai": null, "sample,bam,bai": null, "sample,cram": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Metagenomic MAG assembly with comparative groups. Input files: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group.", "question": {"type": "choice", "instructions": "Which columns are standard for Metagenomic MAG assembly with comparative groups input samplesheet?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "mod_controlfreec_freec2circos_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Format Freec output to circos input format (tools: controlfreec)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq_findtransport": null, "msisensor_msi": null, "controlfreec_freec2circos": null, "controlfreec_freec": null, "cnvnator_cnvnator": null}}, "target": "controlfreec_freec2circos", "target_idx": 2}
{"id": "resource_bedtools_split_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SPLIT", "tool": "bedtools/split", "description": "Split BED files into several smaller BED files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SPLIT (Split BED files into several smaller BED files) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_ltrfinder_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Finds full-length LTR retrotranspsons in genome sequences using the\nparallel version of LTR_Finder (tools: LTR_FINDER_parallel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ltrfinder": "Finds full-length LTR retrotranspsons in genome sequences using the\nparallel version of LTR_Finder", "fasta_hmmsearch_rank_fastas": "Run hmmsearch and output separate fasta files for top scoring hits to each profile", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "gffcompare": "Compare, merge, annotate and estimate accuracy of generated gtf files", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "ltrfinder", "target_idx": 0}
{"id": "mod_bedtools_multiinter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_flank": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file.", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA", "bedtools_genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a", "bedtools_multiinter": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files.", "dshbio_splitbed": "Split features in gzipped BED format"}}, "target": "bedtools_multiinter", "target_idx": 3}
{"id": "mod_sniffles_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: structural-variant calling with sniffles (tools: sniffles)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sawfish/jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "vclust/cluster": "Vclust cluster performs threshold-based clustering by assigning a genome sequence to a cluster if its similari", "rclone/check": "Check that files in source and destination paths match", "cutesv": "structural-variant calling with cutesv", "sniffles": "structural-variant calling with sniffles"}}, "target": "sniffles", "target_idx": 4}
{"id": "core_tool_samtools_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Coordinate-sorting, indexing, and statistics generation for genome-aligned BAM binary alignment files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"sambamba": null, "picard": null, "samtools": null, "bedtools": null, "bamtools": null}}, "target": "samtools", "target_idx": 2}
{"id": "local_subworkflow_irma_1_0", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should this step (irma) be packaged: Iterative assembly step for influenza and coronavirus?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow irma": null, "Local subworkflow IRMA": null}}, "target": "Local subworkflow IRMA", "target_idx": 3}
{"id": "samplesheet_arch_ont_demux_barcodes_1_3", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,barcode": null, "sample,fastq_1,fastq_2": null, "sample,barcode,flowcell,kit,fastq": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "mod_homer_findpeaks_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find peaks with HOMER suite (tools: homer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja_update": "downloads new versions of the curated SARS-CoV-2 lineage file and barcodes", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "homer_findpeaks": "Find peaks with HOMER suite", "purgedups_calcuts": "Calculate coverage cutoffs to determine when to purge duplicated sequence."}}, "target": "homer_findpeaks", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_27", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_seqkit_sana_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sanitize broken single line FASTQ files (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba_getref": "Download and prepare database for Ariba analysis", "ariba_run": "Query input FASTQs against Ariba formatted databases", "cobiontid_kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "seqkit_sana": "Sanitize broken single line FASTQ files"}}, "target": "seqkit_sana", "target_idx": 4}
{"id": "samplesheet_arch_ont_metagenome_single_7_2", "category": "samplesheet_schema", "state": {"technology": "Metagenomics", "workflow_entry": "NANOPLOT", "library_inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/oncoanalyser --input samplesheet.csv (Assay: Longitudinal cancer monitoring across multiple timepoints)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Longitudinal cancer monitoring across multiple timepoints with entry step FASTQC.", "criteria": {"patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "field_constraint_sex_0_13", "category": "samplesheet_schema", "state": {"field_name": "sex", "datatype": "pedigree_sex_enum", "description": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sex'?", "criteria": {"type: boolean": null, "format: file-path": null, "pattern: ^\\S+\\.gz$": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "mod_svtk_countsvtypes_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Count the instances of each SVTYPE observed in each sample in a VCF. (tools: svtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamdbg/asm": "Metagenome assembler for long-read sequences (HiFi and ONT).", "svtk/countsvtypes": "Count the instances of each SVTYPE observed in each sample in a VCF.", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "opt/stat": "stat summarizes opt binding predictions", "svtk/baftest": "Performs tests on BAF files"}}, "target": "svtk/countsvtypes", "target_idx": 1}
{"id": "intent_debug_error_7", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "ask_question": null, "debug_error": null}}, "target": "debug_error", "target_idx": 3}
{"id": "noul_workflow_completion_lifecycle_hook_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_sample_0_2", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"enum: [0, 1]": null, "format: file-path": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_fargene_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full-length antiobiotic resistance genes as output. (tools: fargene)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct_concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "motus_downloaddb": "Download the mOTUs database", "fargene": "tool that takes either fragmented metagenomic data or longer sequences as input and predicts and delivers full", "concoct_cutupfasta": "Cut up fasta file in non-overlapping or overlapping parts of equal length.", "deacon_indexunion": "Combine multiple deacon indexes (A ∪ B ...)"}}, "target": "fargene", "target_idx": 2}
{"id": "resource_amulety_esm2_2", "category": "resource_profiling", "state": {"process": "AMULETY_ESM2", "tool": "amulety/esm2", "description": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ESM2 (A module to create esm2 embeddings of antibody (BCR) amino acid sequences using ) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_modular_subworkflow_composition_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_9", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_krona_ktimporttaxonomy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot. (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deeptools/plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "deeptools/multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "pangolin/run": "Phylogenetic Assignment of Named Global Outbreak LINeages", "krona/ktimporttaxonomy": "KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot.", "viber": "Multisample subclonal deconvolution of cancer genome sequencing data."}}, "target": "krona/ktimporttaxonomy", "target_idx": 3}
{"id": "mod_mitohifi_mitohifi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A python workflow that assembles mitogenomes from Pacbio HiFi reads (tools: mitohifi.py)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mitohifi/mitohifi": null, "hifiasm": null, "hisat2/align": null, "bam2fastx/bam2fastq": null, "riker/multi": null}}, "target": "mitohifi/mitohifi", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral genome sequencing on Oxford Nanopore MinION / GridION)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_bam_dedup_umi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BAM deduplication with UMI processing for both genome and transcriptome alignments (tools: bam_dedup_umi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_dedup_umi": null, "umicollapse": null, "sourmash_compare": null, "fgumi_dedup": null, "flye": null}}, "target": "bam_dedup_umi", "target_idx": 0}
{"id": "mod_trgt_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge TRGT VCFs from multiple samples (tools: trgt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifiadapterfilt_hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out", "trgt_merge": "Merge TRGT VCFs from multiple samples", "finaletoolkit_adjustwps": "Adjusts raw Windowed Protection Score (WPS) by applying a median filter\nand Savitsky-Golay filter.", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "deepbgc_download": "Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning."}}, "target": "trgt_merge", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_6_5", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for 16S rRNA / ITS microbiome amplicon profiling input samplesheet?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,primer_fwd,primer_rev": null, "sample,otu_table": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/spatialaxe) for 10x Xenium in situ subcellular spatial RNA transcriptomics. Input files: Xenium output bundle with transcripts CSV, cell polygons, and morphology images.", "question": {"type": "choice", "instructions": "Which columns are standard for 10x Xenium in situ subcellular spatial RNA transcriptomics input samplesheet?", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Somatic cancer variant calling with tumor-normal pairs", "data_format": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs for patient tumor and germline normal tissue?", "criteria": {"patient,sample,status,bam,bai": null, "sample,fastq_1": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_pangolin_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Phylogenetic Assignment of Named Global Outbreak LINeages (tools: pangolin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pangolin/run": null, "famsa/align": null, "taxonkit/list": null, "ribotish/quality": null, "pangolin/updatedata": null}}, "target": "pangolin/run", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_17", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/eager --input samplesheet.csv (Assay: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/eager, determine the input samplesheet column structure for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment.", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_15", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_45", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_vembrane_table_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates tabular (TSV) files from VCF/BCF data with flexible Python expressions (tools: vembrane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sratools/fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA).", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "gatk4/determinegermlinecontigploidy": "Determines the baseline contig ploidy for germline samples given counts data", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "vembrane/table": "Creates tabular (TSV) files from VCF/BCF data with flexible Python expressions"}}, "target": "vembrane/table", "target_idx": 4}
{"id": "schema_std_viralrecon_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "description": "Assembly and intrahost/low-frequency variant calling for viral samples", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/viralrecon?", "criteria": {"SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,fastq_1,fastq_2,barcode": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "sample,fastq_1,fastq_2,replicate,antibody": null}}, "target": "sample,fastq_1,fastq_2,barcode", "target_idx": 1}
{"id": "mod_vclust_prefilter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by filtering out dissimilar sequences before the alignment step. (tools: vclust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vclust/prefilter": "The prefilter command creates a pre-alignment filter that reduces the number of genome pairs to be aligned by ", "cdhit/cdhit": "Cluster protein sequences using sequence similarity", "clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "bcftools/stats": "Generates stats from VCF files", "picard/collectrnaseqmetrics": "Collect metrics from a RNAseq BAM file"}}, "target": "vclust/prefilter", "target_idx": 0}
{"id": "schema_std_hadge_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/hadge. Description: Comprehensive pipeline for donor demultiplexing in single cell.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/hadge.", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null}}, "target": "sample,bam,vcf,rna_matrix,hto_matrix", "target_idx": 2}
{"id": "resource_bamtofastq10x_0", "category": "resource_profiling", "state": {"process": "BAMTOFASTQ10X", "tool": "bamtofastq10x", "description": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Long Ranger back to FASTQ files that can be used as inputs to re-run analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOFASTQ10X (Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "local_subworkflow_variantsofint_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for VARIANTSOFINT (custom/variantsofint).", "criteria": {"Local subworkflow VARIANTSOFINT": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow variantsofint": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 0}
{"id": "mod_mmseqs_easycluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences using MMSeqs2 easy cluster. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs_createtaxdb": null, "gecco_run": null, "mmseqs_easycluster": null, "mirtrace_qc": null, "mmseqs_createindex": null}}, "target": "mmseqs_easycluster", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_0_21", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "pipe_all101_pixelator_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for molecular-pixelation. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel"}}, "target": "pixelator", "target_idx": 9}
{"id": "intent_debug_error_13", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "ask_question": null, "debug_error": null, "build_pipeline": null}}, "target": "debug_error", "target_idx": 2}
{"id": "mod_picard_splitsambynumberofreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits a SAM/BAM/CRAM file to multiple files. This tool splits the input query-grouped SAM/BAM/CRAM file into multiple files while maintaining the sort order. This can be used to split a large unmapped input in order to parallelize alignment. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diamond/linclust": null, "bcftools/pluginsplit": null, "bedtools/split": null, "custom/tabulartogseagct": null, "picard/splitsambynumberofreads": null}}, "target": "picard/splitsambynumberofreads", "target_idx": 4}
{"id": "resource_angsd_contamination_2", "category": "resource_profiling", "state": {"process": "ANGSD_CONTAMINATION", "tool": "angsd/contamination", "description": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_CONTAMINATION (A tool to estimate nuclear contamination in males based on heterozygosity in the) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bcftools_mpileup_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MPILEUP", "tool": "bcftools/mpileup", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MPILEUP (Compresses VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_7_1", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "template": "nf-core/eager"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_bio2zarr_vcf2zarrexplode_2", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARREXPLODE", "tool": "bio2zarr/vcf2zarrexplode", "description": "Convert VCF(s) to intermediate columnar format (ICF)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARREXPLODE (Convert VCF(s) to intermediate columnar format (ICF)) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_mcstaging_imc2mc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes optional hot pixel removal. (tools: mcstaging)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_vclust_prefilter_align_cluster": null, "mcstaging_imc2mc": null, "basicpy": null, "bioformats2raw": null, "samtools_markdup": null}}, "target": "mcstaging_imc2mc", "target_idx": 1}
{"id": "resource_biscuit_bsconv_2", "category": "resource_profiling", "state": {"process": "BISCUIT_BSCONV", "tool": "biscuit/bsconv", "description": "Summarize and/or filter reads based on bisulfite conversion rate"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BSCONV (Summarize and/or filter reads based on bisulfite conversion rate) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral amplicon sequencing with primers. Input files: Paired-end tiled viral amplicon FASTQs per clinical swab sample.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral amplicon sequencing with primers.", "criteria": {"sample,vcf": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_6_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns are standard for Tumor-only somatic variant calling without matched normal input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_1_4", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_expected_cells_1_0", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 3}
{"id": "mod_icountmini_segment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Formats a GTF file for use with iCount sigxls (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"varlociraptor/estimatealignmentproperties": "In order to judge about candidate indel and structural variants, Varlociraptor needs to know about certain pro", "icountmini/segment": "Formats a GTF file for use with iCount sigxls", "icountmini/metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks.", "fgumi/duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data", "icountmini/summary": "Report proportion of cross-link events/sites on each region type."}}, "target": "icountmini/segment", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_7", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_krakenuniq_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download KrakenUniq databases and related fles (tools: krakenuniq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "picard_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "foldcomp_compress": "Efficient compression tool for protein structures", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "krakenuniq_download": "Download KrakenUniq databases and related fles"}}, "target": "krakenuniq_download", "target_idx": 4}
{"id": "mod_abra2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembly Based ReAligner for next-generation sequencing data (tools: abra2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ashlar": null, "custom_dumpsoftwareversions": null, "mcroni": null, "bwa_mem": null, "abra2": null}}, "target": "abra2", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_1_0", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_samtools_bam2fq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/bam2fq": null, "picard/setnmmdanduqtags": null, "eautils/fastqstats": null, "rustqc": null, "samtools/collatefastq": null}}, "target": "samtools/bam2fq", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents))", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_amulety_embed_2", "category": "resource_profiling", "state": {"process": "AMULETY_EMBED", "tool": "amulety/embed", "description": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_EMBED (A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) ) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_autocycler_cluster_0", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_CLUSTER", "tool": "autocycler/cluster", "description": "Cluster replicons in compressed assemblies with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_CLUSTER (Cluster replicons in compressed assemblies with Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_scramble_clusteranalysis_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The Cluster Analysis tool of Scramble analyses and interprets the soft-clipped clusters found by `cluster_identifier` (tools: scramble)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scramble_clusteridentifier": null, "ribotricer_detectorfs": null, "scramble_clusteranalysis": null, "bcftools_pluginvcf2table": null, "segemehl_align": null}}, "target": "scramble_clusteranalysis", "target_idx": 2}
{"id": "mod_cellrangerarc_mkref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkref command. (tools: cellrangerarc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangerarc/mkref": null, "bowtie/build": null, "finaletoolkit/endmotifs": null, "angsd/gl": null, "bbmap/align": null}}, "target": "cellrangerarc/mkref", "target_idx": 0}
{"id": "mod_bcftools_plugintag2tag_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD. (tools: view)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last/split": "Find split or spliced alignments in a MAF file", "pypgx/createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bcftools/annotate": "Add or remove annotations.", "bcftools/plugintag2tag": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD."}}, "target": "bcftools/plugintag2tag", "target_idx": 4}
{"id": "mod_seacr_callpeak_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call peaks using SEACR on sequenced reads in bedgraph format (tools: seacr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender_merge": null, "seacr_callpeak": null, "homer_makeucscfile": null, "cutesv": null, "idr": null}}, "target": "seacr_callpeak", "target_idx": 1}
{"id": "resource_bowtie_build_1", "category": "resource_profiling", "state": {"process": "BOWTIE_BUILD", "tool": "bowtie/build", "description": "Create bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_BUILD (Create bowtie index for reference genome) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_42", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Xenium in situ subcellular spatial RNA transcriptomics)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 0}
{"id": "noul_mix_operator_async_emission_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "noul_named_process_output_emits_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_blat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Queries a sequence subject (tools: blat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_splitheader": "Extract header lines from a SAM/BAM/CRAM file into separate files depending on type", "blat": "Queries a sequence subject", "shasta": "The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using DNA reads g", "bclconvert": "Demultiplex Illumina BCL files", "nucmer": "NUCmer is a pipeline for the alignment of multiple closely related nucleotide sequences."}}, "target": "blat", "target_idx": 1}
{"id": "resource_bedtools_flank_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_FLANK", "tool": "bedtools/flank", "description": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_FLANK (Creates two new flanking intervals for each interval in a BED/GFF/VCF file.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Tumor-only somatic variant calling without matched normal", "data_format": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads from tumor biopsy without matched normal?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_2_5", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,spikein,fastq": null, "sample,bam": null, "sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "field_constraint_fastq_2_2_4", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "type: required string": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 0}
{"id": "schema_std_variantprioritization_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/variantprioritization. Description: Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number abberations for precision cancer medicine using Personal Cancer Genome Reporter (PCGR). The pipeline offers germline SNVs/INDELS intepretation and annotation using Cancer Predisposition Sequencing Reporter (CPSR)..", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/variantprioritization.", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "patient,sample,vcf,status,cna": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null}}, "target": "patient,sample,vcf,status,cna", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_25", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_iphop_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download, extract, and check md5 of iPHoP databases (tools: iphop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamaps/mapdirectly": "Maps long reads to a metamaps database", "metaphlan/mergemetaphlantables": "Merges output abundance tables from MetaPhlAn4", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "iphop/download": "Download, extract, and check md5 of iPHoP databases"}}, "target": "iphop/download", "target_idx": 4}
{"id": "mod_bwameth_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs indexing of c2t converted reference genome (tools: bwameth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mapad_map": "Map short-reads to an indexed reference genome", "stecfinder": "Serotype STEC samples from paired-end reads or assemblies", "parabricks_fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "bwameth_index": "Performs indexing of c2t converted reference genome", "bismark_align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "bwameth_index", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_1_14", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_bismark_methylationextractor_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts methylation information for individual cytosines from alignments. (tools: bismark)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_coverage2cytosine": null, "bismark_methylationextractor": null, "stacks_refmap": null, "sylph_query": null, "bismark_deduplicate": null}}, "target": "bismark_methylationextractor", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_0_1", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_1_5", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "template": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "intent_ask_question_17", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "debug_error": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 0}
{"id": "mod_bam_variant_demix_boot_freyja_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to the Hu-1 reference) (tools: bam_variant_demix_boot_freyja)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "csvtk_split": "Splits CSV/TSV into multiple files according to column values", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "hmmer_hmmpress": "compress and index profile database for hmmscan"}}, "target": "bam_variant_demix_boot_freyja", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/smrnaseq", "assay_type": "Small RNA / miRNA sequencing", "data_format": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns are standard for Small RNA / miRNA sequencing input samplesheet?", "criteria": {"sample,fastq_1,mirna_id": null, "sample,vcf": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_muse_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pre-filtering and calculating position-specific summary statistics using the Markov substitution model (tools: MuSE)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"telomerehunter": "In silico estimation of telomere content and composition from cancer genomes", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "muse_call": "pre-filtering and calculating position-specific summary statistics using the Markov substitution model", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bcftools_consensus": "Compresses VCF files"}}, "target": "muse_call", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_0_23", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "schema_std_createpanelrefs_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/createpanelrefs", "description": "Generate Panel of Normals, models or other similar references from lots of samples", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/createpanelrefs?", "criteria": {"id,path": null, "sample,fastq_1,fastq_2,strandedness": null, "gene_name,alignment,tree,suite,tool": null, "sample,bam,bai,cram,crai": null}}, "target": "sample,bam,bai,cram,crai", "target_idx": 3}
{"id": "mod_starfusion_build_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download STAR-fusion genome resource required to run STAR-Fusion caller (tools: star-fusion)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"starfusion/build": "Download STAR-fusion genome resource required to run STAR-Fusion caller", "annotsv/installannotations": "Install the AnnotSV annotations", "gget/gget": "gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic da", "rtgtools/rocplot": "Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI is", "blast/updateblastdb": "Downloads a BLAST database from NCBI"}}, "target": "starfusion/build", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_43", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_picard_setnmmdanduqtags_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool takes in a coordinate-sorted SAM or BAM and calculatesthe NM, MD, and UQ tags by comparing with the reference. (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pcangsd/inbreeding": "Estimate per-sample inbreeding coefficients from genotype likelihoods", "tcoffee/consensus": "Computes a consensus alignment using T_COFFEE", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "picard/setnmmdanduqtags": "This tool takes in a coordinate-sorted SAM or BAM and calculatesthe NM, MD, and UQ tags by comparing with the ", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "picard/setnmmdanduqtags", "target_idx": 3}
{"id": "resource_ataqv_mkarv_1", "category": "resource_profiling", "state": {"process": "ATAQV_MKARV", "tool": "ataqv/mkarv", "description": "mkarv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_MKARV (mkarv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_centrifuge_kreport_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates Kraken-style reports from centrifuge out files (tools: centrifuge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "conifer": "Calculate confidence scores from Kraken2 output", "fasta_explore_search_plot_tidk": "Uses Telomere Identification toolKit (TIDK) to identify the frequency of telomeric repeats\nalong a sliding win", "haplogrep2/classify": "classification into haplogroups", "phyloflash": "phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illum"}}, "target": "centrifuge/kreport", "target_idx": 0}
{"id": "field_constraint_expected_cells_3_11", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null, "format: file-path": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "mod_methbat_profile_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs methbat profile command to create methylation profiles for regions of interest from CpG metrics. (tools: methbat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/deduplicate": null, "custom/pcaclustering": null, "bismark/coverage2cytosine": null, "methbat/profile": null, "cooler/cload": null}}, "target": "methbat/profile", "target_idx": 3}
{"id": "mod_untarfiles_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract files. (tools: untar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tar": "Compress directories into tarballs with various compression options", "untarfiles": "Extract files.", "fastq_align_bwa": "Align reads to a reference genome using bwa then sort with samtools", "jellyfish/dump": "Dumps the results from a jellyfish binary file into a human readable format", "untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives"}}, "target": "untarfiles", "target_idx": 1}
{"id": "pipe_all101_rnafusion_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for fusion. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]"}}, "target": "rnafusion", "target_idx": 7}
{"id": "mod_sentieon_readwriter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality Score Recalibration to a file. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "sentieon_readwriter": "Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality S", "plink2_indeppairwise": "Produce pruned set of variants in approximatelinkage equilibrium", "trgt_merge": "Merge TRGT VCFs from multiple samples"}}, "target": "sentieon_readwriter", "target_idx": 2}
{"id": "samplesheet_arch_ampliseq_its_fungal_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: Fungal ITS1/ITS2 marker gene amplicon surveillance)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Fungal ITS1/ITS2 marker gene amplicon surveillance with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,primer_its1,primer_its2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "intent_debug_error_17", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "debug_error": null, "build_pipeline": null, "ask_question": null}}, "target": "debug_error", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_1_3", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_confusing_combine_with_mix_semantics_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_2_29", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_3_1", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "template": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Small RNA / miRNA sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_0_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "mod_smoothxg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Linearize and simplify variation graph in GFA format using blocked partial order alignment (tools: smoothxg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/seqreformat": "Reformats files with t-coffee", "custom/addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field", "smoothxg": "Linearize and simplify variation graph in GFA format using blocked partial order alignment", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format", "bandage/image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}}, "target": "smoothxg", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/cageseq --input samplesheet.csv (Assay: CAGE-seq 5-prime capped transcript end sequencing)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "local_subworkflow_irma_2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for IRMA (irma).", "criteria": {"Use nf-core subworkflow irma": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow IRMA": null}}, "target": "Local subworkflow IRMA", "target_idx": 3}
{"id": "pipe_all101_demultiplex_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Demultiplexing pipeline for sequencing data. Topics: bases2fastq, bcl2fastq, demultiplexing, elementbiosciences, illumina. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"multiplesequencealign": null, "dualrnaseq": null, "demultiplex": null, "proteinfold": null, "riboseq": null}}, "target": "demultiplex", "target_idx": 2}
{"id": "mod_fastx_collapser_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts) (tools: fastx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gunc_downloaddb": "Download database for GUNC detection of Chimerism and Contamination in Prokaryotic Genomes", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "fastx_collapser": "Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts)", "gatk4_intervallisttobed": "Converts an Picard IntervalList file to a BED file.", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "fastx_collapser", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/nanoseq) for Single-end Oxford Nanopore direct RNA. Input files: Single fastq per sample.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fast5": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_merqury_hapmers_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A script to generate hap-mer dbs for trios (tools: merqury)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jvarkit/vcfpolyx": "annotate VCF files for poly repeats", "kraken2/kraken2": "Classifies metagenomic sequence data", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "merqury/hapmers": "A script to generate hap-mer dbs for trios"}}, "target": "merqury/hapmers", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_1_4", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_named_output_channel_access_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_1_20", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_gem2_gemindexer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a GEM index from a FASTA file (tools: gem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem2/gemindexer": "Create a GEM index from a FASTA file", "cellsnp/modea": "Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A ", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "circexplorer2/parse": "CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate."}}, "target": "gem2/gemindexer", "target_idx": 0}
{"id": "field_constraint_strandedness_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'strandedness' (Library strandedness orientation in RNA-seq protocols) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'strandedness' validated?", "criteria": {"type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^[0-9]+$": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "mod_diamond_linclust_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast protein sequence clustering using a greedy incremental approach (tools: diamond)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangeratac/mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkfastq com", "custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "mobsuite/typer": "Bacterial plasmid typing and mobility prediction", "diamond/linclust": "Fast protein sequence clustering using a greedy incremental approach", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin"}}, "target": "diamond/linclust", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_8_2", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fasta": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_folddisco_query_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Search a prebuilt folddisco index for a discontinuous residue motif in a query protein structure (tools: folddisco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect/esummary": "Queries an NCBI database using Unique Identifier(s)", "htsnimtools/vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "folddisco/query": "Search a prebuilt folddisco index for a discontinuous residue motif in a query protein structure", "svdb/query": "Query a structural variant database, using a vcf file as query"}}, "target": "folddisco/query", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_2_10", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_ngscheckmate_patterngenerator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determining whether sequencing data comes from the same individual by using SNP matching. This module generates PT files from a bed file containing individual positions. (tools: ngscheckmate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"khmer/trimlowabund": null, "dastool/fastatocontig2bin": null, "ngscheckmate/patterngenerator": null, "fastq_ngscheckmate": null, "bam_ngscheckmate": null}}, "target": "ngscheckmate/patterngenerator", "target_idx": 2}
{"id": "intent_ask_question_24", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_snpeff_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genetic variant annotation and functional effect prediction toolbox (tools: snpeff)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "vt_normalize": "normalizes variants in a VCF file", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "staphopiasccmec": "Predicts Staphylococcus aureus SCCmec type based on primers.", "snpeff_download": "Genetic variant annotation and functional effect prediction toolbox"}}, "target": "snpeff_download", "target_idx": 4}
{"id": "mod_gatk4_fastqtosam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts FastQ file to SAM/BAM format (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": "split single end read groups by length and merge paired end reads", "gatk4spark/baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "trimmomatic": "Performs quality and adapter trimming on paired end and single end reads", "gatk4/fastqtosam": "Converts FastQ file to SAM/BAM format"}}, "target": "gatk4/fastqtosam", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_bam_0_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "MUTECT2", "library_inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,vcf": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_2_4", "category": "samplesheet_schema", "state": {"assay": "Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq", "first_step": "FASTQC", "inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"plate,sample,bam": null, "sample,well,fastq": null, "sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_methylseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for bisulfite-sequencing. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]"}}, "target": "methylseq", "target_idx": 3}
{"id": "mod_decoupler_decoupler_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: decoupler is a package containing different statistical methods\nto extract biological activities from omics data within a unified framework.\nIt allows to flexibly test any enrichment method with any prior knowledge\nresource and incorporates methods that take into account the sign and weight.\nIt can be used with any omic, as long as its features can be linked to a\nbiological process based on prior knowledge. For example, in transcriptomics\ngene sets regulated by a transcription factor, or in phospho-proteomics\nphosphosites that are targeted by a kinase. (tools: decoupler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"decoupler/decoupler": "decoupler is a package containing different statistical methods\nto extract biological activities from omics da", "propr/grea": "Perform Gene Ratio Enrichment Analysis", "gprofiler2/gost": "runs a functional enrichment analysis with gprofiler2", "glimpse/ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information.", "picard/sortsam": "Sorts BAM/SAM files based on a variety of picard specific criteria"}}, "target": "decoupler/decoupler", "target_idx": 0}
{"id": "mod_president_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairwise nucleotide identity with respect to a reference sequence (tools: president)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "president": "Calculate pairwise nucleotide identity with respect to a reference sequence", "verifybamid/verifybamid2": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "deacon/indexunion": "Combine multiple deacon indexes (A ∪ B ...)"}}, "target": "president", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_44", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "core_tool_featurecounts_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Assign and quantify mapped reads to genomic features such as exons, genes, and promoter annotations from sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"stringtie": null, "kallisto": null, "salmon": null, "htseq": null, "featurecounts": null}}, "target": "featurecounts", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_bgzip_index_dict_samtools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BGZIP_INDEX_DICT_SAMTOOLS", "modules": ["htslib/bgziptabix", "samtools/dict", "samtools/faidx"], "description": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA file."}, "question": {"type": "choice", "instructions": "How should FASTA_BGZIP_INDEX_DICT_SAMTOOLS (htslib/bgziptabix, samtools/dict, samtools/faidx) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_BGZIP_INDEX_DICT_SAMTOOLS": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fasta_bgzip_index_dict_samtools": null}}, "target": "Use nf-core subworkflow fasta_bgzip_index_dict_samtools", "target_idx": 3}
{"id": "samplesheet_arch_spatial_xenium_2_4", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,image": null, "sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,bam": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_4_4", "category": "samplesheet_schema", "state": {"technology": "Ancient DNA", "workflow_entry": "FASTQC", "library_inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status?", "criteria": {"sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_0_2", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_module_metadata_propagation_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_plink2_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters plink bfiles or pfiles with filters such as maf or var (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_extract": "Subset plink pfiles with a text file of variant identifiers", "verifybamid_verifybamid": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "plink2_pca": "Perform PCA analysis using PLINK", "plink2_filter": "Filters plink bfiles or pfiles with filters such as maf or var", "sequencetools_pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods"}}, "target": "plink2_filter", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_35", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_cnvnator_convert2vcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: convert2vcf.pl is command line tool to convert CNVnator calls to vcf format. (tools: cnvnator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"portello": "Transfer HiFi read mappings from their own assembly contigs to a standard reference", "vcf2zarr/explode": "Convert VCF(s) to intermediate columnar format", "cnvkit/target": "Transform bait intervals into targets more suitable for CNVkit.", "cnvnator/convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples)."}}, "target": "cnvnator/convert2vcf", "target_idx": 3}
{"id": "resource_bedtools_subtract_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SUBTRACT", "tool": "bedtools/subtract", "description": "Finds overlaps between two sets of regions (A and B), removes the overlaps from A and reports the remaining portion of A."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SUBTRACT (Finds overlaps between two sets of regions (A and B), removes the overlaps from ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cutandrun", "assay_type": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "data_format": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,spikein,fastq": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "field_constraint_phenotype_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"enum: [normal, tumor]": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_34", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_bracken_bracken_5", "category": "resource_profiling", "state": {"process": "BRACKEN_BRACKEN", "tool": "bracken/bracken", "description": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BRACKEN (Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_gatk4_variantrecalibrator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follow GATK best practices when using this module,\nthe gaussian mixture model requires a large number of samples to be used for the\ntool to produce optimal results. For example, 30 samples for exome data. For more details see\nhttps://gatk.broadinstitute.org/hc/en-us/articles/4402736812443-Which-training-sets-arguments-should-I-use-for-running-VQSR- (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo", "rtgtools/cnveval": "The cnveval tool of RTG tools. It is used to evaluate called CNV regions for agreement with a baseline CNV set", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "megan/daa2info": "Analyses a DAA file and exports information in text format", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data"}}, "target": "gatk4/variantrecalibrator", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_0_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ", "pipeline": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_45", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_1_2", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_mcstaging_macsima2mc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO. (tools: macsima2mc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging/macsima2mc": null, "bioformats2raw": null, "concoct/cutupfasta": null, "deepcell/mesmer": null, "picard/createsequencedictionary": null}}, "target": "mcstaging/macsima2mc", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_0_21", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "schema_std_mhcquant_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mhcquant", "assay": "mhcquant pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/mhcquant (Identify and quantify MHC eluted peptides from mass spectrom)?", "criteria": {"ID,R1,R2,LongFastQ,Fast5": null, "sample,fastq_1,fastq_2,bam,cram": null, "sample,tools,file,index": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "ID,Sample,Condition,ReplicateFileName,Fasta", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_trim_fastp_fastqc_3", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TRIM_FASTP_FASTQC", "modules": ["fastqc", "fastp"], "description": "Read QC, fastp trimming and read qc"}, "question": {"type": "choice", "instructions": "How should FASTQ_TRIM_FASTP_FASTQC (fastqc, fastp) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_trim_fastp_fastqc": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_TRIM_FASTP_FASTQC": null}}, "target": "Use nf-core subworkflow fastq_trim_fastp_fastqc", "target_idx": 1}
{"id": "mod_gatk4_gatherbqsrreports_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gathers scattered BQSR recalibration reports into a single file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "gatk4_gatherbqsrreports": "Gathers scattered BQSR recalibration reports into a single file", "star_indexversion": "Get the minimal allowed index version from STAR", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "mageck_count": "mageck count for functional genomics, reads are usually mapped to a specific sgRNA"}}, "target": "gatk4_gatherbqsrreports", "target_idx": 1}
{"id": "resource_bcftools_pluginfixploidy_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFIXPLOIDY", "tool": "bcftools/pluginfixploidy", "description": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFIXPLOIDY (The fixploidy plugin fixes ploidy in genotype fields according to specified ploi) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_demuxem_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplexing cell nucleus hashing data, using the estimated antibody background probability. (tools: demuxem)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"force_cube": "Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spat", "trinity": "Assembles a de novo transcriptome from RNAseq reads", "popscle_demuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability."}}, "target": "demuxem", "target_idx": 4}
{"id": "pipe_all101_airrflow_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework. Topics: airr, b-cell, immcantation, immunorepertoire, repseq. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "airrflow", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_0_3", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "template": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "mod_ribocode_gtfupdate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Update GTF annotation file for RiboCode compatibility (tools: ribocode)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blat": "Queries a sequence subject", "custom/orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom", "ribocode/gtfupdate": "Update GTF annotation file for RiboCode compatibility", "ribocode/prepare": "Prepare the annotation files for RiboCode ORF calling", "custom/orfmerge": "Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `cus"}}, "target": "ribocode/gtfupdate", "target_idx": 2}
{"id": "mod_vizgenpostprocessing_runsegmentationontile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool. (tools: vizgenpostprocessing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vizgenpostprocessing_compiletilesegmentation": "The module compiles segmentation tiles using Vizgen's post-processing tool.", "baysor_run": "Bayesian segmentation of spatial transcriptomics data.", "viennarna_rnalfold": "calculate locally stable secondary structures of RNAs", "toulligqc": "A post sequencing QC tool for Oxford Nanopore sequencers", "vizgenpostprocessing_runsegmentationontile": "The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool."}}, "target": "vizgenpostprocessing_runsegmentationontile", "target_idx": 4}
{"id": "noul_container_environment_specification_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bbmap_index_1", "category": "resource_profiling", "state": {"process": "BBMAP_INDEX", "tool": "bbmap/index", "description": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_INDEX (Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_fastq_2_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "mod_paftools_sam2paf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program to convert bam into paf. (tools: paftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paftools/sam2paf": "A program to convert bam into paf.", "mm2plus/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "wipertools/fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "pbtk/bam2fastq": "converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq"}}, "target": "paftools/sam2paf", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_6_4", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 2}
{"id": "resource_bracken_bracken_0", "category": "resource_profiling", "state": {"process": "BRACKEN_BRACKEN", "tool": "bracken/bracken", "description": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BRACKEN (Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_barrnap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: barrnap uses a hmmer profile to find rrnas in reads or contig fasta files (tools: barrnap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": null, "annosine": null, "survivor_bedpetovcf": null, "barrnap": null, "fastq_qc_trim_filter_setstrandedness": null}}, "target": "barrnap", "target_idx": 3}
{"id": "mod_integronfinder_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detect integrons in DNA sequences (tools: integronfinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "picard/createsequencedictionary": "Creates a sequence dictionary for a reference sequence.", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization.", "integronfinder": "Detect integrons in DNA sequences", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "integronfinder", "target_idx": 3}
{"id": "mod_openms_idmassaccuracy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates a distribution of the mass error from given mass spectra and IDs. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field", "openms_decoydatabase": "Create a decoy peptide database from a standard FASTA database.", "openms_idmassaccuracy": "Calculates a distribution of the mass error from given mass spectra and IDs.", "openms_peptideindexer": "Refreshes the protein references for all peptide hits.", "openms_idmerger": "Merges several idXML files into one idXML file."}}, "target": "openms_idmassaccuracy", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/riboseq) for Ribosome profiling (Ribo-seq) footprint sequencing. Input files: Single-end ribosome protected RNA fragments (RPFs) with strandedness.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,cdna_fasta": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_5_4", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/smrnaseq, determine the input samplesheet column structure for: Small RNA / miRNA sequencing.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_4_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: High molecular weight environmental metagenomic long reads per sampling site?", "criteria": {"sample,fastq_1,group": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_bedtools_makewindows_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Makes adjacent or sliding windows across a genome or BED file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/makewindows": "Makes adjacent or sliding windows across a genome or BED file.", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "bedops/convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "opt/stat": "stat summarizes opt binding predictions", "gatk4/postprocessgermlinecnvcalls": "Postprocesses the output of GermlineCNVCaller and generates VCFs and denoised copy ratios"}}, "target": "bedtools/makewindows", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "assay_type": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "data_format": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hybrid bacterial assembly combining short Illumina and long Nanopore reads with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "resource_agat_spfilterfeaturefromkilllist_2", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERFEATUREFROMKILLLIST", "tool": "agat/spfilterfeaturefromkilllist", "description": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERFEATUREFROMKILLLIST (The script aims to remove features based on a kill list. The default behaviour i) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_core10_sarek_2_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? GATK best-practices germline and somatic variant calling on human WGS/WES datasets.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)"}}, "target": "sarek", "target_idx": 5}
{"id": "schema_std_bacmodel_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacmodel", "assay": "bacmodel pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/bacmodel (Systems-based bacterial functional modeling pipeline)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,bam,bai": null, "patient,sample,vcf,status,cna": null, "sample_id,idat_red,idat_green,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/viralrecon --input samplesheet.csv (Assay: Viral genome sequencing on Oxford Nanopore MinION / GridION)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "noul_publishdir_directive_usage_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_scds_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use scds for doublet scoring (tools: scds)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scds": "Module to use scds for doublet scoring", "cellbender/removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "anndata/barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "hisat2/extractsplicesites": "Extracts splicing sites from a gtf files", "busco/plot": "BUSCO summary plot generation using the built-in 'busco --plot' command"}}, "target": "scds", "target_idx": 0}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_gatk_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/learnreadorientationmodel", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/learnreadorientationmodel, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK": null, "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk", "target_idx": 3}
{"id": "samplesheet_arch_rare_disease_trio_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/raredisease --input samplesheet.csv (Assay: Trio exome/genome sequencing (Proband, Mother, Father))", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_publishdir_directive_usage_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_23", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_dshbio_splitbed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split features in gzipped BED format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config", "bedtools_jaccard": "Calculate Jaccard statistic b/w two feature files.", "gsea_gsea": "run the Broad Gene Set Enrichment tool in GSEA mode", "dshbio_splitbed": "Split features in gzipped BED format"}}, "target": "dshbio_splitbed", "target_idx": 4}
{"id": "resource_affy_justrma_2", "category": "resource_profiling", "state": {"process": "AFFY_JUSTRMA", "tool": "affy/justrma", "description": "Read CEL files into an ExpressionSet and generate a matrix"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AFFY_JUSTRMA (Read CEL files into an ExpressionSet and generate a matrix) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_1_4", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,barcode": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_5_3", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Parse Biosciences Split-seq combinatorial barcoding.", "criteria": {"sample,bam": null, "sample,well,plate": null, "sample,fastq_1": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_artic_aligntrim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files. (tools: align_trim)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje", "iphop_predict": "Predict phage host using iPHoP", "samtools_ampliconclip": "Clips read alignments where they match BED file defined regions", "artic_aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "crabs_import": "In-house generated or curated data can be imported into CRABS."}}, "target": "artic_aligntrim", "target_idx": 3}
{"id": "mod_checkqc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A simple program to parse Illumina NGS data and check it for quality criteria (tools: checkqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkqc": null, "stardist": null, "concoct_concoct": null, "artic_aligntrim": null, "bclconvert": null}}, "target": "checkqc", "target_idx": 0}
{"id": "schema_std_methylseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "description": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/methylseq?", "criteria": {"sample,fastq_1,fastq_2,genome": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,fastq_1,fastq_2,strandedness,type": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,genome", "target_idx": 0}
{"id": "schema_std_metapep_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/metapep. Description: From metagenomes to epitopes and beyond.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/metapep.", "criteria": {"condition,type,microbiome_path,alleles,weights_path": null, "id,fasta": null, "patient,sample,vcf,status,cna": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "condition,type,microbiome_path,alleles,weights_path", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "noul_named_output_channel_access_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process output defined as `tuple val(meta), path('*.bam'), emit: bam` creates a named output channel accessible as `PROCESS.out.bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_riboseq_profiling_6_5", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC", "inputs": "Single-end ribosome protected RNA fragments (RPFs) with strandedness"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ribosome profiling (Ribo-seq) footprint sequencing input samplesheet?", "criteria": {"sample,fastq_1,strandedness": null, "sample,cdna_fasta": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_1_4", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,host_fasta": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_0_8", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_baysor_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Bayesian segmentation of spatial transcriptomics data. (tools: baysor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ilastik/multicut": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "cat/fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "ilastik/pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "hisat2/align": "Align RNA-Seq reads to a reference with HISAT2"}}, "target": "baysor/run", "target_idx": 3}
{"id": "resource_angsd_docounts_3", "category": "resource_profiling", "state": {"process": "ANGSD_DOCOUNTS", "tool": "angsd/docounts", "description": "Calculates base frequency statistics across reference positions from BAM."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOCOUNTS (Calculates base frequency statistics across reference positions from BAM.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_parabricks_rnafq2bam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool is the equivalent of fq2bam for RNA-Seq samples, receiving inputs in FASTQ format, performing alignment with the splice-aware STAR algorithm, optionally marking of duplicate reads, and outputting an aligned BAM file ready for variant and fusion calling. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks_rnafq2bam": "This tool is the equivalent of fq2bam for RNA-Seq samples, receiving inputs in FASTQ format, performing alignm", "csvtk_join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "gem2_gem2bedmappability": "Convert a mappability file to bedgraph format", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}}, "target": "parabricks_rnafq2bam", "target_idx": 0}
{"id": "mod_h5ad_removebackground_barcodes_cellbender_anndata_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use cellbender for empty droplet removal (tools: h5ad_removebackground_barcodes_cellbender_anndata)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "vg_construct": "Constructs a graph from a reference and variant calls or a multiple sequence alignment file", "picard_renamesampleinvcf": "changes name of sample in the vcf file", "h5ad_removebackground_barcodes_cellbender_anndata": "Use cellbender for empty droplet removal", "anndata_getsize": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}}, "target": "h5ad_removebackground_barcodes_cellbender_anndata", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_47", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_survivor_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter a vcf file based on size and/or regions to ignore (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pigz_compress": "Compresses files with pigz.", "survivor_filter": "Filter a vcf file based on size and/or regions to ignore", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "holodeck_mutate": "Generate a VCF of random mutations from a reference genome with holodeck", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "survivor_filter", "target_idx": 1}
{"id": "resource_bcftools_view_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_VIEW", "tool": "bcftools/view", "description": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_VIEW (View, subset and filter VCF or BCF files by position and filtering expression. C) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_fastq_1_0_6", "category": "samplesheet_schema", "state": {"field_name": "fastq_1", "datatype": "file_pattern", "description": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_1'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_34", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_staphscan_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: staphscan is a tool to screen genome assemblies of Staphylococcus aureus (tools: staphscan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "staphscan": "staphscan is a tool to screen genome assemblies of Staphylococcus aureus", "ngmaster": "Serotyping Neisseria gonorrhoeae assemblies", "mash/screen": "Screens query sequences against large sequence databases", "checkm/qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or "}}, "target": "staphscan", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_5_5", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Standard Paired-end Whole Genome Sequencing (WGS).", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_icountmini_metagene_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plot a metagene of cross-link events/sites around various transcriptomic landmarks. (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"icountmini/segment": "Formats a GTF file for use with iCount sigxls", "icountmini/metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks.", "vcf2db": "A tool to create a Gemini-compatible DB file from an annotated VCF", "peka": "Runs PEKA CLIP peak k-mer analysis", "segemehl/index": "Generate genome indices for segemehl align"}}, "target": "icountmini/metagene", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "FAIRE-seq / DNAse-seq open chromatin profiling", "data_format": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Metagenomic MAG assembly with comparative groups. Input files: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 0}
{"id": "mod_fastqutils_info_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs quality control of FASTQ files (tools: fastqutils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_datametrics": null, "fastqutils_info": null, "bamtofastq10x": null, "ariba_run": null, "fcsgx_rungx": null}}, "target": "fastqutils_info", "target_idx": 1}
{"id": "resource_arriba_arriba_0", "category": "resource_profiling", "state": {"process": "ARRIBA_ARRIBA", "tool": "arriba/arriba", "description": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARRIBA_ARRIBA (Arriba is a command-line tool for the detection of gene fusions from RNA-Seq dat) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_ncbitools_vecscreen_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NCBI tool for detecting vector contamination in nucleic acid sequences. This tool is older than NCBI's FCS-adaptor, which is for the same purpose (tools: ncbitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "paraclu": "Paraclu finds clusters in data attached to sequences.", "odgi/sort": "Apply different kind of sorting algorithms to a graph. The most prominent one is the PG-SGD sorting algorithm.", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "ncbitools/vecscreen": "NCBI tool for detecting vector contamination in nucleic acid sequences. This tool is older than NCBI's FCS-ada"}}, "target": "ncbitools/vecscreen", "target_idx": 4}
{"id": "field_constraint_sample_1_10", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "mod_stainwarpy_extractchannel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract a single channel image from multiplexed tissue images using stainwarpy (tools: stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vardictjava": null, "tif_registration_stainwarpy": null, "stainwarpy_transformsegmask": null, "stainwarpy_extractchannel": null, "gatk4_germlinecnvcaller": null}}, "target": "stainwarpy_extractchannel", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_1_3", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC", "inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,unite_fasta": null, "sample,bam": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_7", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_0_3", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "template": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,cpg,methylation": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_arcashla_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates. (tools: arcashla)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seq2hla": "Precision HLA typing and expression from RNA-seq data using seq2HLA", "t1k/run": "write your description here", "svtk/baftest": "Performs tests on BAF files", "pairtools/restrict": "Assign restriction fragments to pairs", "arcashla/extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}}, "target": "arcashla/extract", "target_idx": 4}
{"id": "noul_multiple_script_sections_invalid_9", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Multiple processes in the same workflow can write simultaneously to the exact same file in the work directory without conflict.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "resource_ataqv_ataqv_2", "category": "resource_profiling", "state": {"process": "ATAQV_ATAQV", "tool": "ataqv/ataqv", "description": "ataqv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_ATAQV (ataqv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_bwa_sampe_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert paired-end bwa SA coordinate files to SAM format (tools: bwa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa_aln": "Find SA coordinates of the input reads for bwa short-read mapping", "fgumi_codec": "Call CODEC consensus reads from a UMI-grouped BAM with fgumi", "bwa_sampe": "Convert paired-end bwa SA coordinate files to SAM format", "fgumi_sort": "Sorts a SAM or BAM file. Several sort orders are available, including coordinate,\nqueryname, and template-coor", "bwamem2_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "bwa_sampe", "target_idx": 2}
{"id": "samplesheet_arch_methylseq_bisulfite_0_1", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,cpg,methylation": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bedtools_coverage_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: computes both the depth and breadth of coverage of features in file B on the features in file A (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools_coverage": "computes both the depth and breadth of coverage of features in file B on the features in file A", "bedtools_genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a", "thermorawfileparser": "Parses a Thermo RAW file containing mass spectra to an open file format", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "bedtools_flank": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file."}}, "target": "bedtools_coverage", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_4_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from Agilent/Twist exome target capture", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from Agilent/Twist exome target capture?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bowtie_build_5", "category": "resource_profiling", "state": {"process": "BOWTIE_BUILD", "tool": "bowtie/build", "description": "Create bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE_BUILD (Create bowtie index for reference genome) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_bam_telomere_estimation_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TELOMERE_ESTIMATION", "modules": ["telseq", "telogator2", "telomerehunter", "custom/summarisetelomereestimation"], "description": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter"}, "question": {"type": "choice", "instructions": "How should BAM_TELOMERE_ESTIMATION (telseq, telogator2, telomerehunter, custom/summarisetelomereestimation) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_telomere_estimation": null, "Local subworkflow BAM_TELOMERE_ESTIMATION": null}}, "target": "Use nf-core subworkflow bam_telomere_estimation", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_0_2", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1,fastq_2": null, "sample,matrix,barcodes,features": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "mod_saltshaker_call_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mtDNA deletion and duplication calling downstream of mitosalt (tools: saltshaker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker_classify": "mtDNA deletion and duplication classification downstream of mitosalt", "sickle": "A windowed adaptive trimming tool for FASTQ files using quality", "saltshaker_call": "mtDNA deletion and duplication calling downstream of mitosalt", "gridss_call": "Run the GRIDSS variant calling step to identify structural variants from pre-processed and assembled alignment", "haplogrep3_classify": "classification into haplogroups"}}, "target": "saltshaker_call", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Parse Biosciences Split-seq combinatorial barcoding)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_pediatric_trio_somatic_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "data_format": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_chopper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter and trim long read data. (tools: zcat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chopper": "Filter and trim long read data.", "gtdbtk_gtdbtoncbimajorityvote": "Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy", "hhsuite_reformat": "Reformat a Multiple Sequence Alignment (MSA) file", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "chopper", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_2_4", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate", "pipeline": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/bacass) for Hybrid bacterial assembly combining short Illumina and long Nanopore reads. Input files: Illumina paired-end reads paired with Oxford Nanopore long reads per isolate.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "intent_build_pipeline_24", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "build_pipeline", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_3", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_0_1", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC", "inputs": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral amplicon sequencing with primers?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_eklipse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: tool for detection and quantification of large mtDNA rearrangements. (tools: eklipse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genomescope2": "Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical ", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "glimpse2_splitreference": "Tool to create a binary reference panel for quick reading time.", "mtnucratio": "A small Java tool to calculate ratios between MT and nuclear sequencing reads in a given BAM file.", "eklipse": "tool for detection and quantification of large mtDNA rearrangements."}}, "target": "eklipse", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_tn_1_5", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_1_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_ngscheckmate_fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determining whether sequencing data comes from the same individual by using SNP matching. This module generates vaf files for individual fastq file(s), ready for the vafncm module. (tools: ngscheckmate)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_mergevcfs": "Merges several vcf files", "custom_addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field", "ngscheckmate_fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "cellsnp_modea": "Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A ", "ngscheckmate_vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate"}}, "target": "ngscheckmate_fastq", "target_idx": 2}
{"id": "schema_std_hlatyping_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/hlatyping. Description: Precision HLA typing from next-generation sequencing data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/hlatyping.", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "sample,nuclear_image,spot_table,membrane_image": null, "ID,R1,R2,LongFastQ,Fast5": null}}, "target": "sample,fastq_1,fastq_2,bam,seq_type", "target_idx": 1}
{"id": "mod_autocycler_trim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim cluster assembly graphs to remove unsupported segments prior to resolution. (tools: autocycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler_trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "autocycler_subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "autocycler_compress": "Package candidate assemblies for clustering by Autocycler.", "hmmer_jackhmmer": "iterative searches to detect distant homologs by refining an HMM profile from hits", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "autocycler_trim", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_16", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_bio2zarr_vcf2zarrexplode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF(s) to intermediate columnar format (ICF) (tools: vcf2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "bio2zarr/vcf2zarrexplode": "Convert VCF(s) to intermediate columnar format (ICF)", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "prodigal": "Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene "}}, "target": "bio2zarr/vcf2zarrexplode", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_6_4", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Multiplexed Oxford Nanopore run with barcode demultiplexing input samplesheet?", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,barcode": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "resource_bwa_aln_3", "category": "resource_profiling", "state": {"process": "BWA_ALN", "tool": "bwa/aln", "description": "Find SA coordinates of the input reads for bwa short-read mapping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_ALN (Find SA coordinates of the input reads for bwa short-read mapping) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_high", "target_idx": 2}
{"id": "mod_quantmsutils_dianncfg_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate DIA-NN configuration arguments from enzyme and Unimod modification parameters.\nThis module uses quantms-utils to convert enzyme and modification specifications into DIA-NN-compatible command-line arguments.\nOnly supports Unimod modifications. For custom modifications, pass arguments directly to the DIANN module. (tools: quantms-utils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cooler_digest": "Generate fragment-delimited genomic bins", "quantmsutils_dianncfg": "Generate DIA-NN configuration arguments from enzyme and Unimod modification parameters.\nThis module uses quant", "midas_run": "A tool to estimate bacterial species abundance", "fgbio_filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "parsesdrf_convert": "Convert an SDRF (Sample and Data Relationship Format) file into a\npipeline-specific samplesheet/configuration "}}, "target": "quantmsutils_dianncfg", "target_idx": 1}
{"id": "resource_biscuit_pileup_4", "category": "resource_profiling", "state": {"process": "BISCUIT_PILEUP", "tool": "biscuit/pileup", "description": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call somatic variants"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_PILEUP (Computes cytosine methylation and callable SNV mutations, optionally in referenc) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_nonpareil_set_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualise metagenome redundancy curves in PNG format from multiple Nonpareil npo files in a single image (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clustalo_align": "Align sequences using Clustal Omega", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "ribotricer_detectorfs": "Accurate detection of short and long active ORFs using Ribo-seq data", "nonpareil_set": "Visualise metagenome redundancy curves in PNG format from multiple Nonpareil npo files in a single image", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}}, "target": "nonpareil_set", "target_idx": 3}
{"id": "samplesheet_arch_epigenomics_hic_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hic", "assay_type": "Hi-C chromosome conformation capture mapping", "data_format": "Paired-end proximity ligation FASTQs with restriction enzyme digestion specification"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,matrix,contacts": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay_type": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "data_format": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_bwameme_mem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA-MEME (tools: bwameme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwamem2/mem": "Performs fastq alignment to a fasta reference using BWA", "bwamem3/mem": "Align fastq reads to a fasta reference using bwa-mem3", "bwameme/mem": "Performs fastq alignment to a fasta reference using BWA-MEME", "trycycler/subsample": "Subsample a long-read sequencing fastq file for multiple assemblies", "cnvpytor/view": "view function to generate vcfs"}}, "target": "bwameme/mem", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_10", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_all101_createtaxdb_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for database. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]"}}, "target": "createtaxdb", "target_idx": 0}
{"id": "mod_eido_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert any PEP project or Nextflow samplesheet to any format (tools: eido)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf2zarr_explode": "Convert VCF(s) to intermediate columnar format", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "eido_convert": "Convert any PEP project or Nextflow samplesheet to any format", "bio2zarr_vcf2zarrconvert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster.", "minibwa_index": "Create a minibwa index for a reference genome"}}, "target": "eido_convert", "target_idx": 2}
{"id": "mod_dshbio_splitgff3_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split features in gzipped GFF3 format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio_filtergff3": null, "cnvnator_cnvnator": null, "liftoff": null, "fastani": null, "dshbio_splitgff3": null}}, "target": "dshbio_splitgff3", "target_idx": 4}
{"id": "noul_deprecated_dsl1_set_keyword_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `set` keyword is used in Nextflow DSL2 instead of `tuple` for channel declarations.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_fgumi_dedup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mark or remove PCR duplicates using UMI information with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metamaps/classify": "Strain-level metagenomic assignment", "fgumi/downsample": "Downsample a BAM by UMI family using streaming with fgumi", "bcftools/split": "Split a vcf file into files per chromosome", "fgbio/callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag.", "fgumi/dedup": "Mark or remove PCR duplicates using UMI information with fgumi"}}, "target": "fgumi/dedup", "target_idx": 4}
{"id": "mod_peddy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Manipulation, validation and exploration of pedigrees (tools: peddy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"resfinder_run": "ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteri", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization.", "somalier_relate": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs", "peddy": "Manipulation, validation and exploration of pedigrees"}}, "target": "peddy", "target_idx": 4}
{"id": "mod_gt_stat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GenomeTools gt-stat utility to show statistics about features contained in GFF3 files (tools: gt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom/geneticmapconvert": null, "agat/convertspgff2tsv": null, "holodeck/methylate": null, "gt/stat": null, "agat/convertgff2bed": null}}, "target": "gt/stat", "target_idx": 3}
{"id": "schema_std_genomeqc_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeqc", "assay": "genomeqc pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/genomeqc (Compare the quality of multiple genomes, along with their an)?", "criteria": {"fasta,assembly,ncbi,gff,fastq": null, "sample_id,name,description,path,path_2": null, "sample,bam,bai,cram,crai": null, "sample,fastq_1,fastq_2,replicate,control": null}}, "target": "fasta,assembly,ncbi,gff,fastq", "target_idx": 0}
{"id": "mod_snpdists_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pairwise SNP distance matrix from a FASTA sequence alignment (tools: snpdists)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sigprofiler": "mutational signature deconvolution of cancer cells", "freebayes": "A haplotype-based variant detector", "snpdists": "Pairwise SNP distance matrix from a FASTA sequence alignment", "eigenstratdatabasetools_eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset.", "finaletoolkit_wps": "Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription"}}, "target": "snpdists", "target_idx": 2}
{"id": "schema_std_chipseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/chipseq", "assay": "chipseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/chipseq (ChIP-seq peak-calling, QC and differential analysis pipeline)?", "criteria": {"sample,bam,vcf,rna_matrix,hto_matrix": null, "family_id,sample,file_path,hpo_terms,sex": null, "sample,trait,pascal,twas,additional_sources": null, "sample,fastq_1,fastq_2,replicate,antibody": null}}, "target": "sample,fastq_1,fastq_2,replicate,antibody", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_0_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "resource_agat_spextractsequences_4", "category": "resource_profiling", "state": {"process": "AGAT_SPEXTRACTSEQUENCES", "tool": "agat/spextractsequences", "description": "This script extracts sequences in fasta format according to features described\nin a gff file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPEXTRACTSEQUENCES (This script extracts sequences in fasta format according to features described\ni) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_invalid_process_communication_via_globals_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, processes communicate by directly declaring global variables inside the script block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/smrnaseq", "assay_type": "Small RNA / miRNA sequencing", "data_format": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end 50bp miRNA reads with 3-prime adapter?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,mirna_id": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "resource_blobtk_create_0", "category": "resource_profiling", "state": {"process": "BLOBTK_CREATE", "tool": "blobtk/create", "description": "Creates a minimal blobdir."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_CREATE (Creates a minimal blobdir.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_2_4", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC", "inputs": "Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "schema_std_molkart_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/molkart", "assay": "molkart pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/molkart (A pipeline for processing Molecular Cartography data from Re)?", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "sample,nuclear_image,spot_table,membrane_image": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,bam,bai,cram,crai": null}}, "target": "sample,nuclear_image,spot_table,membrane_image", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_6_5", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns are standard for Longitudinal cancer monitoring across multiple timepoints input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,bam": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_phaseimpute_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A bioinformatics pipeline to phase and impute genetic data. Topics: genomics, genotype, imputation, low-pass-sequencing, phasing. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina"}}, "target": "phaseimpute", "target_idx": 2}
{"id": "pipe_all101_hadge_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Comprehensive pipeline for donor demultiplexing in single cell. Topics: cell-hashing, deconvolution, demultiplexing, donor-assignment, donor-deconvolution, genetic-demultiplexing. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"crisprseq": null, "scrnaseq": null, "spatialaxe": null, "hadge": null, "readsimulator": null}}, "target": "hadge", "target_idx": 3}
{"id": "intent_debug_error_12", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "debug_error", "target_idx": 1}
{"id": "mod_genmod_models_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: annotate models of inheritance (tools: genmod)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmod_models": "annotate models of inheritance", "seqtk_rename": "Rename sequence names in FASTQ or FASTA files.", "sratools_fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA).", "macsyfinder_download": "Download MacSyFinder models using msf_data", "genmod_compound": "Score compounds"}}, "target": "genmod_models", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_1_2", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "resource_biscuit_index_3", "category": "resource_profiling", "state": {"process": "BISCUIT_INDEX", "tool": "biscuit/index", "description": "Indexes a reference genome for use with Biscuit"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_INDEX (Indexes a reference genome for use with Biscuit) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_tumor_only_6_4", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Tumor-only somatic variant calling without matched normal input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnafusion --input samplesheet.csv (Assay: RNA gene fusion detection (Arriba, STAR-Fusion))", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnafusion, determine the input samplesheet column structure for: RNA gene fusion detection (Arriba, STAR-Fusion).", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_deeptools_multibigwigsummary_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes the average scores for each of the files in every genomic region (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_split": null, "deeptools_multibigwigsummary": null, "ucsc_wigtobigwig": null, "deeptools_bigwigcompare": null, "transrate": null}}, "target": "deeptools_multibigwigsummary", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_1_2", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities", "pipeline": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null, "sample,bam": null}}, "target": "sample,bam", "target_idx": 3}
{"id": "noul_subworkflow_structural_blocks_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Workflows in Nextflow DSL2 define inputs with `take:`, core execution with `main:`, and outputs with `emit:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_viral_ont_single_8_1", "category": "samplesheet_schema", "state": {"assay": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "first_step": "NANOPLOT", "inputs": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns are standard for viral amplicon sequencing?", "criteria": {"sample,fasta": null, "sample,vcf": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "intent_ask_question_22", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "field_constraint_sample_0_6", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"format: file-path": null, "type: integer": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "resource_amulety_antiberty_2", "category": "resource_profiling", "state": {"process": "AMULETY_ANTIBERTY", "tool": "amulety/antiberty", "description": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMULETY_ANTIBERTY (A module to create antiberty embeddings of antibody (BCR) amino acid sequences u) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_ampcombi_4", "category": "resource_profiling", "state": {"process": "AMPCOMBI", "tool": "ampcombi", "description": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI (A tool to parse and summarise results from antimicrobial peptides tools and pres) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bedtools_shuffle_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SHUFFLE", "tool": "bedtools/shuffle", "description": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a genome file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SHUFFLE (bedtools shuffle will randomly permute the genomic locations of a feature file a) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_11", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_longphase_haplotag_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modifications for Nanopore and PacBio platforms. (tools: longphase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fqtk": "Demultiplex fastq files", "longphase_haplotag": "LongPhase is an ultra-fast program for simultaneously co-phasing SNPs, small indels, large SVs, and (5mC) modi", "autocycler_compress": "Package candidate assemblies for clustering by Autocycler.", "hlala_typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "autocycler_combine": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}}, "target": "longphase_haplotag", "target_idx": 1}
{"id": "local_subworkflow_preparereports_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPAREREPORTS (custom/preparereports, multiqc).", "criteria": {"Use nf-core subworkflow preparereports": null, "Local subworkflow PREPAREREPORTS": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 1}
{"id": "mod_glimpse_concordance_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the high-coverage dataset. (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "glimpse2_ligate": "Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks tha", "fmhfunprofiler": "Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references.", "glimpse_concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "gatk4_concordance": "Evaluate concordance of an input VCF against a validated truth VCF"}}, "target": "glimpse_concordance", "target_idx": 3}
{"id": "noul_channel_collect_operator_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_19", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_gmmdemux_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MULTI-seq). (tools: gmmdemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bff": "Generating cell hashing calls from a matrix of count data.", "gatk4/svcluster": "Clusters structural variants based on coordinates, event type, and supporting algorithms", "foldmason/createdb": "Creates a database for Foldmason.", "demuxem": "Demultiplexing cell nucleus hashing data, using the estimated antibody background probability.", "gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU"}}, "target": "gmmdemux", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_1_23", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_glimpse_chunk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Defines chunks where to run imputation (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chewbbaca/createschema": null, "bamtools/split": null, "t1k/run": null, "glimpse/chunk": null, "glimpse2/chunk": null}}, "target": "glimpse/chunk", "target_idx": 3}
{"id": "mod_cellranger_count_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expression. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellranger_count": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Gene Expressi", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "mosdepth": "Calculates genome-wide sequencing coverage.", "sylph_profile": "Sylph profile command for taxonoming profiling", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "cellranger_count", "target_idx": 0}
{"id": "mod_arcane_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane (tools: arcane)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/rsempreparereference": null, "anndata/barcodes": null, "anndata/getsize": null, "genmap/index": null, "arcane/filter": null}}, "target": "arcane/filter", "target_idx": 4}
{"id": "mod_gnu_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split a file into consecutive or interleaved sections (tools: gnu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gnu_split": "Split a file into consecutive or interleaved sections", "bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "bcftools_split": "Split a vcf file into files per chromosome", "pharmcat_matcher": "The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to", "tif_registration_stainwarpy": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy"}}, "target": "gnu_split", "target_idx": 0}
{"id": "samplesheet_arch_ont_metagenome_single_1_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fasta": null, "sample,bam": null, "sample,fastq_1,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "resource_bcftools_pluginscatter_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSCATTER", "tool": "bcftools/pluginscatter", "description": "Split VCF by chunks or regions, creating multiple VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSCATTER (Split VCF by chunks or regions, creating multiple VCFs.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_gunc_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Detection of Chimerism and Contamination in Prokaryotic Genomes (tools: gunc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pharmcat/vcfpreprocessor": null, "gunc/run": null, "gunc/mergecheckm": null, "hlala/typing": null, "biohansel": null}}, "target": "gunc/run", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_11", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_pe250?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_preseq_ccurve_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Software for predicting library complexity and genome coverage in high-throughput sequencing (tools: preseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/bwaindex": "Create BWA index for reference genome", "raw2ometiff": "write your description here", "preseq/ccurve": "Software for predicting library complexity and genome coverage in high-throughput sequencing", "nonpareil/nonpareil": "Calculate metagenome redundancy curve from FASTQ files", "bam_qc_rnaseq": "Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC "}}, "target": "preseq/ccurve", "target_idx": 2}
{"id": "resource_autocycler_combine_4", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMBINE", "tool": "autocycler/combine", "description": "Merge resolved cluster assemblies into final consensus outputs with Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMBINE (Merge resolved cluster assemblies into final consensus outputs with Autocycler.) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_bam_0_14", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "mod_shasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using DNA reads generated by Oxford Nanopore flow cells as input. Please note Assembler is design to focus on speed, so assembly may be considered somewhat non-deterministic as final assembly may vary across executions. See https://github.com/chanzuckerberg/shasta/issues/296. (tools: shasta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusionreport/detect": "fusionreport_detect", "shasta": "The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using DNA reads g", "chopper": "Filter and trim long read data.", "vsearch/sintax": "Taxonomic classification using the sintax algorithm.", "filtlong": "Filtlong filters long reads based on quality measures or short read data."}}, "target": "shasta", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral amplicon sequencing with primers", "data_format": "Paired-end tiled viral amplicon FASTQs per clinical swab sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Viral amplicon sequencing with primers?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_36", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "pipe_all101_reportho_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for ortholog. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "metapep": "From metagenomes to epitopes and beyond", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra"}}, "target": "reportho", "target_idx": 6}
{"id": "noul_channel_filter_operator_17", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_custom_orfcollapse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom/orfmerge` (coordinate-based catalogue),\n`bedtools/getfasta` + `seqkit/translate` (AA FASTA keyed by orf_id), and\n`mmseqs/easycluster` (AA clusters) upstream.\n\nThe coordinate-based merge in `custom/orfmerge` only groups ORFs that overlap\non the genome, so the same micropeptide encoded at several distinct,\nnon-overlapping loci (typically repetitive regions) survives as separate rows.\nThis adopts the peptide-level deduplication and 0.9 amino-acid-similarity\nthreshold of the GENCODE Ribo-seq ORF consolidation (Mudge et al. 2022,\nNat Biotechnol, doi:10.1038/s41587-022-01369-0; gencode-riboseqORFs\ncollapse_cutoff 0.9), implemented here with MMseqs2 sequence-identity\nclustering rather than that tool's longest-shared-string / P-site-overlap\nmetric. Small ORFs (`aa_length` <= `--smorf-max-aa`, default 100) are clustered by\namino-acid identity upstream and this module folds each multi-member cluster\ndown to one representative.\n\nOnly small ORFs are collapsed; larger ORFs are passed through untouched.\nEligibility is the catalogue's `is_smorf` flag, independent of `orf_class`, so\na short uORF and a short novel ORF are both candidates; `--smorf-max-aa`\nre-derives the flag and aborts on disagreement. Among the members of a cluster\nthe representative is chosen by class specificity, then longest aa_length,\nthen orf_id, so the result does not depend on which sequence MMseqs2 labelled\nthe cluster representative. Catalogue row order is preserved; dropped members fold their\n`called_by_<caller>` / `score_<caller>` evidence, `n_samples` / `samples`\nrecurrence and gene mappings into the survivor. (tools: orfcollapse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"paraphrase": null, "orfm": null, "custom_orfcollapse": null, "fgumi_group": null, "gedi_price": null}}, "target": "custom_orfcollapse", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_7", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_plink_indep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produce a pruned subset of markers that are in approximate linkage equilibrium with each other. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink_genome": null, "plink_bmerge": null, "plink_indep": null, "spring_compress": null, "kalign_align": null}}, "target": "plink_indep", "target_idx": 2}
{"id": "resource_amplify_predict_2", "category": "resource_profiling", "state": {"process": "AMPLIFY_PREDICT", "tool": "amplify/predict", "description": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPLIFY_PREDICT (AMPlify is an attentive deep learning model for antimicrobial peptide prediction) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bedtools_intersect_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_INTERSECT", "tool": "bedtools/intersect", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_INTERSECT (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_bam_tumor_only_somatic_variant_calling_gatk_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a single tumor sample using mutect2 tumor only mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk": null, "Leave them out": null, "Local subworkflow BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_fgumi_group_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template, and then templates are sorted by the 5' mapping positions\nof the reads from the template. Reads that have the same end positions are then sub-grouped\nby UMI sequence. This is a high-performance replacement for fgbio GroupReadsByUmi. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hhsuite/reformat": "Reformat a Multiple Sequence Alignment (MSA) file", "cellranger/mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command.", "fgbio/zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "fgbio/callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "fgumi/group": "Groups reads together that appear to have come from the same original molecule.\nReads are grouped by template,"}}, "target": "fgumi/group", "target_idx": 4}
{"id": "samplesheet_arch_mira_influenza_sc2_4_3", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "template": "custom/mira-nf"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end surveillance FASTQs from respiratory pathogen panels?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_svdb_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The merge module merges structural variants within one or more vcf files. (tools: svdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "caddsv_get": "Download CADD-SV annotation resources or SegmentNT model files.", "clippy": "Runs the Clippy CLIP peak caller", "svdb_merge": "The merge module merges structural variants within one or more vcf files.", "refsolver_compare": "Compare two sequence dictionaries (headers/references) using ref-solver"}}, "target": "svdb_merge", "target_idx": 3}
{"id": "mod_wittyer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A large variant benchmarking tool analogous to hap.py for small variants. (tools: wittyer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"holodeck/eval": "Evaluate alignment accuracy of holodeck-simulated reads", "holodeck/mutate": "Generate a VCF of random mutations from a reference genome with holodeck", "blobtk/plot": "Creates differing styles of blobplots depending on provided arguments.", "cellranger/vdj": "Module to use Cell Ranger's pipelines analyze sequencing data produced from Chromium Single Cell Immune Profil", "wittyer": "A large variant benchmarking tool analogous to hap.py for small variants."}}, "target": "wittyer", "target_idx": 4}
{"id": "samplesheet_arch_atacseq_replicates_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "assay_type": "ATAC-seq chromatin accessibility with biological replicates", "data_format": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end Tn5 transposed FASTQs across conditions and replicates?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 2}
{"id": "resource_bamcmp_2", "category": "resource_profiling", "state": {"process": "BAMCMP", "tool": "bamcmp", "description": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For instance, filtering out mouse reads from patient derived xenograft mouse models (PDX)."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCMP (Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and ) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_19", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_pairtools_dedup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find and remove PCR/optical duplicates (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"helitronscanner/scan": null, "sentieon/dedup": null, "cnvkit/fix": null, "umitools/group": null, "pairtools/dedup": null}}, "target": "pairtools/dedup", "target_idx": 4}
{"id": "mod_ldak_kvikstep1_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run LDAK-KVIK step 1 to fit the genome-wide model and emit the minimal prediction artifact tuple consumed by ldak/kvikstep2 (tools: ldak6)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/databases": "Download an mmseqs-formatted database", "ldak/thinpredictors": "Run linkage disequilibrium (LD) pruning with linkage disequilibrium-adjusted kinship (LDAK) to create a thinne", "cooler/merge": "Merge multiple coolers with identical axes", "ldak/kvikstep1": "Run LDAK-KVIK step 1 to fit the genome-wide model and emit the minimal prediction artifact tuple consumed by l", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs"}}, "target": "ldak/kvikstep1", "target_idx": 3}
{"id": "core_tool_kraken2_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Exact k-mer matching taxonomic classifier mapping metagenomic reads to bacterial and viral reference genomes with lowest common ancestor algorithm.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"metaphlan": null, "centrifuge": null, "motus": null, "diamond": null, "kraken2": null}}, "target": "kraken2", "target_idx": 4}
{"id": "noul_channel_mix_operator_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_blobtk_create_5", "category": "resource_profiling", "state": {"process": "BLOBTK_CREATE", "tool": "blobtk/create", "description": "Creates a minimal blobdir."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_CREATE (Creates a minimal blobdir.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_3_0", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Environmental community metatranscriptomics de novo assembly with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,environment": null, "sample,fastq_1,fastq_2": null, "sample,rrna_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 0}
{"id": "mod_singlem_dbdownload_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download the SingleM metapackage database used for metagenome profiling (tools: singlem)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "hamronization_deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "repeatmasker_rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "singlem_dbdownload": "Download the SingleM metapackage database used for metagenome profiling", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD"}}, "target": "singlem_dbdownload", "target_idx": 3}
{"id": "pipe_all101_magmap_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Best-practice analysis pipeline for mapping reads to a (large) collections of genomes. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"readsimulator": null, "coproid": null, "magmap": null, "scnanoseq": null, "crisprseq": null}}, "target": "magmap", "target_idx": 2}
{"id": "samplesheet_arch_atacseq_replicates_0_1", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,bam": null, "sample,bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "mod_ultra_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment (tools: ultra)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra_align": null, "ultra_index": null, "biscuit_index": null, "clair3": null, "custom_tabulartogseachip": null}}, "target": "ultra_index", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_0_0", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents). Input files: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage.", "question": {"type": "choice", "instructions": "Which columns are standard for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) input samplesheet?", "criteria": {"family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_fq_generate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: fq generate is a FASTQ file pair generator. It creates two reads, formatting names as described by Illumina. While generate creates \"valid\" FASTQ reads, the content of the files are completely random. The sequences do not align to any genome. This requires a seed (--seed) to be supplied in ext.args. (tools: fq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/csq": "bcftools Haplotype-aware consequence caller", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "fq/generate": "fq generate is a FASTQ file pair generator. It creates two reads, formatting names as described by Illumina. W"}}, "target": "fq/generate", "target_idx": 4}
{"id": "noul_container_environment_specification_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_idemux_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex paired-end FASTQ files from QuantSeq-Pool (tools: idemux)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"viber": null, "mgikit/demultiplex": null, "bcl2fastq": null, "custom/orfmerge": null, "idemux": null}}, "target": "idemux", "target_idx": 4}
{"id": "schema_std_hlatyping_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hlatyping", "assay": "hlatyping pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/hlatyping (Precision HLA typing from next-generation sequencing data)?", "criteria": {"sample,fastq_1,fastq_2,bam,seq_type": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,seed": null, "vcf,fasta,genome,site,source": null}}, "target": "sample,fastq_1,fastq_2,bam,seq_type", "target_idx": 0}
{"id": "resource_bamreadcount_4", "category": "resource_profiling", "state": {"process": "BAMREADCOUNT", "tool": "bamreadcount", "description": "bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMREADCOUNT (bam-readcount is a utility that runs on a BAM or CRAM file and generates low-lev) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_arriba_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data. (tools: arriba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"starfusion/detect": "Fast and Accurate Fusion Transcript Detection from RNA-Seq", "igv/js": "igv.js is an embeddable interactive genome visualization component", "fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "mgikit/demultiplex": "Demultiplex MGI fastq files", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}}, "target": "arriba/download", "target_idx": 4}
{"id": "resource_blat_4", "category": "resource_profiling", "state": {"process": "BLAT", "tool": "blat", "description": "Queries a sequence subject"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAT (Queries a sequence subject) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_blobtk_plot_0", "category": "resource_profiling", "state": {"process": "BLOBTK_PLOT", "tool": "blobtk/plot", "description": "Creates differing styles of blobplots depending on provided arguments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_PLOT (Creates differing styles of blobplots depending on provided arguments.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bismark_summary_2", "category": "resource_profiling", "state": {"process": "BISMARK_SUMMARY", "tool": "bismark/summary", "description": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_SUMMARY (Uses Bismark report files of several samples in a run folder to generate a graph) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_genomeassembler_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for genome-assembly analysis? Specific context: Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads. Topics: genome-assembly. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]"}}, "target": "genomeassembler", "target_idx": 4}
{"id": "field_constraint_sex_3_10", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "pipe_all101_rnadnavar_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pipeline for RNA and DNA integrated analysis for somatic mutation detection. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"createpanelrefs": null, "readsimulator": null, "demultiplex": null, "bamtofastq": null, "rnadnavar": null, "funcscan": null, "riboseq": null, "rnaseq": null}}, "target": "rnadnavar", "target_idx": 4}
{"id": "mod_ragtag_patch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Homology-based assembly patching: Make continuous joins and fill gaps in 'target.fa' using sequences from 'query.fa' (tools: ragtag)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macse_refinealignment": "improves the input nucleotide alignment in a codon-aware manner", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "ragtag_patch": "Homology-based assembly patching: Make continuous joins and fill gaps in 'target.fa' using sequences from 'que", "pypgx_runngspipeline": "PyPGx pharmacogenomics genotyping pipeline for NGS data."}}, "target": "ragtag_patch", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_12", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "field_constraint_phenotype_1_11", "category": "samplesheet_schema", "state": {"column": "phenotype", "purpose": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'phenotype' (Affection status in clinical trio / family analysis).", "criteria": {"enum: [normal, tumor]": null, "type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "resource_biscuit_mergecg_4", "category": "resource_profiling", "state": {"process": "BISCUIT_MERGECG", "tool": "biscuit/mergecg", "description": "Merges methylation information for opposite-strand C's in a CpG context"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_MERGECG (Merges methylation information for opposite-strand C's in a CpG context) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_motus_downloaddb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download the mOTUs database (tools: motus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "hamronization/abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "haplogrep3/classify": "classification into haplogroups", "motus/downloaddb": "Download the mOTUs database", "sentieon/readwriter": "Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality S"}}, "target": "motus/downloaddb", "target_idx": 3}
{"id": "mod_gatk4spark_applybqsr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply base quality score recalibration (BQSR) to a bam file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metabuli_build": null, "picrust2_pipeline": null, "gatk4spark_applybqsr": null, "ascat": null, "bamclipper": null}}, "target": "gatk4spark_applybqsr", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_8_2", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_0_3", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "mod_deeptools_plotfingerprint_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: plots cumulative reads coverages by BAM file (tools: deeptools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/rsemcalculateexpression": "Calculate expression with RSEM", "deeptools/plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "deeptools/plotfingerprint": "plots cumulative reads coverages by BAM file", "purecn/normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as", "krona/ktimporttaxonomy": "KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot."}}, "target": "deeptools/plotfingerprint", "target_idx": 2}
{"id": "resource_beagle5_beagle_5", "category": "resource_profiling", "state": {"process": "BEAGLE5_BEAGLE", "tool": "beagle5/beagle", "description": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEAGLE5_BEAGLE (Beagle v5.5 is a software package for phasing genotypes and for imputing ungenot) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_fgumi_simplexmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gffread": null, "fgumi/simplexmetrics": null, "fgumi/clip": null, "caalm/caalm": null, "fgumi/correct": null}}, "target": "fgumi/simplexmetrics", "target_idx": 1}
{"id": "mod_stringtie_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges the annotation gtf file and the stringtie output gtf files (tools: stringtie2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mapdamage2": "Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads ge", "bamutil/clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "bedtools/merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "stringtie/merge": "Merges the annotation gtf file and the stringtie output gtf files"}}, "target": "stringtie/merge", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_8", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "pipe_all101_pathogensurveillance_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Surveillance of pathogens using population genomics and sequencing. Topics: biosurveillance, pathogen-identification. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T"}}, "target": "pathogensurveillance", "target_idx": 3}
{"id": "schema_std_bacass_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "assay": "bacass pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/bacass (Simple bacterial assembly and annotation pipeline)?", "criteria": {"sample,type,level,msfile": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,fasta,protein,gbk,gff": null}}, "target": "ID,R1,R2,LongFastQ,Fast5", "target_idx": 2}
{"id": "resource_bedtools_unionbedg_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_UNIONBEDG", "tool": "bedtools/unionbedg", "description": "Combines multiple BedGraph files into a single file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_UNIONBEDG (Combines multiple BedGraph files into a single file) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_sourmash_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a database of sourmash signatures (a group of FracMinHash sketches) to be used as references. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/index": "Create a database of sourmash signatures (a group of FracMinHash sketches) to be used as references.", "sourmash/pairwise": "Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch.", "sourmash/taxannotate": "Annotate list of metagenome members (based on sourmash signature matches) with taxonomic information.", "custom/tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq"}}, "target": "sourmash/index", "target_idx": 0}
{"id": "pipe_all101_differentialabundance_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq. Topics: atac-seq, chip-seq, deseq2, differential-abundance, differential-expression, gsea. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]"}}, "target": "differentialabundance", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_1_2", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin", "pipeline": "nf-core/chipseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "pipe_all101_pacvar_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for alignment. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]"}}, "target": "pacvar", "target_idx": 4}
{"id": "mod_sourmash_sketch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a signature (a group of FracMinHash sketches) of a sequence using sourmash (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sourmash/compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "sourmash/gather": "Search a metagenome sourmash signature against one or many reference databases and return the minimum set of g", "sourmash/sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "ribodetector": "Accurate and rapid RiboRNA sequences Detector based on deep learning", "kaiju/mergeoutputs": "Merge two tab-separated output files of Kaiju and Kraken in the column format"}}, "target": "sourmash/sketch", "target_idx": 2}
{"id": "field_constraint_bai_1_4", "category": "samplesheet_schema", "state": {"column": "bai", "purpose": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bai' (Companion BAM index file).", "criteria": {"pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_2_5", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_nonpareil_curve_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualise metagenome redundancy curve in PNG format from a single Nonpareil npo file (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nonpareil_curve": "Visualise metagenome redundancy curve in PNG format from a single Nonpareil npo file", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "deepvariant_makeexamples": "Transforms the input alignments to a format suitable for the deep neural network variant caller", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "ucsc_bigwigaverageoverbed": "compute average score of bigwig over bed file"}}, "target": "nonpareil_curve", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_5_3", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Single-end Oxford Nanopore direct RNA.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fast5": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "schema_std_pacvar_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pacvar", "assay": "pacvar pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/pacvar (Longread PacBio sequencing processing for WGS and PureTarget)?", "criteria": {"sample,bam,pbi,fail,repeat_id": null, "id,taxid,fasta_dna,fasta_aa": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null}}, "target": "sample,bam,pbi,fail,repeat_id", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_33", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnafusion) for RNA gene fusion detection (Arriba, STAR-Fusion). Input files: Paired-end oncology RNA-seq reads for chimeric transcript discovery.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnafusion, determine the input samplesheet column structure for: RNA gene fusion detection (Arriba, STAR-Fusion).", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fusion_bed": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "resource_barrnap_2", "category": "resource_profiling", "state": {"process": "BARRNAP", "tool": "barrnap", "description": "barrnap uses a hmmer profile to find rrnas in reads or contig fasta files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BARRNAP (barrnap uses a hmmer profile to find rrnas in reads or contig fasta files) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_ariba_getref_1", "category": "resource_profiling", "state": {"process": "ARIBA_GETREF", "tool": "ariba/getref", "description": "Download and prepare database for Ariba analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARIBA_GETREF (Download and prepare database for Ariba analysis) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "intent_ask_question_21", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "ask_question": null, "prepare_data": null, "debug_error": null}}, "target": "ask_question", "target_idx": 1}
{"id": "resource_bedtools_closest_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_CLOSEST", "tool": "bedtools/closest", "description": "For each feature in A, finds the closest feature (upstream or downstream) in B."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_CLOSEST (For each feature in A, finds the closest feature (upstream or downstream) in B.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_pangenome_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for pangenome. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "metapep": "From metagenomes to epitopes and beyond", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]"}}, "target": "pangenome", "target_idx": 5}
{"id": "field_constraint_sex_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"format: file-path": null, "pattern: ^\\S+\\.gz$": null, "type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 3}
{"id": "resource_artic_minion_3", "category": "resource_profiling", "state": {"process": "ARTIC_MINION", "tool": "artic/minion", "description": "Run the alignment/variant-call/consensus logic of the artic pipeline"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_MINION (Run the alignment/variant-call/consensus logic of the artic pipeline) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_5_2", "category": "samplesheet_schema", "state": {"assay": "Single-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Single-end FASTQ reads per library", "pipeline": "nf-core/rnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Single-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "pipe_core10_eager_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Archaeological skeletal sample sequencing for DNA degradation estimation, deamination analysis, and mitochondrial consensus reconstruction.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar"}}, "target": "eager", "target_idx": 3}
{"id": "noul_retry_errorstrategy_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "pipe_all101_ampliseq_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Amplicon sequencing analysis workflow using DADA2 and QIIME2. Topics: 16s, 18s, amplicon-sequencing, edna, illumina, iontorrent. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "metapep": "From metagenomes to epitopes and beyond"}}, "target": "ampliseq", "target_idx": 4}
{"id": "subworkflow_pkg_mmseqs_contig_taxonomy_2", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_CONTIG_TAXONOMY", "modules": ["mmseqs/databases", "mmseqs/createdb", "mmseqs/taxonomy", "mmseqs/createtsv"], "description": "Assign taxonomy to contigs using the MMseqs2 workflow."}, "question": {"type": "choice", "instructions": "How should MMSEQS_CONTIG_TAXONOMY (mmseqs/databases, mmseqs/createdb, mmseqs/taxonomy, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Use nf-core subworkflow mmseqs_contig_taxonomy": null, "Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow MMSEQS_CONTIG_TAXONOMY": null}}, "target": "Use nf-core subworkflow mmseqs_contig_taxonomy", "target_idx": 0}
{"id": "resource_agat_convertgff2bed_0", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTGFF2BED", "tool": "agat/convertgff2bed", "description": "Takes a GFF3 file and converts to a bed12 file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTGFF2BED (Takes a GFF3 file and converts to a bed12 file) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "local_subworkflow_nextclade_0_3", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should NEXTCLADE (nextclade/run) be built?", "criteria": {"Leave them out": null, "Use nf-core subworkflow nextclade": null, "Keep the modules in the main workflow": null, "Local subworkflow NEXTCLADE": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 3}
{"id": "mod_svtyper_svtyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SVTyper performs breakpoint genotyping of structural variants (SVs) using whole genome sequencing data (tools: svtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtyper/svtyper": "SVTyper performs breakpoint genotyping of structural variants (SVs) using whole genome sequencing data", "caddsv/get": "Download CADD-SV annotation resources or SegmentNT model files.", "amplify/predict": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction.", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "samclip": "Filters SAM/BAM/CRAM files for soft and hard clipped alignments"}}, "target": "svtyper/svtyper", "target_idx": 0}
{"id": "schema_std_diseasemodulediscovery_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/diseasemodulediscovery", "description": "A pipeline for network-based disease module identification.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/diseasemodulediscovery?", "criteria": {"id,fasta": null, "seeds,network,perturbed_networks": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "seeds,network,perturbed_networks", "target_idx": 1}
{"id": "pipe_all101_pairgenomealign_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results. Topics: comparative-genomics, dot-plot, genomics, last, pairwise-alignment, synteny. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralrecon": null, "marsseq": null, "proteinfold": null, "genomeqc": null, "pairgenomealign": null, "hicar": null, "nanostring": null, "airrflow": null}}, "target": "pairgenomealign", "target_idx": 4}
{"id": "noul_workflow_completion_lifecycle_hook_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "resource_bcftools_pluginscatter_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSCATTER", "tool": "bcftools/pluginscatter", "description": "Split VCF by chunks or regions, creating multiple VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSCATTER (Split VCF by chunks or regions, creating multiple VCFs.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}